diff --git a/.vscode/launch.json b/.vscode/launch.json index 793165a..bded3f8 100644 --- a/.vscode/launch.json +++ b/.vscode/launch.json @@ -36,181 +36,60 @@ ], }, { - "name": "-------- OLS --------", - }, - { - "name": "CRYPTO OLS (rolling)", - "type": "debugpy", - "request": "launch", - "python": "/home/oleg/.pyenv/python3.12-venv/bin/python", - "program": "${workspaceFolder}/research/backtest.py", - "args": [ - "--config=${workspaceFolder}/configuration/ols.cfg", - "--instruments=ADA-USDT:CRYPTO:BNBSPOT,SOL-USDT:CRYPTO:BNBSPOT", - "--date_pattern=20250605", - "--result_db=${workspaceFolder}/research/results/crypto/%T.ols.ADA-SOL.20250605.crypto_results.db", - ], - "env": { - "PYTHONPATH": "${workspaceFolder}/lib" - }, - "console": "integratedTerminal" - }, - { - "name": "CRYPTO OLS (optimized)", - "type": "debugpy", - "request": "launch", - "python": "/home/oleg/.pyenv/python3.12-venv/bin/python", - "program": "${workspaceFolder}/research/backtest.py", - "args": [ - "--config=${workspaceFolder}/configuration/ols-opt.cfg", - "--instruments=ADA-USDT:CRYPTO:BNBSPOT,SOL-USDT:CRYPTO:BNBSPOT", - "--date_pattern=20250605", - "--result_db=${workspaceFolder}/research/results/crypto/%T.ols-opt.ADA-SOL.20250605.crypto_results.db", - ], - "env": { - "PYTHONPATH": "${workspaceFolder}/lib" - }, - "console": "integratedTerminal" - }, - // { - // "name": "CRYPTO OLS (expanding)", - // "type": "debugpy", - // "request": "launch", - // "python": "/home/oleg/.pyenv/python3.12-venv/bin/python", - // "program": "${workspaceFolder}/research/backtest.py", - // "args": [ - // "--config=${workspaceFolder}/configuration/ols-exp.cfg", - // "--instruments=ADA-USDT:CRYPTO:BNBSPOT,SOL-USDT:CRYPTO:BNBSPOT", - // "--date_pattern=20250605", - // "--result_db=${workspaceFolder}/research/results/crypto/%T.ols-exp.ADA-SOL.20250605.crypto_results.db", - // ], - // "env": { - // "PYTHONPATH": "${workspaceFolder}/lib" - // }, - // "console": "integratedTerminal" - // }, - { - "name": "EQUITY OLS (rolling)", - "type": "debugpy", - "request": "launch", - "python": "/home/oleg/.pyenv/python3.12-venv/bin/python", - "program": "${workspaceFolder}/research/backtest.py", - "args": [ - "--config=${workspaceFolder}/configuration/ols.cfg", - "--instruments=COIN:EQUITY:ALPACA,MSTR:EQUITY:ALPACA", - "--date_pattern=20250605", - "--result_db=${workspaceFolder}/research/results/equity/%T.ols.COIN-MSTR.20250605.equity_results.db", - ], - "env": { - "PYTHONPATH": "${workspaceFolder}/lib" - }, - "console": "integratedTerminal" - }, - { - "name": "EQUITY-CRYPTO OLS (rolling)", - "type": "debugpy", - "request": "launch", - "python": "/home/oleg/.pyenv/python3.12-venv/bin/python", - "program": "${workspaceFolder}/research/backtest.py", - "args": [ - "--config=${workspaceFolder}/configuration/ols.cfg", - "--instruments=COIN:EQUITY:ALPACA,BTC-USDT:CRYPTO:BNBSPOT", - "--date_pattern=20250605", - "--result_db=${workspaceFolder}/research/results/intermarket/%T.ols.COIN-BTC.20250605.equity_results.db", - ], - "env": { - "PYTHONPATH": "${workspaceFolder}/lib" - }, - "console": "integratedTerminal" - }, - { "name": "-------- VECM --------", }, { - "name": "CRYPTO VECM (rolling)", - "type": "debugpy", - "request": "launch", - "python": "/home/oleg/.pyenv/python3.12-venv/bin/python", - "program": "${workspaceFolder}/research/backtest.py", - "args": [ - "--config=${workspaceFolder}/configuration/vecm.cfg", - "--instruments=ADA-USDT:CRYPTO:BNBSPOT,SOL-USDT:CRYPTO:BNBSPOT", - "--date_pattern=20250605", - "--result_db=${workspaceFolder}/research/results/crypto/%T.vecm.ADA-SOL.20250605.crypto_results.db", - ], - "env": { - "PYTHONPATH": "${workspaceFolder}/lib" - }, - "console": "integratedTerminal" - }, - { - "name": "CRYPTO VECM (optimized)", + "name": "CRYPTO VECM BACKTEST (optimized)", "type": "debugpy", "request": "launch", "python": "/home/oleg/.pyenv/python3.12-venv/bin/python", "program": "${workspaceFolder}/research/backtest.py", "args": [ "--config=${workspaceFolder}/configuration/vecm-opt.cfg", - "--instruments=ADA-USDT:CRYPTO:BNBSPOT,SOL-USDT:CRYPTO:BNBSPOT", - "--date_pattern=20250605", + "--instruments=CRYPTO:BNBSPOT:PAIR-ADA-USDT,CRYPTO:BNBSPOT:PAIR-SOL-USDT", + "--date_pattern=20250910", "--result_db=${workspaceFolder}/research/results/crypto/%T.vecm-opt.ADA-SOL.20250605.crypto_results.db", ], "env": { - "PYTHONPATH": "${workspaceFolder}/lib" + "PYTHONPATH": "${workspaceFolder}/..", + "CONFIG_SERVICE": "cloud16.cvtt.vpn:6789" }, "console": "integratedTerminal" }, // { - // "name": "CRYPTO VECM (expanding)", + // "name": "EQUITY VECM (rolling)", // "type": "debugpy", // "request": "launch", // "python": "/home/oleg/.pyenv/python3.12-venv/bin/python", // "program": "${workspaceFolder}/research/backtest.py", // "args": [ - // "--config=${workspaceFolder}/configuration/vecm-exp.cfg", - // "--instruments=ADA-USDT:CRYPTO:BNBSPOT,SOL-USDT:CRYPTO:BNBSPOT", + // "--config=${workspaceFolder}/configuration/vecm.cfg", + // "--instruments=COIN:EQUITY:ALPACA,MSTR:EQUITY:ALPACA", // "--date_pattern=20250605", - // "--result_db=${workspaceFolder}/research/results/crypto/%T.vecm-exp.ADA-SOL.20250605.crypto_results.db", + // "--result_db=${workspaceFolder}/research/results/equity/%T.vecm.COIN-MSTR.20250605.equity_results.db", + // ], + // "env": { + // "PYTHONPATH": "${workspaceFolder}/lib" + // }, + // "console": "integratedTerminal" + // }, + // { + // "name": "EQUITY-CRYPTO VECM (rolling)", + // "type": "debugpy", + // "request": "launch", + // "python": "/home/oleg/.pyenv/python3.12-venv/bin/python", + // "program": "${workspaceFolder}/research/backtest.py", + // "args": [ + // "--config=${workspaceFolder}/configuration/vecm.cfg", + // "--instruments=COIN:EQUITY:ALPACA,BTC-USDT:CRYPTO:BNBSPOT", + // "--date_pattern=20250605", + // "--result_db=${workspaceFolder}/research/results/intermarket/%T.vecm.COIN-BTC.20250601.equity_results.db", // ], // "env": { // "PYTHONPATH": "${workspaceFolder}/lib" // }, // "console": "integratedTerminal" // }, - { - "name": "EQUITY VECM (rolling)", - "type": "debugpy", - "request": "launch", - "python": "/home/oleg/.pyenv/python3.12-venv/bin/python", - "program": "${workspaceFolder}/research/backtest.py", - "args": [ - "--config=${workspaceFolder}/configuration/vecm.cfg", - "--instruments=COIN:EQUITY:ALPACA,MSTR:EQUITY:ALPACA", - "--date_pattern=20250605", - "--result_db=${workspaceFolder}/research/results/equity/%T.vecm.COIN-MSTR.20250605.equity_results.db", - ], - "env": { - "PYTHONPATH": "${workspaceFolder}/lib" - }, - "console": "integratedTerminal" - }, - { - "name": "EQUITY-CRYPTO VECM (rolling)", - "type": "debugpy", - "request": "launch", - "python": "/home/oleg/.pyenv/python3.12-venv/bin/python", - "program": "${workspaceFolder}/research/backtest.py", - "args": [ - "--config=${workspaceFolder}/configuration/vecm.cfg", - "--instruments=COIN:EQUITY:ALPACA,BTC-USDT:CRYPTO:BNBSPOT", - "--date_pattern=20250605", - "--result_db=${workspaceFolder}/research/results/intermarket/%T.vecm.COIN-BTC.20250601.equity_results.db", - ], - "env": { - "PYTHONPATH": "${workspaceFolder}/lib" - }, - "console": "integratedTerminal" - }, { "name": "-------- B a t c h e s --------", }, diff --git a/.vscode/settings.json b/.vscode/settings.json index e42933d..5173f0d 100644 --- a/.vscode/settings.json +++ b/.vscode/settings.json @@ -6,7 +6,7 @@ ], "python.testing.cwd": "${workspaceFolder}", "python.testing.autoTestDiscoverOnSaveEnabled": true, - "python.defaultInterpreterPath": "/usr/bin/python3", + "python.defaultInterpreterPath": "/home/oleg/.pyenv/python3.12-venv/bin/python3", "python.testing.pytestPath": "python3", "python.analysis.extraPaths": [ "${workspaceFolder}", diff --git a/apps/pairs_trader.py b/apps/pairs_trader.py index 212ac3c..d03ffec 100644 --- a/apps/pairs_trader.py +++ b/apps/pairs_trader.py @@ -90,8 +90,7 @@ class PairsTrader(NamedObject): strategy_config = self.config_.get_subconfig("strategy_config", Config({})) self.live_strategy_ = PtLiveStrategy( config=strategy_config, - instruments=self.instruments_, - pairs_trader=self + pairs_trader=self, ) Log.info(f"{self.fname()} Strategy created: {self.live_strategy_}") @@ -133,8 +132,11 @@ class PairsTrader(NamedObject): await self.live_strategy_.on_mkt_data_hist_snapshot(hist_aggr=history) async def _on_api_request(self, request: web.Request) -> web.Response: + # TODO choose pair + # TODO confirm chosen pair (after selection is implemented) return web.Response() # TODO API request handler implementation + async def run(self) -> None: Log.info(f"{self.fname()} ...") pass diff --git a/configuration/ols-exp.cfg b/configuration/__DELETE__/ols-exp.cfg similarity index 85% rename from configuration/ols-exp.cfg rename to configuration/__DELETE__/ols-exp.cfg index 09ef8f6..aa25a38 100644 --- a/configuration/ols-exp.cfg +++ b/configuration/__DELETE__/ols-exp.cfg @@ -23,8 +23,8 @@ "dis-equilibrium_open_trshld": 2.0, "dis-equilibrium_close_trshld": 0.5, "training_size": 120, - "model_class": "pt_strategy.models.OLSModel", - "model_data_policy_class": "pt_strategy.model_data_policy.ExpandingWindowDataPolicy", + "model_class": "pairs_trading.lib.pt_strategy.models.OLSModel", + "model_data_policy_class": "pairs_trading.lib.pt_strategy.model_data_policy.ExpandingWindowDataPolicy", # ====== Stop Conditions ====== "stop_close_conditions": { diff --git a/configuration/ols-opt.cfg b/configuration/__DELETE__/ols-opt.cfg similarity index 73% rename from configuration/ols-opt.cfg rename to configuration/__DELETE__/ols-opt.cfg index e40a8a3..0e8843e 100644 --- a/configuration/ols-opt.cfg +++ b/configuration/__DELETE__/ols-opt.cfg @@ -22,11 +22,11 @@ }, "dis-equilibrium_open_trshld": 1.75, "dis-equilibrium_close_trshld": 0.9, - "model_class": "pt_strategy.models.OLSModel", + "model_class": "pairs_trading.lib.pt_strategy.models.OLSModel", - # "model_data_policy_class": "pt_strategy.model_data_policy.EGOptimizedWndDataPolicy", - # "model_data_policy_class": "pt_strategy.model_data_policy.ADFOptimizedWndDataPolicy", - "model_data_policy_class": "pt_strategy.model_data_policy.JohansenOptdWndDataPolicy", + # "model_data_policy_class": "pairs_trading.lib.pt_strategy.model_data_policy.EGOptimizedWndDataPolicy", + # "model_data_policy_class": "pairs_trading.lib.pt_strategy.model_data_policy.ADFOptimizedWndDataPolicy", + "model_data_policy_class": "pairs_trading.lib.pt_strategy.model_data_policy.JohansenOptdWndDataPolicy", "min_training_size": 60, "max_training_size": 150, diff --git a/configuration/ols.cfg b/configuration/__DELETE__/ols.cfg similarity index 80% rename from configuration/ols.cfg rename to configuration/__DELETE__/ols.cfg index ceaa4b8..4524a02 100644 --- a/configuration/ols.cfg +++ b/configuration/__DELETE__/ols.cfg @@ -22,11 +22,11 @@ }, "dis-equilibrium_open_trshld": 1.75, "dis-equilibrium_close_trshld": 0.9, - "model_class": "pt_strategy.models.OLSModel", + "model_class": "pairs_trading.lib.pt_strategy.models.OLSModel", "training_size": 120, - "model_data_policy_class": "pt_strategy.model_data_policy.RollingWindowDataPolicy", - # "model_data_policy_class": "pt_strategy.model_data_policy.OptimizedWindowDataPolicy", + "model_data_policy_class": "pairs_trading.lib.pt_strategy.model_data_policy.RollingWindowDataPolicy", + # "model_data_policy_class": "pairs_trading.lib.pt_strategy.model_data_policy.OptimizedWindowDataPolicy", # "min_training_size": 60, # "max_training_size": 150, diff --git a/configuration/pairs_trader.cfg b/configuration/__DELETE__/pairs_trader.cfg similarity index 100% rename from configuration/pairs_trader.cfg rename to configuration/__DELETE__/pairs_trader.cfg diff --git a/configuration/vecm.cfg b/configuration/__DELETE__/vecm.cfg similarity index 79% rename from configuration/vecm.cfg rename to configuration/__DELETE__/vecm.cfg index 71fb9c6..9c3e5da 100644 --- a/configuration/vecm.cfg +++ b/configuration/__DELETE__/vecm.cfg @@ -23,11 +23,11 @@ }, "dis-equilibrium_open_trshld": 1.75, "dis-equilibrium_close_trshld": 1.0, - "model_class": "pt_strategy.models.VECMModel", + "model_class": "pairs_trading.lib.pt_strategy.models.VECMModel", "training_size": 120, - "model_data_policy_class": "pt_strategy.model_data_policy.RollingWindowDataPolicy", - # "model_data_policy_class": "pt_strategy.model_data_policy.OptimizedWindowDataPolicy", + "model_data_policy_class": "pairs_trading.lib.pt_strategy.model_data_policy.RollingWindowDataPolicy", + # "model_data_policy_class": "pairs_trading.lib.pt_strategy.model_data_policy.OptimizedWindowDataPolicy", # "min_training_size": 60, # "max_training_size": 150, diff --git a/configuration/vecm-opt.cfg b/configuration/vecm-opt.cfg index 8c3f4e5..df0eea2 100644 --- a/configuration/vecm-opt.cfg +++ b/configuration/vecm-opt.cfg @@ -1,9 +1,16 @@ { + "refdata": { + "assets": @inc=http://@env{CONFIG_SERVICE}/refdata/assets + , "instruments": @inc=http://@env{CONFIG_SERVICE}/refdata/instruments + , "exchange_instruments": @inc=http://@env{CONFIG_SERVICE}/refdata/exchange_instruments + , "dynamic_instrument_exchanges": ["ALPACA"] + , "exchanges": @inc=http://@env{CONFIG_SERVICE}/refdata/exchanges + }, "market_data_loading": { "CRYPTO": { - "data_directory": "./data/crypto", - "db_table_name": "md_1min_bars", - "instrument_id_pfx": "PAIR-", + "data_directory": "./data/crypto", + "db_table_name": "md_1min_bars", + "instrument_id_pfx": "PAIR-", }, "EQUITY": { "data_directory": "./data/equity", @@ -24,11 +31,11 @@ "dis-equilibrium_open_trshld": 1.75, "dis-equilibrium_close_trshld": 1.0, - "model_class": "pt_strategy.models.VECMModel", + "model_class": "pairs_trading.lib.pt_strategy.models.VECMModel", # "training_size": 120, - # "model_data_policy_class": "pt_strategy.model_data_policy.RollingWindowDataPolicy", - "model_data_policy_class": "pt_strategy.model_data_policy.ADFOptimizedWndDataPolicy", + # "model_data_policy_class": "pairs_trading.lib.pt_strategy.model_data_policy.RollingWindowDataPolicy", + "model_data_policy_class": "pairs_trading.lib.pt_strategy.model_data_policy.ADFOptimizedWndDataPolicy", "min_training_size": 60, "max_training_size": 150, diff --git a/lib/pt_strategy/live/live_strategy.py b/lib/pt_strategy/live/live_strategy.py index f05e3fd..78da9e3 100644 --- a/lib/pt_strategy/live/live_strategy.py +++ b/lib/pt_strategy/live/live_strategy.py @@ -10,19 +10,23 @@ import pandas as pd from cvttpy_tools.base import NamedObject from cvttpy_tools.app import App from cvttpy_tools.config import Config -from cvttpy_tools.settings.cvtt_types import IntervalSecT -from cvttpy_tools.timeutils import SecPerHour +from cvttpy_tools.settings.cvtt_types import BookIdT, IntervalSecT +from cvttpy_tools.timeutils import SecPerHour, current_nanoseconds from cvttpy_tools.logger import Log # --- from cvttpy_trading.trading.instrument import ExchangeInstrument from cvttpy_trading.trading.mkt_data.md_summary import MdTradesAggregate from cvttpy_trading.trading.trading_instructions import TradingInstructions +from cvttpy_trading.trading.accounting.cvtt_book import CvttBook +from cvttpy_trading.trading.trading_instructions import TargetPositionSignal + # --- from pairs_trading.lib.pt_strategy.model_data_policy import ModelDataPolicy from pairs_trading.lib.pt_strategy.pt_model import Prediction -from pairs_trading.lib.pt_strategy.trading_pair import PairState, TradingPair +from pairs_trading.lib.pt_strategy.trading_pair import LiveTradingPair from pairs_trading.apps.pairs_trader import PairsTrader +from pairs_trading.lib.pt_strategy.pt_market_data import LiveMarketData """ @@ -51,7 +55,7 @@ class PtLiveStrategy(NamedObject): open_threshold_: float close_threshold_: float - trading_pair_: TradingPair + trading_pair_: LiveTradingPair model_data_policy_: ModelDataPolicy pairs_trader_: PairsTrader @@ -60,28 +64,29 @@ class PtLiveStrategy(NamedObject): # for presentation: history of prediction values and trading signals predictions_df_: pd.DataFrame trading_signals_df_: pd.DataFrame + # book_: CvttBook def __init__( self, config: Config, - instruments: List[ExchangeInstrument], pairs_trader: PairsTrader, ): - self.trading_pair_ = TradingPair( - config=cast(Dict[str, Any], config.data()), - instruments=[{"instrument_id": ei.instrument_id()} for ei in instruments], + self.pairs_trader_ = pairs_trader + self.trading_pair_ = LiveTradingPair( + config=config, + instruments=self.pairs_trader_.instruments_, ) self.predictions_df_ = pd.DataFrame() self.trading_signals_df_ = pd.DataFrame() - self.pairs_trader_ = pairs_trader + # self.book_ = book import copy # modified config must be passed to PtMarketData self.config_ = Config(json_src=copy.deepcopy(config.data())) - self.instruments_ = instruments + self.instruments_ = self.pairs_trader_.instruments_ App.instance().add_call( stage=App.Stage.Config, func=self._on_config(), can_run_now=True @@ -95,9 +100,6 @@ class PtLiveStrategy(NamedObject): await self.pairs_trader_.subscribe_md() - self.model_data_policy_ = ModelDataPolicy.create( - self.config_, is_real_time=True, pair=self.trading_pair_ - ) self.open_threshold_ = self.config_.get_value( "dis-equilibrium_open_trshld", 0.0 ) @@ -121,13 +123,22 @@ class PtLiveStrategy(NamedObject): if not self._is_md_actual(hist_aggr=hist_aggr): return - market_data_df: Optional[pd.DataFrame] = self._create_md_pdf(hist_aggr=hist_aggr) - if market_data_df is None: + market_data_df: pd.DataFrame = self._create_md_df(hist_aggr=hist_aggr) + if len(market_data_df) == 0: Log.warning(f"{self.fname()} Unable to create market data df") return self.trading_pair_.market_data_ = market_data_df - self.model_data_policy_.advance() + self.model_data_policy_ = ModelDataPolicy.create( + self.config_, + is_real_time=True, + pair=self.trading_pair_, + mkt_data=market_data_df, + ) + assert ( + self.model_data_policy_ is not None + ), f"{self.fname()}: Unable to create ModelDataPolicy" + prediction = self.trading_pair_.run( market_data_df, self.model_data_policy_.advance() ) @@ -135,7 +146,7 @@ class PtLiveStrategy(NamedObject): [self.predictions_df_, prediction.to_df()], ignore_index=True ) - trading_instructions: Optional[TradingInstructions] = ( + trading_instructions: List[TradingInstructions] = ( self._create_trading_instructions( prediction=prediction, last_row=market_data_df.iloc[-1] ) @@ -144,10 +155,74 @@ class PtLiveStrategy(NamedObject): await self._send_trading_instructions(trading_instructions) def _is_md_actual(self, hist_aggr: List[MdTradesAggregate]) -> bool: - return False # URGENT _is_md_actual + return False # URGENT _is_md_actual - def _create_md_pdf(self, hist_aggr: List[MdTradesAggregate]) -> Optional[pd.DataFrame]: - return None # URGENT _create_md_pdf + def _create_md_df(self, hist_aggr: List[MdTradesAggregate]) -> pd.DataFrame: + """ + tstamp time_ns symbol open high low close volume num_trades vwap + 0 2025-09-10 11:30:00 1757503800000000000 ADA-USDT 0.8750 0.8750 0.8743 0.8743 50710.500 0 0.874489 + 1 2025-09-10 11:30:00 1757503800000000000 SOL-USDT 219.9700 219.9800 219.6600 219.7000 2648.582 0 219.787847 + 2 2025-09-10 11:31:00 1757503860000000000 SOL-USDT 219.7000 219.7300 219.6200 219.6200 1134.886 0 219.663460 + 3 2025-09-10 11:31:00 1757503860000000000 ADA-USDT 0.8743 0.8745 0.8741 0.8741 10696.400 0 0.874234 + 4 2025-09-10 11:32:00 1757503920000000000 ADA-USDT 0.8742 0.8742 0.8739 0.8740 18546.900 0 0.874037 + """ + + rows: List[Dict[str, Any]] = [] + + for aggr in hist_aggr: + exch_inst = aggr.exch_inst_ + + rows.append( + { + # convert nanoseconds → tz-aware pandas timestamp + "tstamp": pd.to_datetime(aggr.time_ns_, unit="ns", utc=True), + "time_ns": aggr.time_ns_, + "symbol": exch_inst.instrument_id().split("-", 1)[1], + "exchange_id": exch_inst.exchange_id_, + "instrument_id": exch_inst.instrument_id(), + "open": exch_inst.get_price(aggr.open_), + "high": exch_inst.get_price(aggr.high_), + "low": exch_inst.get_price(aggr.low_), + "close": exch_inst.get_price(aggr.close_), + "volume": exch_inst.get_quantity(aggr.volume_), + "num_trades": aggr.num_trades_, + "vwap": exch_inst.get_price(aggr.vwap_), + } + ) + + source_md_df = pd.DataFrame( + rows, + columns=[ + "tstamp", + "time_ns", + "symbol", + "exchange_id", + "instrument_id", + "open", + "high", + "low", + "close", + "volume", + "num_trades", + "vwap", + ], + ) + + # automatic sorting + source_md_df.sort_values( + by=["time_ns", "symbol"], + ascending=True, + inplace=True, + kind="mergesort", # stable sort + ) + + source_md_df.reset_index(drop=True, inplace=True) + + pt_mkt_data = LiveMarketData(config=self.config_, instruments=self.instruments_) + pt_mkt_data.origin_mkt_data_df_ = source_md_df + pt_mkt_data.set_market_data() + + return pt_mkt_data.market_data_df_ def interval_sec(self) -> IntervalSecT: return self.interval_sec_ @@ -156,271 +231,110 @@ class PtLiveStrategy(NamedObject): return self.history_depth_sec_ async def _send_trading_instructions( - self, trading_instructions: TradingInstructions + self, trading_instructions: List[TradingInstructions] ) -> None: - await self.pairs_trader_.ti_sender_.send_trading_instructions(trading_instructions) - pass # URGENT _send_trading_instructions + for ti in trading_instructions: + Log.info(f"{self.fname()} Sending trading instructions {ti}") + await self.pairs_trader_.ti_sender_.send_trading_instructions(ti) def _create_trading_instructions( self, prediction: Prediction, last_row: pd.Series - ) -> Optional[TradingInstructions]: + ) -> List[TradingInstructions]: + trd_instructions: List[TradingInstructions] = [] pair = self.trading_pair_ - res: Optional[TradingInstructions] scaled_disequilibrium = prediction.scaled_disequilibrium_ abs_scaled_disequilibrium = abs(scaled_disequilibrium) - if pair.is_closed(): - if abs_scaled_disequilibrium >= self.open_threshold_: - trd_instructions = self._create_open_trade_instructions( - pair, row=last_row, prediction=prediction - ) - elif pair.is_open(): - if abs_scaled_disequilibrium <= self.close_threshold_: - trd_instructions = self._create_close_trade_instructions( - pair, row=last_row # , prediction=prediction - ) - elif pair.to_stop_close_conditions(predicted_row=last_row): - trd_instructions = self._create_close_trade_instructions( - pair, row=last_row - ) + if abs_scaled_disequilibrium >= self.open_threshold_: + trd_instructions = self._create_open_trade_instructions( + pair, row=last_row, prediction=prediction + ) + + elif abs_scaled_disequilibrium <= self.close_threshold_ or pair.to_stop_close_conditions(predicted_row=last_row): + trd_instructions = self._create_close_trade_instructions( + pair, row=last_row # , prediction=prediction + ) + return trd_instructions + + def _strength(self, scaled_disequilibrium) -> float: + # URGENT PtLiveStrategy._strength() + return 1.0 def _create_open_trade_instructions( - self, pair: TradingPair, row: pd.Series, prediction: Prediction - ) -> Optional[TradingInstructions]: - ti: Optional[TradingInstructions] = None - scaled_disequilibrium = prediction.scaled_disequilibrium_ - # URGENT _create_open_trade_instructions - - # if scaled_disequilibrium > 0: - # side_a = "SELL" - # trd_inst_a = TradingInstruction( - # type_=TradingInstructionType.TARGET_POSITION, - # exch_instr_=pair.get_instrument_a(), - # specifics_={"side": "SELL", "strength": -1}, - # ) - # side_b = "BUY" - # else: - # side_a = "BUY" - # side_b = "SELL" - - # colname_a, colname_b = pair.exec_prices_colnames() - # px_a = row[f"{colname_a}"] - # px_b = row[f"{colname_b}"] - - # tstamp = row["tstamp"] - # diseqlbrm = prediction.disequilibrium_ - # scaled_disequilibrium = prediction.scaled_disequilibrium_ - - # df = self._trades_df() - - # # save closing sides - # pair.user_data_["open_side_a"] = side_a # used in oustanding positions - # pair.user_data_["open_side_b"] = side_b - # pair.user_data_["open_px_a"] = px_a - # pair.user_data_["open_px_b"] = px_b - # pair.user_data_["open_tstamp"] = tstamp - - # pair.user_data_["close_side_a"] = side_b # used for closing trades - # pair.user_data_["close_side_b"] = side_a - - # # create opening trades - # df.loc[len(df)] = { - # "time": tstamp, - # "symbol": pair.symbol_a_, - # "side": side_a, - # "action": "OPEN", - # "price": px_a, - # "disequilibrium": diseqlbrm, - # "signed_scaled_disequilibrium": scaled_disequilibrium, - # "scaled_disequilibrium": abs(scaled_disequilibrium), - # # "pair": pair, - # } - # df.loc[len(df)] = { - # "time": tstamp, - # "symbol": pair.symbol_b_, - # "side": side_b, - # "action": "OPEN", - # "price": px_b, - # "disequilibrium": diseqlbrm, - # "scaled_disequilibrium": abs(scaled_disequilibrium), - # "signed_scaled_disequilibrium": scaled_disequilibrium, - # # "pair": pair, - # } - # ti: List[TradingInstruction] = self._create_trading_instructions( - # prediction=prediction, last_row=row - # ) - return ti - - def _create_close_trade_instructions( - self, pair: TradingPair, row: pd.Series # , prediction: Prediction - ) -> Optional[TradingInstructions]: - ti: Optional[TradingInstructions] = None - # URGENT _create_close_trade_instructions - return ti - - def _handle_outstanding_positions(self) -> Optional[pd.DataFrame]: - trades = None - pair = self.trading_pair_ - - # Outstanding positions - if pair.user_data_["state"] == PairState.OPEN: - print(f"{pair}: *** Position is NOT CLOSED. ***") - # outstanding positions - if self.config_.key_exists("close_outstanding_positions"): - close_position_row = pd.Series(pair.market_data_.iloc[-2]) - # close_position_row["disequilibrium"] = 0.0 - # close_position_row["scaled_disequilibrium"] = 0.0 - # close_position_row["signed_scaled_disequilibrium"] = 0.0 - - trades = self._create_close_trades( - pair=pair, row=close_position_row, prediction=None - ) - if trades is not None: - trades["status"] = PairState.CLOSE_POSITION.name - print(f"CLOSE_POSITION TRADES:\n{trades}") - pair.user_data_["state"] = PairState.CLOSE_POSITION - pair.on_close_trades(trades) - else: - pair.add_outstanding_position( - symbol=pair.symbol_a_, - open_side=pair.user_data_["open_side_a"], - open_px=pair.user_data_["open_px_a"], - open_tstamp=pair.user_data_["open_tstamp"], - last_mkt_data_row=pair.market_data_.iloc[-1], - ) - pair.add_outstanding_position( - symbol=pair.symbol_b_, - open_side=pair.user_data_["open_side_b"], - open_px=pair.user_data_["open_px_b"], - open_tstamp=pair.user_data_["open_tstamp"], - last_mkt_data_row=pair.market_data_.iloc[-1], - ) - return trades - - def _trades_df(self) -> pd.DataFrame: - types = { - "time": "datetime64[ns]", - "action": "string", - "symbol": "string", - "side": "string", - "price": "float64", - "disequilibrium": "float64", - "scaled_disequilibrium": "float64", - "signed_scaled_disequilibrium": "float64", - # "pair": "object", - } - columns = list(types.keys()) - return pd.DataFrame(columns=columns).astype(types) - - def _create_open_trades( - self, pair: TradingPair, row: pd.Series, prediction: Prediction - ) -> Optional[pd.DataFrame]: - colname_a, colname_b = pair.exec_prices_colnames() - - tstamp = row["tstamp"] + self, pair: LiveTradingPair, row: pd.Series, prediction: Prediction + ) -> List[TradingInstructions]: diseqlbrm = prediction.disequilibrium_ scaled_disequilibrium = prediction.scaled_disequilibrium_ - px_a = row[f"{colname_a}"] - px_b = row[f"{colname_b}"] - - # creating the trades - df = self._trades_df() - - print(f"OPEN_TRADES: {row["tstamp"]} {scaled_disequilibrium=}") if diseqlbrm > 0: - side_a = "SELL" - side_b = "BUY" + side_a = -1 + side_b = 1 else: - side_a = "BUY" - side_b = "SELL" + side_a = 1 + side_b = -1 - # save closing sides - pair.user_data_["open_side_a"] = side_a # used in oustanding positions - pair.user_data_["open_side_b"] = side_b - pair.user_data_["open_px_a"] = px_a - pair.user_data_["open_px_b"] = px_b - pair.user_data_["open_tstamp"] = tstamp + ti_a: Optional[TradingInstructions] = TradingInstructions( + book=self.pairs_trader_.book_id_, + strategy_id=self.__class__.__name__, + ti_type=TradingInstructions.Type.TARGET_POSITION, + issued_ts_ns=current_nanoseconds(), + data=TargetPositionSignal( + strength=side_a * self._strength(scaled_disequilibrium), + base_asset=pair.get_instrument_a().base_asset_id_, + quote_asset=pair.get_instrument_a().quote_asset_id_, + user_data={} + ), + ) + if not ti_a: + return [] + ti_b: Optional[TradingInstructions] = TradingInstructions( + book=self.pairs_trader_.book_id_, + strategy_id=self.__class__.__name__, + ti_type=TradingInstructions.Type.TARGET_POSITION, + issued_ts_ns=current_nanoseconds(), + data=TargetPositionSignal( + strength=side_b * self._strength(scaled_disequilibrium), + base_asset=pair.get_instrument_b().base_asset_id_, + quote_asset=pair.get_instrument_b().quote_asset_id_, + user_data={} + ), + ) + if not ti_b: + return [] + return [ti_a, ti_b] - pair.user_data_["close_side_a"] = side_b # used for closing trades - pair.user_data_["close_side_b"] = side_a - # create opening trades - df.loc[len(df)] = { - "time": tstamp, - "symbol": pair.symbol_a_, - "side": side_a, - "action": "OPEN", - "price": px_a, - "disequilibrium": diseqlbrm, - "signed_scaled_disequilibrium": scaled_disequilibrium, - "scaled_disequilibrium": abs(scaled_disequilibrium), - # "pair": pair, - } - df.loc[len(df)] = { - "time": tstamp, - "symbol": pair.symbol_b_, - "side": side_b, - "action": "OPEN", - "price": px_b, - "disequilibrium": diseqlbrm, - "scaled_disequilibrium": abs(scaled_disequilibrium), - "signed_scaled_disequilibrium": scaled_disequilibrium, - # "pair": pair, - } - return df - - def _create_close_trades( - self, pair: TradingPair, row: pd.Series, prediction: Optional[Prediction] = None - ) -> Optional[pd.DataFrame]: - colname_a, colname_b = pair.exec_prices_colnames() - - tstamp = row["tstamp"] - if prediction is not None: - diseqlbrm = prediction.disequilibrium_ - signed_scaled_disequilibrium = prediction.scaled_disequilibrium_ - scaled_disequilibrium = abs(prediction.scaled_disequilibrium_) - else: - diseqlbrm = 0.0 - signed_scaled_disequilibrium = 0.0 - scaled_disequilibrium = 0.0 - px_a = row[f"{colname_a}"] - px_b = row[f"{colname_b}"] - - # creating the trades - df = self._trades_df() - - # create opening trades - df.loc[len(df)] = { - "time": tstamp, - "symbol": pair.symbol_a_, - "side": pair.user_data_["close_side_a"], - "action": "CLOSE", - "price": px_a, - "disequilibrium": diseqlbrm, - "scaled_disequilibrium": scaled_disequilibrium, - "signed_scaled_disequilibrium": signed_scaled_disequilibrium, - # "pair": pair, - } - df.loc[len(df)] = { - "time": tstamp, - "symbol": pair.symbol_b_, - "side": pair.user_data_["close_side_b"], - "action": "CLOSE", - "price": px_b, - "disequilibrium": diseqlbrm, - "scaled_disequilibrium": scaled_disequilibrium, - "signed_scaled_disequilibrium": signed_scaled_disequilibrium, - # "pair": pair, - } - del pair.user_data_["close_side_a"] - del pair.user_data_["close_side_b"] - - del pair.user_data_["open_tstamp"] - del pair.user_data_["open_px_a"] - del pair.user_data_["open_px_b"] - del pair.user_data_["open_side_a"] - del pair.user_data_["open_side_b"] - return df + def _create_close_trade_instructions( + self, pair: LiveTradingPair, row: pd.Series + ) -> List[TradingInstructions]: + ti_a: Optional[TradingInstructions] = TradingInstructions( + book=self.pairs_trader_.book_id_, + strategy_id=self.__class__.__name__, + ti_type=TradingInstructions.Type.TARGET_POSITION, + issued_ts_ns=current_nanoseconds(), + data=TargetPositionSignal( + strength=0, + base_asset=pair.get_instrument_a().base_asset_id_, + quote_asset=pair.get_instrument_a().quote_asset_id_, + user_data={} + ), + ) + if not ti_a: + return [] + ti_b: Optional[TradingInstructions] = TradingInstructions( + book=self.pairs_trader_.book_id_, + strategy_id=self.__class__.__name__, + ti_type=TradingInstructions.Type.TARGET_POSITION, + issued_ts_ns=current_nanoseconds(), + data=TargetPositionSignal( + strength=0, + base_asset=pair.get_instrument_b().base_asset_id_, + quote_asset=pair.get_instrument_b().quote_asset_id_, + user_data={} + ), + ) + if not ti_b: + return [] + return [ti_a, ti_b] diff --git a/lib/pt_strategy/model_data_policy.py b/lib/pt_strategy/model_data_policy.py index 89dfcca..b8b299c 100644 --- a/lib/pt_strategy/model_data_policy.py +++ b/lib/pt_strategy/model_data_policy.py @@ -12,8 +12,8 @@ from cvttpy_tools.config import Config @dataclass class DataWindowParams: - training_size: int - training_start_index: int + training_size_: int + training_start_index_: int class ModelDataPolicy(ABC): @@ -24,16 +24,9 @@ class ModelDataPolicy(ABC): def __init__(self, config: Config, *args: Any, **kwargs: Any): self.config_ = config - training_size = config.get_value("training_size", 120) - training_start_index = 0 - if kwargs.get("is_real_time", False): - training_size = 120 - training_start_index = 0 - else: - training_size = config.get_value("training_size", 120) self.current_data_params_ = DataWindowParams( - training_size=config.get_value("training_size", 120), - training_start_index=0, + training_size_=config.get_value("training_size", 120), + training_start_index_=0, ) self.count_ = 0 self.is_real_time_ = kwargs.get("is_real_time", False) @@ -66,9 +59,9 @@ class RollingWindowDataPolicy(ModelDataPolicy): def advance(self, mkt_data_df: Optional[pd.DataFrame] = None) -> DataWindowParams: super().advance(mkt_data_df) if self.is_real_time_: - self.current_data_params_.training_start_index = -self.current_data_params_.training_size + self.current_data_params_.training_start_index_ = -self.current_data_params_.training_size_ else: - self.current_data_params_.training_start_index += 1 + self.current_data_params_.training_start_index_ += 1 return self.current_data_params_ @@ -111,12 +104,12 @@ class OptimizedWndDataPolicy(ModelDataPolicy, ABC): if self.is_real_time_: self.end_index_ = len(self.mkt_data_df_) - 1 else: - self.end_index_ = self.current_data_params_.training_start_index + self.max_training_size_ + self.end_index_ = self.current_data_params_.training_start_index_ + self.max_training_size_ if self.end_index_ > len(self.mkt_data_df_) - 1: self.end_index_ = len(self.mkt_data_df_) - 1 - self.current_data_params_.training_start_index = self.end_index_ - self.max_training_size_ - if self.current_data_params_.training_start_index < 0: - self.current_data_params_.training_start_index = 0 + self.current_data_params_.training_start_index_ = self.end_index_ - self.max_training_size_ + if self.current_data_params_.training_start_index_ < 0: + self.current_data_params_.training_start_index_ = 0 col_a, col_b = self.pair_.colnames() self.prices_a_ = np.array(self.mkt_data_df_[col_a]) @@ -153,8 +146,8 @@ class EGOptimizedWndDataPolicy(OptimizedWndDataPolicy): eg_pvalue = float(coint(series_a, series_b)[1]) if eg_pvalue < last_pvalue: last_pvalue = eg_pvalue - result.training_size = trn_size - result.training_start_index = start_index + result.training_size_ = trn_size + result.training_start_index_ = start_index # print( # f"*** DEBUG *** end_index={self.end_index_}, best_trn_size={self.current_data_params_.training_size}, {last_pvalue=}" @@ -197,8 +190,8 @@ class ADFOptimizedWndDataPolicy(OptimizedWndDataPolicy): if adf_pvalue < last_pvalue: last_pvalue = adf_pvalue - result.training_size = trn_size - result.training_start_index = start_index + result.training_size_ = trn_size + result.training_start_index_ = start_index # print( # f"*** DEBUG *** end_index={self.end_index_}," @@ -247,8 +240,8 @@ class JohansenOptdWndDataPolicy(OptimizedWndDataPolicy): continue if best_trn_size > 0: - result.training_size = best_trn_size - result.training_start_index = best_start_index + result.training_size_ = best_trn_size + result.training_start_index_ = best_start_index else: print("*** WARNING: No valid cointegration window found.") diff --git a/lib/pt_strategy/pt_market_data.py b/lib/pt_strategy/pt_market_data.py index edf0dd6..e56da16 100644 --- a/lib/pt_strategy/pt_market_data.py +++ b/lib/pt_strategy/pt_market_data.py @@ -1,157 +1,61 @@ from __future__ import annotations +from abc import ABC, abstractmethod from typing import Any, Dict, List, Optional import pandas as pd + # --- +from cvttpy_tools.base import NamedObject +from cvttpy_tools.config import Config from cvttpy_tools.settings.cvtt_types import JsonDictT + # --- from cvttpy_trading.trading.mkt_data.md_summary import MdTradesAggregate +from cvttpy_trading.trading.instrument import ExchangeInstrument # --- from pairs_trading.lib.tools.data_loader import load_market_data -class PtMarketData(): - config_: Dict[str, Any] +class PtMarketData(NamedObject, ABC): + config_: Config origin_mkt_data_df_: pd.DataFrame market_data_df_: pd.DataFrame + stat_model_price_: str + instruments_: List[ExchangeInstrument] + symbol_a_: str + symbol_b_: str - def __init__(self, config: Dict[str, Any]): + def __init__(self, config: Config, instruments: List[ExchangeInstrument]): self.config_ = config self.origin_mkt_data_df_ = pd.DataFrame() self.market_data_df_ = pd.DataFrame() + self.stat_model_price_ = self.config_.get_value("stat_model_price") + self.instruments_ = instruments + assert len(self.instruments_) > 0, "No instruments found in config" + self.symbol_a_ = self.instruments_[0].instrument_id().split("-", 1)[1] + self.symbol_b_ = self.instruments_[1].instrument_id().split("-", 1)[1] -class ResearchMarketData(PtMarketData): - current_index_: int - - is_execution_price_: bool - - def __init__(self, config: Dict[str, Any]): - super().__init__(config) - self.current_index_ = 0 - self.is_execution_price_ = "execution_price" in self.config_ - if self.is_execution_price_: - self.execution_price_column_ = self.config_["execution_price"]["column"] - self.execution_price_shift_ = self.config_["execution_price"]["shift"] - else: - self.execution_price_column_ = None - self.execution_price_shift_ = 0 + @abstractmethod + def md_columns(self) -> List[str]: ... - def has_next(self) -> bool: - return self.current_index_ < len(self.market_data_df_) + @abstractmethod + def rename_columns(self, symbol_df: pd.DataFrame) -> pd.DataFrame: ... - def get_next(self) -> pd.Series: - result = self.market_data_df_.iloc[self.current_index_] - self.current_index_ += 1 - return result - - def load(self) -> None: - datafiles: List[str] = self.config_.get("datafiles", []) - instruments: List[Dict[str, str]] = self.config_.get("instruments", []) - assert len(instruments) > 0, "No instruments found in config" - assert len(datafiles) > 0, "No datafiles found in config" - self.symbol_a_ = instruments[0]["symbol"] - self.symbol_b_ = instruments[1]["symbol"] - self.stat_model_price_ = self.config_["stat_model_price"] + @abstractmethod + def tranform_df_target_colnames(self) -> List[str]: ... - extra_minutes: int - extra_minutes = self.execution_price_shift_ - - for datafile in datafiles: - md_df = load_market_data( - datafile=datafile, - instruments=instruments, - db_table_name=self.config_["market_data_loading"][instruments[0]["instrument_type"]]["db_table_name"], - trading_hours=self.config_["trading_hours"], - extra_minutes=extra_minutes, - ) - self.origin_mkt_data_df_ = pd.concat([self.origin_mkt_data_df_, md_df]) - - self.origin_mkt_data_df_ = self.origin_mkt_data_df_.sort_values(by="tstamp") - self.origin_mkt_data_df_ = self.origin_mkt_data_df_.dropna().reset_index(drop=True) - self._set_market_data() - - def _set_market_data(self, ) -> None: - if self.is_execution_price_: - self.market_data_df_ = pd.DataFrame( - self._transform_dataframe(self.origin_mkt_data_df_)[["tstamp"] + self.colnames() + self.orig_exec_prices_colnames()] - ) - else: - self.market_data_df_ = pd.DataFrame( - self._transform_dataframe(self.origin_mkt_data_df_)[["tstamp"] + self.colnames()] - ) + def set_market_data(self) -> None: + self.market_data_df_ = pd.DataFrame( + self._transform_dataframe(self.origin_mkt_data_df_)[ + ["tstamp"] + self.tranform_df_target_colnames() + ] + ) self.market_data_df_ = self.market_data_df_.dropna().reset_index(drop=True) self.market_data_df_["tstamp"] = pd.to_datetime(self.market_data_df_["tstamp"]) self.market_data_df_ = self.market_data_df_.sort_values("tstamp") - self._set_execution_price_data() - - def _transform_dataframe(self, df: pd.DataFrame) -> pd.DataFrame: - df_selected: pd.DataFrame - if self.is_execution_price_: - execution_price_column = self.config_["execution_price"]["column"] - - df_selected = pd.DataFrame( - df[["tstamp", "symbol", self.stat_model_price_, execution_price_column]] - ) - else: - df_selected = pd.DataFrame( - df[["tstamp", "symbol", self.stat_model_price_]] - ) - - result_df = pd.DataFrame(df_selected["tstamp"]).drop_duplicates().reset_index(drop=True) - - # For each unique symbol, add a corresponding stat_model_price column - symbols = df_selected["symbol"].unique() - - - - for symbol in symbols: - # Filter rows for this symbol - df_symbol = df_selected[df_selected["symbol"] == symbol].reset_index( - drop=True - ) - - # Create column name like "close-COIN" - new_price_column = f"{self.stat_model_price_}_{symbol}" - if self.is_execution_price_: - new_execution_price_column = f"{self.execution_price_column_}_{symbol}" - - # Create temporary dataframe with timestamp and price - temp_df = pd.DataFrame( - { - "tstamp": df_symbol["tstamp"], - new_price_column: df_symbol[self.stat_model_price_], - new_execution_price_column: df_symbol[execution_price_column], - } - ) - else: - temp_df = pd.DataFrame( - { - "tstamp": df_symbol["tstamp"], - new_price_column: df_symbol[self.stat_model_price_], - } - ) - - # Join with our result dataframe - result_df = pd.merge(result_df, temp_df, on="tstamp", how="left") - result_df = result_df.reset_index( - drop=True - ) # do not dropna() since irrelevant symbol would affect dataset - - return result_df.dropna() - - def _set_execution_price_data(self) -> None: - if "execution_price" not in self.config_: - self.market_data_df_[f"exec_price_{self.symbol_a_}"] = self.market_data_df_[f"{self.stat_model_price_}_{self.symbol_a_}"] - self.market_data_df_[f"exec_price_{self.symbol_b_}"] = self.market_data_df_[f"{self.stat_model_price_}_{self.symbol_b_}"] - return - execution_price_column = self.config_["execution_price"]["column"] - execution_price_shift = self.config_["execution_price"]["shift"] - self.market_data_df_[f"exec_price_{self.symbol_a_}"] = self.market_data_df_[f"{execution_price_column}_{self.symbol_a_}"].shift(-execution_price_shift) - self.market_data_df_[f"exec_price_{self.symbol_b_}"] = self.market_data_df_[f"{execution_price_column}_{self.symbol_b_}"].shift(-execution_price_shift) - self.market_data_df_ = self.market_data_df_.dropna().reset_index(drop=True) def colnames(self) -> List[str]: return [ @@ -159,15 +63,161 @@ class ResearchMarketData(PtMarketData): f"{self.stat_model_price_}_{self.symbol_b_}", ] + def _transform_dataframe(self, df: pd.DataFrame) -> pd.DataFrame: + df_selected: pd.DataFrame = pd.DataFrame(df[self.md_columns()]) + result_df = ( + pd.DataFrame(df_selected["tstamp"]).drop_duplicates().reset_index(drop=True) + ) + + # For each unique symbol, add a corresponding stat_model_price column + symbols = df_selected["symbol"].unique() + + for symbol in symbols: + # Filter rows for this symbol + df_symbol = df_selected[df_selected["symbol"] == symbol].reset_index( + drop=True + ) + # Create column name like "close-COIN" + temp_df: pd.DataFrame = self.rename_columns(df_symbol) + # Join with our result dataframe + result_df = pd.merge(result_df, temp_df, on="tstamp", how="left") + result_df = result_df.reset_index( + drop=True + ) # do not dropna() since irrelevant symbol would affect dataset + + return result_df.dropna() + +class ResearchMarketData(PtMarketData): + current_index_: int + is_execution_price_: bool + + def __init__(self, config: Config, instruments: List[ExchangeInstrument]): + super().__init__(config, instruments) + self.current_index_ = 0 + self.is_execution_price_ = self.config_.key_exists("execution_price") + if self.is_execution_price_: + self.execution_price_column_ = self.config_.get_value("execution_price")["column"] + self.execution_price_shift_ = self.config_.get_value("execution_price")["shift"] + else: + self.execution_price_column_ = None + self.execution_price_shift_ = 0 + + def has_next(self) -> bool: + return self.current_index_ < len(self.market_data_df_) + + def get_next(self) -> pd.Series: + result = self.market_data_df_.iloc[self.current_index_] + self.current_index_ += 1 + return result + + def load(self) -> None: + datafiles: List[str] = self.config_.get_value("datafiles", []) + assert len(datafiles) > 0, "No datafiles found in config" + + extra_minutes: int = self.execution_price_shift_ + + for datafile in datafiles: + md_df = load_market_data( + datafile=datafile, + instruments=self.instruments_, + db_table_name=self.config_.get_value("market_data_loading")[ + self.instruments_[0].user_data_.get("instrument_type", "?instrument_type?") + ]["db_table_name"], + trading_hours=self.config_.get_value("trading_hours"), + extra_minutes=extra_minutes, + ) + self.origin_mkt_data_df_ = pd.concat([self.origin_mkt_data_df_, md_df]) + + self.origin_mkt_data_df_ = self.origin_mkt_data_df_.sort_values(by="tstamp") + self.origin_mkt_data_df_ = self.origin_mkt_data_df_.dropna().reset_index( + drop=True + ) + self.set_market_data() + self._set_execution_price_data() + + def _set_execution_price_data(self) -> None: + if not self.is_execution_price_: + return + if not self.config_.key_exists("execution_price"): + self.market_data_df_[f"exec_price_{self.symbol_a_}"] = self.market_data_df_[ + f"{self.stat_model_price_}_{self.symbol_a_}" + ] + self.market_data_df_[f"exec_price_{self.symbol_b_}"] = self.market_data_df_[ + f"{self.stat_model_price_}_{self.symbol_b_}" + ] + return + execution_price_column = self.config_.get_value("execution_price")["column"] + execution_price_shift = self.config_.get_value("execution_price")["shift"] + self.market_data_df_[f"exec_price_{self.symbol_a_}"] = self.market_data_df_[ + f"{execution_price_column}_{self.symbol_a_}" + ].shift(-execution_price_shift) + self.market_data_df_[f"exec_price_{self.symbol_b_}"] = self.market_data_df_[ + f"{execution_price_column}_{self.symbol_b_}" + ].shift(-execution_price_shift) + self.market_data_df_ = self.market_data_df_.dropna().reset_index(drop=True) + + def md_columns(self) -> List[str]: + # @abstractmethod + if self.is_execution_price_: + return ["tstamp", "symbol", self.stat_model_price_, self.execution_price_column_] + else: + return ["tstamp", "symbol", self.stat_model_price_] + + def rename_columns(self, selected_symbol_df: pd.DataFrame) -> pd.DataFrame: + # @abstractmethod + symbol = selected_symbol_df.iloc[0]["symbol"] + new_price_column = f"{self.stat_model_price_}_{symbol}" + if self.is_execution_price_: + new_execution_price_column = f"{self.execution_price_column_}_{symbol}" + + # Create temporary dataframe with timestamp and price + temp_df = pd.DataFrame( + { + "tstamp": selected_symbol_df["tstamp"], + new_price_column: selected_symbol_df[self.stat_model_price_], + new_execution_price_column: selected_symbol_df[self.execution_price_column_], + } + ) + else: + temp_df = pd.DataFrame( + { + "tstamp": selected_symbol_df["tstamp"], + new_price_column: selected_symbol_df[self.stat_model_price_], + } + ) + return temp_df + + def tranform_df_target_colnames(self): + # @abstractmethod + return self.colnames() + self.orig_exec_prices_colnames() + def orig_exec_prices_colnames(self) -> List[str]: return [ f"{self.execution_price_column_}_{self.symbol_a_}", f"{self.execution_price_column_}_{self.symbol_b_}", - ] + ] if self.is_execution_price_ else [] - def exec_prices_colnames(self) -> List[str]: - return [ - f"exec_price_{self.symbol_a_}", - f"exec_price_{self.symbol_b_}", - ] +class LiveMarketData(PtMarketData): + def __init__(self, config: Config, instruments: List[ExchangeInstrument]): + super().__init__(config, instruments) + + def md_columns(self) -> List[str]: + # @abstractmethod + return ["tstamp", "symbol", self.stat_model_price_] + + def rename_columns(self, selected_symbol_df: pd.DataFrame) -> pd.DataFrame: + # @abstractmethod + symbol = selected_symbol_df.iloc[0]["symbol"] + new_price_column = f"{self.stat_model_price_}_{symbol}" + temp_df = pd.DataFrame( + { + "tstamp": selected_symbol_df["tstamp"], + new_price_column: selected_symbol_df[self.stat_model_price_], + } + ) + return temp_df + + def tranform_df_target_colnames(self): + # @abstractmethod + return self.colnames() diff --git a/lib/pt_strategy/pt_model.py b/lib/pt_strategy/pt_model.py index 6af809e..45a225c 100644 --- a/lib/pt_strategy/pt_model.py +++ b/lib/pt_strategy/pt_model.py @@ -3,6 +3,9 @@ from __future__ import annotations from abc import ABC, abstractmethod from typing import Any, Dict, cast +# --- +from cvttpy_tools.config import Config +# --- from pairs_trading.lib.pt_strategy.prediction import Prediction from pairs_trading.lib.pt_strategy.trading_pair import TradingPair @@ -13,10 +16,10 @@ class PairsTradingModel(ABC): ... @staticmethod - def create(config: Dict[str, Any]) -> PairsTradingModel: + def create(config: Config) -> PairsTradingModel: import importlib - model_class_name = config.get("model_class", None) + model_class_name = config.get_value("model_class", None) assert model_class_name is not None module_name, class_name = model_class_name.rsplit(".", 1) module = importlib.import_module(module_name) diff --git a/lib/pt_strategy/research_strategy.py b/lib/pt_strategy/research_strategy.py index 7aed24f..670b612 100644 --- a/lib/pt_strategy/research_strategy.py +++ b/lib/pt_strategy/research_strategy.py @@ -1,56 +1,56 @@ from __future__ import annotations -from typing import Any, Dict, List, Optional +from typing import Any, Dict, List, Optional, Tuple import pandas as pd +# --- from cvttpy_tools.config import Config - +# --- +from cvttpy_trading.trading.instrument import ExchangeInstrument +# --- from pairs_trading.lib.pt_strategy.model_data_policy import ModelDataPolicy from pairs_trading.lib.pt_strategy.pt_market_data import ResearchMarketData from pairs_trading.lib.pt_strategy.pt_model import Prediction -from pairs_trading.lib.pt_strategy.trading_pair import PairState, TradingPair - +from pairs_trading.lib.pt_strategy.trading_pair import PairState, TradingPair, ResearchTradingPair class PtResearchStrategy: - config_: Dict[str, Any] - trading_pair_: TradingPair + config_: Config + trading_pair_: ResearchTradingPair model_data_policy_: ModelDataPolicy pt_mkt_data_: ResearchMarketData trades_: List[pd.DataFrame] - predictions_: pd.DataFrame + predictions_df_: pd.DataFrame def __init__( self, - config: Dict[str, Any], - datafiles: List[str], - instruments: List[Dict[str, str]], + config: Config, + instruments: List[ExchangeInstrument] ): from pairs_trading.lib.pt_strategy.model_data_policy import ModelDataPolicy from pairs_trading.lib.pt_strategy.trading_pair import TradingPair self.config_ = config self.trades_ = [] - self.trading_pair_ = TradingPair(config=config, instruments=instruments) - self.predictions_ = pd.DataFrame() + self.trading_pair_ = ResearchTradingPair(config=config, instruments=instruments) + self.predictions_df_ = pd.DataFrame() import copy # modified config must be passed to PtMarketData config_copy = copy.deepcopy(config) - config_copy["instruments"] = instruments - config_copy["datafiles"] = datafiles - self.pt_mkt_data_ = ResearchMarketData(config=config_copy) + config_copy.set_value("instruments", instruments) + self.pt_mkt_data_ = ResearchMarketData(config=config_copy, instruments=instruments) self.pt_mkt_data_.load() self.model_data_policy_ = ModelDataPolicy.create( - Config(config_copy), mkt_data=self.pt_mkt_data_.market_data_df_, pair=self.trading_pair_ + config_copy, mkt_data=self.pt_mkt_data_.market_data_df_, pair=self.trading_pair_ ) def outstanding_positions(self) -> List[Dict[str, Any]]: return list(self.trading_pair_.user_data_.get("outstanding_positions", [])) def run(self) -> None: - training_minutes = self.config_.get("training_minutes", 120) + training_minutes = self.config_.get_value("training_minutes", 120) market_data_series: pd.Series market_data_df = pd.DataFrame() @@ -74,8 +74,8 @@ class PtResearchStrategy: prediction = self.trading_pair_.run( market_data_df, self.model_data_policy_.advance(mkt_data_df=market_data_df) ) - self.predictions_ = pd.concat( - [self.predictions_, prediction.to_df()], ignore_index=True + self.predictions_df_ = pd.concat( + [self.predictions_df_, prediction.to_df()], ignore_index=True ) assert prediction is not None @@ -95,8 +95,8 @@ class PtResearchStrategy: pair = self.trading_pair_ trades = None - open_threshold = self.config_["dis-equilibrium_open_trshld"] - close_threshold = self.config_["dis-equilibrium_close_trshld"] + open_threshold = self.config_.get_value("dis-equilibrium_open_trshld") + close_threshold = self.config_.get_value("dis-equilibrium_close_trshld") scaled_disequilibrium = prediction.scaled_disequilibrium_ abs_scaled_disequilibrium = abs(scaled_disequilibrium) @@ -145,7 +145,7 @@ class PtResearchStrategy: if pair.user_data_["state"] == PairState.OPEN: print(f"{pair}: *** Position is NOT CLOSED. ***") # outstanding positions - if self.config_["close_outstanding_positions"]: + if self.config_.get_value("close_outstanding_positions", False): close_position_row = pd.Series(pair.market_data_.iloc[-2]) # close_position_row["disequilibrium"] = 0.0 # close_position_row["scaled_disequilibrium"] = 0.0 @@ -161,14 +161,14 @@ class PtResearchStrategy: pair.on_close_trades(trades) else: pair.add_outstanding_position( - symbol=pair.symbol_a_, + symbol=pair.symbol_a(), open_side=pair.user_data_["open_side_a"], open_px=pair.user_data_["open_px_a"], open_tstamp=pair.user_data_["open_tstamp"], last_mkt_data_row=pair.market_data_.iloc[-1], ) pair.add_outstanding_position( - symbol=pair.symbol_b_, + symbol=pair.symbol_b(), open_side=pair.user_data_["open_side_b"], open_px=pair.user_data_["open_px_b"], open_tstamp=pair.user_data_["open_tstamp"], @@ -192,7 +192,7 @@ class PtResearchStrategy: return pd.DataFrame(columns=columns).astype(types) def _create_open_trades( - self, pair: TradingPair, row: pd.Series, prediction: Prediction + self, pair: ResearchTradingPair, row: pd.Series, prediction: Prediction ) -> Optional[pd.DataFrame]: colname_a, colname_b = pair.exec_prices_colnames() @@ -226,7 +226,7 @@ class PtResearchStrategy: # create opening trades df.loc[len(df)] = { "time": tstamp, - "symbol": pair.symbol_a_, + "symbol": pair.symbol_a(), "side": side_a, "action": "OPEN", "price": px_a, @@ -237,7 +237,7 @@ class PtResearchStrategy: } df.loc[len(df)] = { "time": tstamp, - "symbol": pair.symbol_b_, + "symbol": pair.symbol_b(), "side": side_b, "action": "OPEN", "price": px_b, @@ -249,7 +249,7 @@ class PtResearchStrategy: return df def _create_close_trades( - self, pair: TradingPair, row: pd.Series, prediction: Optional[Prediction] = None + self, pair: ResearchTradingPair, row: pd.Series, prediction: Optional[Prediction] = None ) -> Optional[pd.DataFrame]: colname_a, colname_b = pair.exec_prices_colnames() @@ -271,7 +271,7 @@ class PtResearchStrategy: # create opening trades df.loc[len(df)] = { "time": tstamp, - "symbol": pair.symbol_a_, + "symbol": pair.symbol_a(), "side": pair.user_data_["close_side_a"], "action": "CLOSE", "price": px_a, @@ -282,7 +282,7 @@ class PtResearchStrategy: } df.loc[len(df)] = { "time": tstamp, - "symbol": pair.symbol_b_, + "symbol": pair.symbol_b(), "side": pair.user_data_["close_side_b"], "action": "CLOSE", "price": px_b, diff --git a/lib/pt_strategy/results.py b/lib/pt_strategy/results.py index af64c5e..5fecfa3 100644 --- a/lib/pt_strategy/results.py +++ b/lib/pt_strategy/results.py @@ -4,6 +4,8 @@ from datetime import date, datetime from typing import Any, Dict, List, Optional, Tuple import pandas as pd +from cvttpy_trading.trading.instrument import ExchangeInstrument + from pairs_trading.lib.pt_strategy.trading_pair import TradingPair @@ -120,7 +122,7 @@ def store_config_in_database( config_file_path: str, config: Dict, datafiles: List[Tuple[str, str]], - instruments: List[Dict[str, str]], + instruments: List[ExchangeInstrument], ) -> None: """ Store configuration information in the database for reference. @@ -141,7 +143,7 @@ def store_config_in_database( datafiles_str = ", ".join([f"{datafile}" for _, datafile in datafiles]) instruments_str = ", ".join( [ - f"{inst['symbol']}:{inst['instrument_type']}:{inst['exchange_id']}" + inst.details_short() for inst in instruments ] ) @@ -292,7 +294,7 @@ class PairResearchResult: pair_return = symbol_a_return + symbol_b_return # Create round-trip records for both symbols - funding_per_position = self.config_.get("funding_per_pair", 10000) / 2 + funding_per_position = self.config_.get_value("funding_per_pair", 10000) / 2 # Symbol A round-trip day_roundtrips.append({ diff --git a/lib/pt_strategy/trading_pair.py b/lib/pt_strategy/trading_pair.py index 4a243c2..792d82f 100644 --- a/lib/pt_strategy/trading_pair.py +++ b/lib/pt_strategy/trading_pair.py @@ -1,17 +1,21 @@ from __future__ import annotations +from abc import ABC, abstractmethod from datetime import datetime from enum import Enum from typing import Any, Dict, List import pandas as pd +# --- +from cvttpy_tools.base import NamedObject +from cvttpy_tools.config import Config # --- from cvttpy_trading.trading.instrument import ExchangeInstrument # --- from pairs_trading.lib.pt_strategy.model_data_policy import DataWindowParams from pairs_trading.lib.pt_strategy.prediction import Prediction -from pairs_trading.lib.pt_strategy.models import PairsTradingModel + class PairState(Enum): @@ -23,62 +27,90 @@ class PairState(Enum): CLOSE_STOP_PROFIT = 6 -def get_symbol(instrument: Dict[str, str]) -> str: - if "symbol" in instrument: - return instrument["symbol"] - elif "instrument_id" in instrument: - instrument_id = instrument["instrument_id"] - instrument_pfx = instrument_id[:instrument_id.find("-") + 1] - symbol = instrument_id[len(instrument_pfx):] - instrument["symbol"] = symbol - instrument["instrument_id_pfx"] = instrument_pfx - return symbol - else: - raise ValueError(f"Invalid instrument: {instrument}, missing symbol or instrument_id") +# def get_symbol(instrument: Dict[str, str]) -> str: +# if "symbol" in instrument: +# return instrument["symbol"] +# elif "instrument_id" in instrument: +# instrument_id = instrument["instrument_id"] +# instrument_pfx = instrument_id[: instrument_id.find("-") + 1] +# symbol = instrument_id[len(instrument_pfx) :] +# instrument["symbol"] = symbol +# instrument["instrument_id_pfx"] = instrument_pfx +# return symbol +# else: +# raise ValueError( +# f"Invalid instrument: {instrument}, missing symbol or instrument_id" +# ) -class TradingPair: - config_: Dict[str, Any] + +class TradingPair(NamedObject, ABC): + config_: Config + model_: Any # "PairsTradingModel" market_data_: pd.DataFrame - instruments_: List[Dict[str, str]] - symbol_a_: str - symbol_b_: str - - stat_model_price_: str - model_: PairsTradingModel # type: ignore[assignment] - - user_data_: Dict[str, Any] - exch_inst_a_: ExchangeInstrument - exch_inst_b_: ExchangeInstrument - + user_data_: Dict[str, Any] + stat_model_price_: str + + instruments_: List[ExchangeInstrument] + def __init__( self, - config: Dict[str, Any], - instruments: List[Dict[str, str]], + config: Config, + instruments: List[ExchangeInstrument], ): - from pairs_trading.lib.pt_strategy.pt_model import PairsTradingModel - - assert len(instruments) == 2, "Trading pair must have exactly 2 instruments" - - self.config_ = config - self.instruments_ = instruments - self.symbol_a_ = get_symbol(instruments[0]) - self.symbol_b_ = get_symbol(instruments[1]) - self.model_ = PairsTradingModel.create(config) - self.stat_model_price_ = config["stat_model_price"] - self.user_data_ = { - "state": PairState.INITIAL, - } + self.config_ = config + self.model_ = PairsTradingModel.create(config) + self.user_data_ = {} + self.instruments_ = instruments + self.instruments_[0].user_data_["symbol"] = instruments[0].instrument_id().split("-", 1)[1] + self.instruments_[1].user_data_["symbol"] = instruments[1].instrument_id().split("-", 1)[1] + def __repr__(self) -> str: return ( f"{self.__class__.__name__}:" - f" symbol_a={self.symbol_a_}," - f" symbol_b={self.symbol_b_}," + f" symbol_a={self.symbol_a()}," + f" symbol_b={self.symbol_b()}," f" model={self.model_.__class__.__name__}" ) + + def colnames(self) -> List[str]: + return [ + f"{self.stat_model_price_}_{self.symbol_a()}", + f"{self.stat_model_price_}_{self.symbol_b()}", + ] + def symbol_a(self) -> str: + return self.get_instrument_a().user_data_["symbol"] + def symbol_b(self) -> str: + return self.get_instrument_b().user_data_["symbol"] + + def get_instrument_a(self) -> ExchangeInstrument: + return self.instruments_[0] + + def get_instrument_b(self) -> ExchangeInstrument: + return self.instruments_[1] + + + +class ResearchTradingPair(TradingPair): + + def __init__( + self, + config: Config, + instruments: List[ExchangeInstrument], + ): + assert len(instruments) == 2, "Trading pair must have exactly 2 instruments" + super().__init__(config=config, instruments=instruments) + + self.stat_model_price_ = config.get_value("stat_model_price") + self.user_data_ = { + "state": PairState.INITIAL, + } + + # URGENT set exchange instruments for the pair + def is_closed(self) -> bool: return self.user_data_["state"] in [ PairState.CLOSE, @@ -86,39 +118,34 @@ class TradingPair: PairState.CLOSE_STOP_LOSS, PairState.CLOSE_STOP_PROFIT, ] + def is_open(self) -> bool: - return self.user_data_["state"] == PairState.OPEN - - def colnames(self) -> List[str]: - return [ - f"{self.stat_model_price_}_{self.symbol_a_}", - f"{self.stat_model_price_}_{self.symbol_b_}", - ] + return not self.is_closed() def exec_prices_colnames(self) -> List[str]: return [ - f"exec_price_{self.symbol_a_}", - f"exec_price_{self.symbol_b_}", + f"exec_price_{self.symbol_a()}", + f"exec_price_{self.symbol_b()}", ] def to_stop_close_conditions(self, predicted_row: pd.Series) -> bool: config = self.config_ if ( - "stop_close_conditions" not in config - or config["stop_close_conditions"] is None + not config.key_exists("stop_close_conditions") + or config.get_value("stop_close_conditions") is None ): return False - if "profit" in config["stop_close_conditions"]: + if "profit" in config.get_value("stop_close_conditions"): current_return = self._current_return(predicted_row) # # print(f"time={predicted_row['tstamp']} current_return={current_return}") # - if current_return >= config["stop_close_conditions"]["profit"]: + if current_return >= config.get_value("stop_close_conditions")["profit"]: print(f"STOP PROFIT: {current_return}") self.user_data_["stop_close_state"] = PairState.CLOSE_STOP_PROFIT return True - if "loss" in config["stop_close_conditions"]: - if current_return <= config["stop_close_conditions"]["loss"]: + if "loss" in config.get_value("stop_close_conditions"): + if current_return <= config.get_value("stop_close_conditions")["loss"]: print(f"STOP LOSS: {current_return}") self.user_data_["stop_close_state"] = PairState.CLOSE_STOP_LOSS return True @@ -143,8 +170,8 @@ class TradingPair: ) return float(instrument_return) * 100.0 - instrument_a_return = _single_instrument_return(self.symbol_a_) - instrument_b_return = _single_instrument_return(self.symbol_b_) + instrument_a_return = _single_instrument_return(self.symbol_a()) + instrument_b_return = _single_instrument_return(self.symbol_b()) return instrument_a_return + instrument_b_return return 0.0 @@ -165,46 +192,56 @@ class TradingPair: open_tstamp: datetime, last_mkt_data_row: pd.Series, ) -> None: - assert symbol in [self.symbol_a_, self.symbol_b_], "Symbol must be one of the pair's symbols" + assert symbol in [ + self.symbol_a(), + self.symbol_b(), + ], "Symbol must be one of the pair's symbols" assert open_side in ["BUY", "SELL"], "Open side must be either BUY or SELL" assert open_px > 0, "Open price must be greater than 0" assert open_tstamp is not None, "Open timestamp must be provided" assert last_mkt_data_row is not None, "Last market data row must be provided" - + exec_prices_col_a, exec_prices_col_b = self.exec_prices_colnames() - if symbol == self.symbol_a_: + if symbol == self.symbol_a(): last_px = last_mkt_data_row[exec_prices_col_a] else: last_px = last_mkt_data_row[exec_prices_col_b] - - funding_per_position = self.config_["funding_per_pair"] / 2 + funding_per_position = self.config_.get_value("funding_per_pair") / 2 shares = funding_per_position / open_px if open_side == "SELL": shares = -shares - + if "outstanding_positions" not in self.user_data_: self.user_data_["outstanding_positions"] = [] - self.user_data_["outstanding_positions"].append({ - "symbol": symbol, - "open_side": open_side, - "open_px": open_px, - "shares": shares, - "open_tstamp": open_tstamp, - "last_px": last_px, - "last_tstamp": last_mkt_data_row["tstamp"], - "last_value": last_px * shares, - }) + self.user_data_["outstanding_positions"].append( + { + "symbol": symbol, + "open_side": open_side, + "open_px": open_px, + "shares": shares, + "open_tstamp": open_tstamp, + "last_px": last_px, + "last_tstamp": last_mkt_data_row["tstamp"], + "last_value": last_px * shares, + } + ) - def get_instrument_a(self) -> ExchangeInstrument: - return self.exch_inst_a_ - def get_instrument_b(self) -> ExchangeInstrument: - return self.exch_inst_b_ - - def run(self, market_data: pd.DataFrame, data_params: DataWindowParams) -> Prediction: # type: ignore[assignment] - self.market_data_ = market_data[data_params.training_start_index:data_params.training_start_index + data_params.training_size] + def run(self, market_data: pd.DataFrame, data_params: DataWindowParams) -> Prediction: # type: ignore[assignment] + self.market_data_ = market_data[ + data_params.training_start_index_ : data_params.training_start_index_ + + data_params.training_size_ + ] return self.model_.predict(pair=self) +class LiveTradingPair(TradingPair): + def __init__(self, config: Config, instruments: List[ExchangeInstrument]): + super().__init__(config, instruments) + + def to_stop_close_conditions(self, predicted_row: pd.Series) -> bool: + # TODO LiveTradingPair.to_stop_close_conditions() + return False + diff --git a/lib/tools/config.py b/lib/tools/config.py index a88aa74..4d84db3 100644 --- a/lib/tools/config.py +++ b/lib/tools/config.py @@ -1,12 +1,12 @@ import hjson from typing import Dict from datetime import datetime +# --- +from cvttpy_tools.config import Config -def load_config(config_path: str) -> Dict: - with open(config_path, "r") as f: - config = hjson.load(f) - return dict(config) +def load_config(config_path: str) -> Config: + return Config(json_src=f"file://{config_path}") def expand_filename(filename: str) -> str: diff --git a/lib/tools/data_loader.py b/lib/tools/data_loader.py index b137dcc..9203782 100644 --- a/lib/tools/data_loader.py +++ b/lib/tools/data_loader.py @@ -1,9 +1,10 @@ from __future__ import annotations import sqlite3 -from typing import Dict, List, cast +from typing import Any, Dict, List, Tuple, cast import pandas as pd +from cvttpy_trading.trading.instrument import ExchangeInstrument def load_sqlite_to_dataframe(db_path:str, query:str) -> pd.DataFrame: df: pd.DataFrame = pd.DataFrame() @@ -45,19 +46,17 @@ def convert_time_to_UTC(value: str, timezone: str, extra_minutes: int = 0) -> st def load_market_data( datafile: str, - instruments: List[Dict[str, str]], + instruments: List[ExchangeInstrument], db_table_name: str, trading_hours: Dict = {}, extra_minutes: int = 0, ) -> pd.DataFrame: - insts = [ - '"' + instrument["instrument_id_pfx"] + instrument["symbol"] + '"' - for instrument in instruments - ] - instrument_ids = list(set(insts)) + + inst_ids = ['"' + exch_inst.instrument_id() + '"' for exch_inst in instruments] + instrument_ids = list(set(inst_ids)) exchange_ids = list( - set(['"' + instrument["exchange_id"] + '"' for instrument in instruments]) + set(['"' + instrument.exchange_id() + '"' for instrument in instruments]) ) query = "select" diff --git a/lib/tools/filetools.py b/lib/tools/filetools.py index 4c3a6e5..950ede2 100644 --- a/lib/tools/filetools.py +++ b/lib/tools/filetools.py @@ -1,17 +1,21 @@ import os import glob from typing import Dict, List, Tuple +# --- +from cvttpy_tools.config import CvttAppConfig +# --- +from cvttpy_trading.trading.instrument import ExchangeInstrument DayT = str DataFileNameT = str def resolve_datafiles( - config: Dict, date_pattern: str, instruments: List[Dict[str, str]] + config: Dict, date_pattern: str, instruments: List[ExchangeInstrument] ) -> List[Tuple[DayT, DataFileNameT]]: resolved_files: List[Tuple[DayT, DataFileNameT]] = [] - for inst in instruments: + for exch_inst in instruments: pattern = date_pattern - inst_type = inst["instrument_type"] + inst_type = exch_inst.user_data_.get("instrument_type", "?instrument_type?") data_dir = config["market_data_loading"][inst_type]["data_directory"] if "*" in pattern or "?" in pattern: # Handle wildcards diff --git a/lib/tools/instruments.py b/lib/tools/instruments.py deleted file mode 100644 index ea8cddd..0000000 --- a/lib/tools/instruments.py +++ /dev/null @@ -1,21 +0,0 @@ -import argparse -from typing import Dict, List - -def get_instruments(args: argparse.Namespace, config: Dict) -> List[Dict[str, str]]: - - instruments = [ - { - "symbol": inst.split(":")[0], - "instrument_type": inst.split(":")[1], - "exchange_id": inst.split(":")[2], - "instrument_id_pfx": config["market_data_loading"][inst.split(":")[1]][ - "instrument_id_pfx" - ], - "db_table_name": config["market_data_loading"][inst.split(":")[1]][ - "db_table_name" - ], - } - for inst in args.instruments.split(",") - ] - return instruments - diff --git a/lib/tools/viz/viz_prices.py b/lib/tools/viz/viz_prices.py index e84bae5..1d2ab4c 100644 --- a/lib/tools/viz/viz_prices.py +++ b/lib/tools/viz/viz_prices.py @@ -8,8 +8,8 @@ def visualize_prices(strategy: PtResearchStrategy, trading_date: str) -> None: import seaborn as sns pair = strategy.trading_pair_ - SYMBOL_A = pair.symbol_a_ - SYMBOL_B = pair.symbol_b_ + SYMBOL_A = pair.symbol_a() + SYMBOL_B = pair.symbol_b() TRD_DATE = f"{trading_date[0:4]}-{trading_date[4:6]}-{trading_date[6:8]}" plt.style.use('seaborn-v0_8') diff --git a/lib/tools/viz/viz_trades.py b/lib/tools/viz/viz_trades.py index 147c278..4fb99b4 100644 --- a/lib/tools/viz/viz_trades.py +++ b/lib/tools/viz/viz_trades.py @@ -1,13 +1,8 @@ from __future__ import annotations -import os -from typing import Any, Dict -from pairs_trading.lib.pairs_trading.lib.tegy.results import (PairResearchResult, create_result_database, - store_config_in_database) -from pairs_trading.lib.pairs_trading.lib.t_strategy.research_strategy import PtResearchStrategy -from pairs_trading.lib.tools.filetools import resolve_datafiles -from pairs_trading.lib.tools.instruments import get_instruments +from pairs_trading.lib.pt_strategy.results import (PairResearchResult) +from pairs_trading.lib.pt_strategy.research_strategy import PtResearchStrategy def visualize_trades(strategy: PtResearchStrategy, results: PairResearchResult, trading_date: str) -> None: @@ -25,8 +20,8 @@ def visualize_trades(strategy: PtResearchStrategy, results: PairResearchResult, origin_mkt_data_df = strategy.pt_mkt_data_.origin_mkt_data_df_ mkt_data_df = strategy.pt_mkt_data_.market_data_df_ TRD_DATE = f"{trading_date[0:4]}-{trading_date[4:6]}-{trading_date[6:8]}" - SYMBOL_A = pair.symbol_a_ - SYMBOL_B = pair.symbol_b_ + SYMBOL_A = pair.symbol_a() + SYMBOL_B = pair.symbol_b() print(f"\nCreated trading pair: {pair}") @@ -51,7 +46,7 @@ def visualize_trades(strategy: PtResearchStrategy, results: PairResearchResult, timeline_df = pd.DataFrame({'tstamp': all_timestamps}) # Merge with predicted data to get dis-equilibrium values - timeline_df = timeline_df.merge(strategy.predictions_[['tstamp', 'disequilibrium', 'scaled_disequilibrium', 'signed_scaled_disequilibrium']], + timeline_df = timeline_df.merge(strategy.predictions_df_[['tstamp', 'disequilibrium', 'scaled_disequilibrium', 'signed_scaled_disequilibrium']], on='tstamp', how='left') # Get Symbol_A and Symbol_B market data @@ -110,8 +105,8 @@ def visualize_trades(strategy: PtResearchStrategy, results: PairResearchResult, type="line", x0=timeline_df['tstamp'].min(), x1=timeline_df['tstamp'].max(), - y0=strategy.config_['dis-equilibrium_open_trshld'], - y1=strategy.config_['dis-equilibrium_open_trshld'], + y0=strategy.config_.get_value('dis-equilibrium_open_trshld'), + y1=strategy.config_.get_value('dis-equilibrium_open_trshld'), line=dict(color="purple", width=2, dash="dot"), opacity=0.7, row=1, col=1 @@ -121,8 +116,8 @@ def visualize_trades(strategy: PtResearchStrategy, results: PairResearchResult, type="line", x0=timeline_df['tstamp'].min(), x1=timeline_df['tstamp'].max(), - y0=-strategy.config_['dis-equilibrium_open_trshld'], - y1=-strategy.config_['dis-equilibrium_open_trshld'], + y0=-strategy.config_.get_value('dis-equilibrium_open_trshld'), + y1=-strategy.config_.get_value('dis-equilibrium_open_trshld'), line=dict(color="purple", width=2, dash="dot"), opacity=0.7, row=1, col=1 @@ -132,8 +127,8 @@ def visualize_trades(strategy: PtResearchStrategy, results: PairResearchResult, type="line", x0=timeline_df['tstamp'].min(), x1=timeline_df['tstamp'].max(), - y0=strategy.config_['dis-equilibrium_close_trshld'], - y1=strategy.config_['dis-equilibrium_close_trshld'], + y0=strategy.config_.get_value('dis-equilibrium_close_trshld'), + y1=strategy.config_.get_value('dis-equilibrium_close_trshld'), line=dict(color="brown", width=2, dash="dot"), opacity=0.7, row=1, col=1 @@ -143,8 +138,8 @@ def visualize_trades(strategy: PtResearchStrategy, results: PairResearchResult, type="line", x0=timeline_df['tstamp'].min(), x1=timeline_df['tstamp'].max(), - y0=-strategy.config_['dis-equilibrium_close_trshld'], - y1=-strategy.config_['dis-equilibrium_close_trshld'], + y0=-strategy.config_.get_value('dis-equilibrium_close_trshld'), + y1=-strategy.config_.get_value('dis-equilibrium_close_trshld'), line=dict(color="brown", width=2, dash="dot"), opacity=0.7, row=1, col=1 diff --git a/research/backtest.py b/research/backtest.py index d023a0e..3b2b523 100644 --- a/research/backtest.py +++ b/research/backtest.py @@ -1,8 +1,18 @@ from __future__ import annotations import os -from typing import Any, Dict +from typing import Any, Dict, List, Tuple +# --- +from cvttpy_tools.app import App +from cvttpy_tools.base import NamedObject +from cvttpy_tools.config import CvttAppConfig + +# --- +from cvttpy_trading.trading.instrument import ExchangeInstrument +from cvttpy_trading.settings.instruments import Instruments + +# --- from pairs_trading.lib.pt_strategy.results import ( PairResearchResult, create_result_database, @@ -10,97 +20,120 @@ from pairs_trading.lib.pt_strategy.results import ( ) from pairs_trading.lib.pt_strategy.research_strategy import PtResearchStrategy from pairs_trading.lib.tools.filetools import resolve_datafiles -from pairs_trading.lib.tools.instruments import get_instruments + +InstrumentTypeT = str -def main() -> None: - import argparse +class Runner(NamedObject): + def __init__(self): + App() + CvttAppConfig() - from pairs_trading.lib.tools.config import expand_filename, load_config + # App.instance().add_cmdline_arg( + # "--config", type=str, required=True, help="Path to the configuration file." + # ) + App.instance().add_cmdline_arg( + "--date_pattern", + type=str, + required=True, + help="Date YYYYMMDD, allows * and ? wildcards", + ) + App.instance().add_cmdline_arg( + "--instruments", + type=str, + required=True, + help="Comma-separated list of instrument symbols (e.g., COIN:EQUITY,GBTC:CRYPTO)", + ) + App.instance().add_cmdline_arg( + "--result_db", + type=str, + required=True, + help="Path to SQLite database for storing results. Use 'NONE' to disable database output.", + ) - parser = argparse.ArgumentParser(description="Run pairs trading backtest.") - parser.add_argument( - "--config", type=str, required=True, help="Path to the configuration file." - ) - parser.add_argument( - "--date_pattern", - type=str, - required=True, - help="Date YYYYMMDD, allows * and ? wildcards", - ) - parser.add_argument( - "--instruments", - type=str, - required=True, - help="Comma-separated list of instrument symbols (e.g., COIN:EQUITY,GBTC:CRYPTO)", - ) - parser.add_argument( - "--result_db", - type=str, - required=True, - help="Path to SQLite database for storing results. Use 'NONE' to disable database output.", - ) + App.instance().add_call(stage=App.Stage.Config, func=self._on_config()) + App.instance().add_call(stage=App.Stage.Run, func=self.run()) - args = parser.parse_args() + async def _on_config(self) -> None: + # Resolve data files (CLI takes priority over config) + instruments: List[ExchangeInstrument] = self._get_instruments() + datafiles = resolve_datafiles( + config=CvttAppConfig.instance().to_dict(), + date_pattern=App.instance().get_argument("date_pattern"), + instruments=instruments, + ) - config: Dict = load_config(args.config) + days = list(set([day for day, _ in datafiles])) + print(f"Found {len(datafiles)} data files to process:") + for df in datafiles: + print(f" - {df}") - # Resolve data files (CLI takes priority over config) - instruments = get_instruments(args, config) - datafiles = resolve_datafiles(config, args.date_pattern, instruments) + # Create result database if needed + if App.instance().get_argument("result_db").upper() != "NONE": + create_result_database(App.instance().get_argument("result_db")) - days = list(set([day for day, _ in datafiles])) - print(f"Found {len(datafiles)} data files to process:") - for df in datafiles: - print(f" - {df}") + # Initialize a dictionary to store all trade results + all_results: Dict[str, Dict[str, Any]] = {} + is_config_stored = False + # Process each data file - # Create result database if needed - if args.result_db.upper() != "NONE": - args.result_db = expand_filename(args.result_db) - create_result_database(args.result_db) + results = PairResearchResult(config=CvttAppConfig.instance().to_dict()) + for day in sorted(days): + md_datafiles = [datafile for md_day, datafile in datafiles if md_day == day] + if not all([os.path.exists(datafile) for datafile in md_datafiles]): + print(f"WARNING: insufficient data files: {md_datafiles}") + exit(1) + print(f"\n====== Processing {day} ======") - # Initialize a dictionary to store all trade results - all_results: Dict[str, Dict[str, Any]] = {} - is_config_stored = False - # Process each data file + if not is_config_stored: + store_config_in_database( + db_path=App.instance().get_argument("result_db"), + config_file_path=App.instance().get_argument("config"), + config=CvttAppConfig.instance().to_dict(), + datafiles=datafiles, + instruments=instruments, + ) + is_config_stored = True - results = PairResearchResult(config=config) - for day in sorted(days): - md_datafiles = [datafile for md_day, datafile in datafiles if md_day == day] - if not all([os.path.exists(datafile) for datafile in md_datafiles]): - print(f"WARNING: insufficient data files: {md_datafiles}") - continue - print(f"\n====== Processing {day} ======") - - if not is_config_stored: - store_config_in_database( - db_path=args.result_db, - config_file_path=args.config, - config=config, - datafiles=datafiles, + CvttAppConfig.instance().set_value("datafiles", md_datafiles) + pt_strategy = PtResearchStrategy( + config=CvttAppConfig.instance(), instruments=instruments, ) - is_config_stored = True + pt_strategy.run() + results.add_day_results( + day=day, + trades=pt_strategy.day_trades(), + outstanding_positions=pt_strategy.outstanding_positions(), + ) - pt_strategy = PtResearchStrategy( - config=config, datafiles=md_datafiles, instruments=instruments - ) - pt_strategy.run() - results.add_day_results( - day=day, - trades=pt_strategy.day_trades(), - outstanding_positions=pt_strategy.outstanding_positions(), - ) + results.analyze_pair_performance() + def _get_instruments(self) -> List[ExchangeInstrument]: + res: List[ExchangeInstrument] = [] - results.analyze_pair_performance() + for inst in App.instance().get_argument("instruments").split(","): + instrument_type = inst.split(":")[0] + exchange_id = inst.split(":")[1] + instrument_id = inst.split(":")[2] + exch_inst: ExchangeInstrument = Instruments.instance().get_exch_inst( + exch_id=exchange_id, inst_id=instrument_id, src=f"{self.fname()}" + ) + exch_inst.user_data_["instrument_type"] = instrument_type + res.append(exch_inst) + return res - if args.result_db.upper() != "NONE": - print(f"\nResults stored in database: {args.result_db}") - else: - print("No results to display.") + async def run(self) -> None: + + if App.instance().get_argument("result_db").upper() != "NONE": + print( + f'\nResults stored in database: {App.instance().get_argument("result_db")}' + ) + else: + print("No results to display.") if __name__ == "__main__": - main() + Runner() + App.instance().run() diff --git a/research/notebooks/pair_trading_test.ipynb b/research/notebooks/pair_trading_test.ipynb index 0bcbff6..c268a7a 100644 --- a/research/notebooks/pair_trading_test.ipynb +++ b/research/notebooks/pair_trading_test.ipynb @@ -14,7 +14,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -36,68 +36,74 @@ "global INSTRUMENTS\n", "\n", "import os\n", + "import sys\n", + "from typing import Dict\n", + "sys.path.append('/home/oleg/develop')\n", + "\n", + "from cvttpy_trading.trading.instrument import ExchangeInstrument\n", "\n", "ROOT_DIR = \"/home/oleg/develop/pairs_trading\"\n", "os.chdir(ROOT_DIR)\n", "\n", - "CONFIG_FILE = f\"{ROOT_DIR}/configuration/ols.cfg\"\n", + "CONFIG_FILE = f\"{ROOT_DIR}/configuration/vecm-opt.cfg\"\n", "\n", "# Date for data file selection (format: YYYYMMDD)\n", - "TRADING_DATE = \"20250605\" # Change this to your desired date\n", + "TRADING_DATE = \"20250910\" # Change this to your desired date\n", + "sys.path.append('/home/oleg/develop')\n", "\n", "# ================================ E Q U I T Y ================================\n", - "# INSTRUMENTS = {\n", + "# pair_settings = {\n", "# \"A\": {\n", - "# \"symbol\": \"COIN\",\n", - "# \"exchange_id\": \"ALPACA\",\n", "# \"instrument_type\": \"EQUITY\",\n", - "# \"instrument_id_pfx\": \"STOCK-\",\n", + "# \"exchange_id\": \"ALPACA\",\n", + "# \"instrument_id\": \"STOCK-COIN\",\n", "# },\n", "# \"B\": {\n", - "# \"symbol\": \"MSTR\",\n", - "# \"exchange_id\": \"ALPACA\",\n", "# \"instrument_type\": \"EQUITY\",\n", - "# \"instrument_id_pfx\": \"STOCK-\",\n", + "# \"exchange_id\": \"ALPACA\",\n", + "# \"instrument_id\": \"STOCK-MSTR\",\n", "# },\n", "# }\n", "# ================================ E Q U I T Y ================================\n", "\n", "# ================================ C R Y P T O ================================\n", - "INSTRUMENTS = {\n", + "pair_settings = {\n", " \"A\": {\n", - " \"symbol\": \"ADA-USDT\",\n", - " \"exchange_id\": \"BNBSPOT\",\n", " \"instrument_type\": \"CRYPTO\",\n", - " \"instrument_id_pfx\": \"PAIR-\",\n", + " \"instrument_id\": \"PAIR-ADA-USDT\",\n", + " \"exchange_id\": \"BNBSPOT\",\n", " },\n", " \"B\": {\n", - " \"symbol\": \"SOL-USDT\",\n", - " \"exchange_id\": \"BNBSPOT\",\n", " \"instrument_type\": \"CRYPTO\",\n", - " \"instrument_id_pfx\": \"PAIR-\",\n", + " \"instrument_id\": \"PAIR-SOL-USDT\",\n", + " \"exchange_id\": \"BNBSPOT\",\n", " },\n", "}\n", "# ================================ C R Y P T O ================================\n", "\n", "# ================================ E Q U I T Y VS. C R Y P T O ================================\n", - "# INSTRUMENTS = {\n", + "# pair_settings = {\n", "# \"A\": {\n", - "# \"symbol\": \"MSTR\",\n", - "# \"exchange_id\": \"ALPACA\",\n", "# \"instrument_type\": \"EQUITY\",\n", - "# \"instrument_id_pfx\": \"STOCK-\",\n", + "# \"exchange_id\": \"ALPACA\",\n", + "# \"instrument_id\": \"STOCK-MSTR\",\n", "# },\n", "# \"B\": {\n", - "# \"symbol\": \"ETH-USDT\",\n", - "# \"exchange_id\": \"BNBSPOT\",\n", "# \"instrument_type\": \"CRYPTO\",\n", - "# \"instrument_id_pfx\": \"PAIR-\",\n", + "# \"exchange_id\": \"BNBSPOT\",\n", + "# \"instrument_id\": \"PAIR-ETH-USDT\",\n", "# },\n", "# }\n", "# ================================ E Q U I T Y VS. C R Y P T O ================================\n", + "INSTRUMENTS: Dict[str, ExchangeInstrument] = {}\n", + "for ab, inst_setting in pair_settings.items():\n", + " exch_inst = ExchangeInstrument(jdict=inst_setting)\n", + " exch_inst.user_data_[\"instrument_type\"] = inst_setting[\"instrument_type\"]\n", + " exch_inst.user_data_[\"symbol\"] = exch_inst.instrument_id().split(\"-\", 1)[1]\n", + " INSTRUMENTS[ab] = exch_inst\n", "\n", - "SYMBOL_A = INSTRUMENTS[\"A\"][\"symbol\"]\n", - "SYMBOL_B = INSTRUMENTS[\"B\"][\"symbol\"]\n", + "SYMBOL_A = INSTRUMENTS[\"A\"].user_data_[\"symbol\"]\n", + "SYMBOL_B = INSTRUMENTS[\"B\"].user_data_[\"symbol\"]\n", "TRD_DATE = f\"{TRADING_DATE[0:4]}-{TRADING_DATE[4:6]}-{TRADING_DATE[6:8]}\"\n" ] }, @@ -117,16 +123,15 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ + "\n", "def setup() -> None:\n", " import sys\n", " import os\n", - " sys.path.append('/home/oleg/develop/pairs_trading/lib')\n", - " sys.path.append('/home/coder/pairs_trading/lib')\n", - " \n", + " sys.path.append('/home/oleg/develop') \n", "\n", " import pandas as pd\n", " import numpy as np\n", @@ -135,8 +140,9 @@ " from IPython.display import clear_output\n", "\n", " # Import our modules\n", - " from pairs_trading.lib.pairs_trading.lib.pairs_trading.lib.pt_strategy.trading_pair import TradingPair, PairState\n", - " from pairs_trading.lib.pairs_trading.lib.pairs_trading.lib.pt_strategy.results import PairResearchResult\n", + " # ---\n", + " from pairs_trading.lib.pt_strategy.trading_pair import TradingPair, PairState\n", + " from pairs_trading.lib.pt_strategy.results import PairResearchResult\n", "\n", " pd.set_option('display.width', 400)\n", " pd.set_option('display.max_colwidth', None)\n", @@ -144,7 +150,9 @@ "\n", " print(\"Setup complete!\")\n", " os.chdir(os.path.abspath(os.path.join(os.getcwd(), \"..\", \"..\")))\n", - " print(f\"Current working directory: {os.getcwd()}\")\n" + " print(f\"Current working directory: {os.getcwd()}\")\n", + "\n", + "# setup() # DEBUG" ] }, { @@ -160,7 +168,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -170,6 +178,8 @@ "import os\n", "import importlib\n", "\n", + "from cvttpy_tools.config import Config\n", + "\n", "def load_config_from_file() -> Optional[Dict]:\n", " global DB_TABLE_NAME\n", " global PT_BT_CONFIG\n", @@ -198,22 +208,24 @@ " print(f\"Unexpected error loading config from {config_file}: {e}\")\n", " \n", " assert config is not None\n", - " PT_BT_CONFIG = dict(config)\n", - " DB_TABLE_NAME = PT_BT_CONFIG[\"market_data_loading\"][INSTRUMENTS[\"A\"][\"instrument_type\"]][\"db_table_name\"]\n", + " PT_BT_CONFIG = Config(config)\n", + " DB_TABLE_NAME = PT_BT_CONFIG.get_value(\"market_data_loading\")[INSTRUMENTS[\"A\"].user_data_[\"instrument_type\"]][\"db_table_name\"]\n", "\n", - "\n" + "# -------- DEBUG \n", + "# setup() \n", + "# load_config_from_file() " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Print Configuration" + "## Prepare Config" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -244,25 +256,24 @@ "\n", " if PT_BT_CONFIG:\n", " print(f\"✓ Successfully loaded configuration\")\n", - " print(f\" Training window: {PT_BT_CONFIG['training_size']} minutes\")\n", - " print(f\" Open threshold: {PT_BT_CONFIG['dis-equilibrium_open_trshld']}\")\n", - " print(f\" Close threshold: {PT_BT_CONFIG['dis-equilibrium_close_trshld']}\")\n", + " print(f\" Open threshold: {PT_BT_CONFIG.get_value('dis-equilibrium_open_trshld')}\")\n", + " print(f\" Close threshold: {PT_BT_CONFIG.get_value('dis-equilibrium_close_trshld')}\")\n", " \n", " # Automatically construct data file name based on date and config type\n", " DATA_FILE = f\"{TRADING_DATE}.mktdata.ohlcv.db\"\n", - " data_directory_a = PT_BT_CONFIG[\"market_data_loading\"][INSTRUMENTS[\"A\"][\"instrument_type\"]][\"data_directory\"]\n", - " data_directory_b = PT_BT_CONFIG[\"market_data_loading\"][INSTRUMENTS[\"B\"][\"instrument_type\"]][\"data_directory\"]\n", + " data_directory_a = PT_BT_CONFIG.get_value(\"market_data_loading\")[INSTRUMENTS[\"A\"].user_data_[\"instrument_type\"]][\"data_directory\"]\n", + " data_directory_b = PT_BT_CONFIG.get_value(\"market_data_loading\")[INSTRUMENTS[\"B\"].user_data_[\"instrument_type\"]][\"data_directory\"]\n", " DATA_FILE_A = f\"{data_directory_a}/{TRADING_DATE}.mktdata.ohlcv.db\"\n", " DATA_FILE_B = f\"{data_directory_b}/{TRADING_DATE}.mktdata.ohlcv.db\"\n", "\n", - " PT_BT_CONFIG[\"datafiles\"] = list(set([DATA_FILE_A, DATA_FILE_B]))\n", + " PT_BT_CONFIG.set_value(\"datafiles\", list(set([DATA_FILE_A, DATA_FILE_B])))\n", " \n", " print(f\"\\nData Configuration:\")\n", " print(f\" Data File: {DATA_FILE}\")\n", " \n", " # Verify data file exists\n", " os.chdir(ROOT_DIR)\n", - " for data_file_path in PT_BT_CONFIG[\"datafiles\"]:\n", + " for data_file_path in PT_BT_CONFIG.get_value(\"datafiles\"):\n", " if os.path.exists(data_file_path):\n", " print(f\" ✓ Data file found: {data_file_path}\")\n", " else:\n", @@ -272,7 +283,12 @@ " )\n", " \n", " else:\n", - " print(\"⚠ Failed to load configuration. Please check the configuration file.\")\n" + " print(\"⚠ Failed to load configuration. Please check the configuration file.\")\n", + "\n", + "# -------- DEBUG \n", + "# setup() \n", + "# load_config_from_file() \n", + "# prepare_config()" ] }, { @@ -288,7 +304,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -308,7 +324,9 @@ " # Create trading pair\n", " PT_RESULTS = PairResearchResult(config=PT_BT_CONFIG)\n", " PT_RESEARCH_STRATEGY = PtResearchStrategy(\n", - " config=PT_BT_CONFIG, datafiles=PT_BT_CONFIG[\"datafiles\"], instruments=list(INSTRUMENTS.values())\n", + " config=PT_BT_CONFIG, \n", + " # datafiles=PT_BT_CONFIG[\"datafiles\"], \n", + " instruments=list(INSTRUMENTS.values())\n", " )\n", "\n", " PT_RESEARCH_STRATEGY.run()\n", @@ -332,7 +350,12 @@ " display(pair.market_data_.head())\n", "\n", " display(pair.market_data_.tail())\n", - "\n" + "\n", + "# -------- DEBUG \n", + "# setup() \n", + "# load_config_from_file() \n", + "# prepare_config()\n", + "# run_strategy()" ] }, { @@ -344,14 +367,15 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "def visualize() -> None:\n", - " from tools.viz.viz_prices import visualize_prices\n", + " from pairs_trading.lib.tools.viz.viz_prices import visualize_prices\n", + " from pairs_trading.lib.tools.viz.viz_trades import visualize_trades\n", + "\n", " visualize_prices(strategy=PT_RESEARCH_STRATEGY, trading_date=TRADING_DATE)\n", - " from tools.viz.viz_trades import visualize_trades\n", " visualize_trades(strategy=PT_RESEARCH_STRATEGY, results=PT_RESULTS, trading_date=TRADING_DATE)" ] }, @@ -368,7 +392,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -386,7 +410,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -396,123 +420,109 @@ "Setup complete!\n", "Current working directory: /home/oleg\n", "Trading Parameters:\n", - " Configuration: /home/oleg/develop/pairs_trading/configuration/ols.cfg\n", + " Configuration: /home/oleg/develop/pairs_trading/configuration/vecm-opt.cfg\n", " Symbol A: ADA-USDT\n", " Symbol B: SOL-USDT\n", - " Trading Date: 2025-06-05\n", + " Trading Date: 2025-09-10\n", "\n", - "Loading /home/oleg/develop/pairs_trading/configuration/ols.cfg configuration using HJSON...\n", + "Loading /home/oleg/develop/pairs_trading/configuration/vecm-opt.cfg configuration using HJSON...\n", "✓ Successfully loaded configuration\n", - " Training window: 120 minutes\n", - " Open threshold: 2\n", - " Close threshold: 0.5\n", + " Open threshold: 1.75\n", + " Close threshold: 1\n", + "[2026-01-11 13:31:46.741606] INFO Config.set_value(): NEW Config parameter [datafiles] is set to [['./data/crypto/20250910.mktdata.ohlcv.db']]\n", "\n", "Data Configuration:\n", - " Data File: 20250605.mktdata.ohlcv.db\n", - " ✓ Data file found: ./data/crypto/20250605.mktdata.ohlcv.db\n", - "OPEN_TRADES: 2025-06-05 13:32:00 scaled_disequilibrium=-2.4460555867838187\n", + " Data File: 20250910.mktdata.ohlcv.db\n", + " ✓ Data file found: ./data/crypto/20250910.mktdata.ohlcv.db\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Log is not instantiated. Using Default Log\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[2026-01-11 13:31:48.046862] INFO Config.set_value(): NEW Config parameter [instruments] is set to [[[instrument_id_=PAIR-ADA-USDT][base_asset_id_=][quote_asset_id_=USDT][price_tick_=0.0][quantity_precision_=0.0001][exchange_id_=BNBSPOT][md_symbol_=][trade_symbol_=][contract_code_=][contract_size_=1.0][specifics_={}][no_loss_proc_queue_=EventProcessQueue:BNBSPOT_PAIR-ADA-USDT][book_top_proc_queue_=EventProcessQueue:TOP_BNBSPOT_PAIR-ADA-USDT][book_depth_proc_queue_=EventProcessQueue:DEPTH_BNBSPOT_PAIR-ADA-USDT][mkt_data_=ExchInstMarketData Object][user_data_={'instrument_type': 'CRYPTO', 'symbol': 'ADA-USDT'}][exchange_id_=BNBSPOT][md_symbol_=][trade_symbol_=][contract_code_=][contract_size_=1.0][price_tick_=0.0][user_data_={'instrument_type': 'CRYPTO', 'symbol': 'ADA-USDT'}], [instrument_id_=PAIR-SOL-USDT][base_asset_id_=][quote_asset_id_=USDT][price_tick_=0.0][quantity_precision_=0.0001][exchange_id_=BNBSPOT][md_symbol_=][trade_symbol_=][contract_code_=][contract_size_=1.0][specifics_={}][no_loss_proc_queue_=EventProcessQueue:BNBSPOT_PAIR-SOL-USDT][book_top_proc_queue_=EventProcessQueue:TOP_BNBSPOT_PAIR-SOL-USDT][book_depth_proc_queue_=EventProcessQueue:DEPTH_BNBSPOT_PAIR-SOL-USDT][mkt_data_=ExchInstMarketData Object][user_data_={'instrument_type': 'CRYPTO', 'symbol': 'SOL-USDT'}][exchange_id_=BNBSPOT][md_symbol_=][trade_symbol_=][contract_code_=][contract_size_=1.0][price_tick_=0.0][user_data_={'instrument_type': 'CRYPTO', 'symbol': 'SOL-USDT'}]]]\n", + "OPEN_TRADES: 2025-09-10 13:50:00 scaled_disequilibrium=np.float64(1.9292245624262738)\n", "OPEN TRADES:\n", " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 13:32:00 OPEN ADA-USDT BUY 0.682562 -2.446056 2.446056 -2.446056 OPEN\n", - "1 2025-06-05 13:32:00 OPEN SOL-USDT SELL 153.597967 -2.446056 2.446056 -2.446056 OPEN\n", + "0 2025-09-10 13:50:00 OPEN ADA-USDT SELL 0.892900 0.001712 1.929225 1.929225 OPEN\n", + "1 2025-09-10 13:50:00 OPEN SOL-USDT BUY 224.156429 0.001712 1.929225 1.929225 OPEN\n", "CLOSE TRADES:\n", " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 13:41:00 CLOSE ADA-USDT SELL 0.683371 -0.329524 0.329524 -0.329524 CLOSE\n", - "1 2025-06-05 13:41:00 CLOSE SOL-USDT BUY 153.047927 -0.329524 0.329524 -0.329524 CLOSE\n", - "OPEN_TRADES: 2025-06-05 14:36:00 scaled_disequilibrium=-2.0656672663903457\n", + "0 2025-09-10 14:04:00 CLOSE ADA-USDT BUY 0.893018 0.001066 0.859822 0.859822 CLOSE\n", + "1 2025-09-10 14:04:00 CLOSE SOL-USDT SELL 224.700367 0.001066 0.859822 0.859822 CLOSE\n", + "OPEN_TRADES: 2025-09-10 14:08:00 scaled_disequilibrium=np.float64(1.7714496652478648)\n", "OPEN TRADES:\n", " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 14:36:00 OPEN ADA-USDT BUY 0.670864 -2.065667 2.065667 -2.065667 OPEN\n", - "1 2025-06-05 14:36:00 OPEN SOL-USDT SELL 149.937010 -2.065667 2.065667 -2.065667 OPEN\n", + "0 2025-09-10 14:08:00 OPEN ADA-USDT SELL 0.894122 0.002284 1.77145 1.77145 OPEN\n", + "1 2025-09-10 14:08:00 OPEN SOL-USDT BUY 224.398883 0.002284 1.77145 1.77145 OPEN\n", "CLOSE TRADES:\n", " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 14:47:00 CLOSE ADA-USDT SELL 0.677909 0.449403 0.449403 0.449403 CLOSE\n", - "1 2025-06-05 14:47:00 CLOSE SOL-USDT BUY 151.278572 0.449403 0.449403 0.449403 CLOSE\n", - "OPEN_TRADES: 2025-06-05 14:55:00 scaled_disequilibrium=-2.0134100228666436\n", + "0 2025-09-10 14:39:00 CLOSE ADA-USDT BUY 0.887826 0.00086 0.719625 0.719625 CLOSE\n", + "1 2025-09-10 14:39:00 CLOSE SOL-USDT SELL 222.863446 0.00086 0.719625 0.719625 CLOSE\n", + "OPEN_TRADES: 2025-09-10 15:36:00 scaled_disequilibrium=np.float64(-1.892487041689297)\n", "OPEN TRADES:\n", " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 14:55:00 OPEN ADA-USDT BUY 0.673174 -2.01341 2.01341 -2.01341 OPEN\n", - "1 2025-06-05 14:55:00 OPEN SOL-USDT SELL 150.812932 -2.01341 2.01341 -2.01341 OPEN\n", + "0 2025-09-10 15:36:00 OPEN ADA-USDT BUY 0.887343 -0.001469 1.892487 -1.892487 OPEN\n", + "1 2025-09-10 15:36:00 OPEN SOL-USDT SELL 223.411486 -0.001469 1.892487 -1.892487 OPEN\n", "CLOSE TRADES:\n", " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 15:22:00 CLOSE ADA-USDT SELL 0.675208 -0.182443 0.182443 -0.182443 CLOSE\n", - "1 2025-06-05 15:22:00 CLOSE SOL-USDT BUY 150.984110 -0.182443 0.182443 -0.182443 CLOSE\n", - "OPEN_TRADES: 2025-06-05 16:03:00 scaled_disequilibrium=-2.109009416680833\n", + "0 2025-09-10 15:47:00 CLOSE ADA-USDT SELL 0.889067 0.001095 0.532319 0.532319 CLOSE\n", + "1 2025-09-10 15:47:00 CLOSE SOL-USDT BUY 223.034736 0.001095 0.532319 0.532319 CLOSE\n", + "OPEN_TRADES: 2025-09-10 16:12:00 scaled_disequilibrium=np.float64(-2.232955950237203)\n", "OPEN TRADES:\n", " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 16:03:00 OPEN ADA-USDT BUY 0.671655 -2.109009 2.109009 -2.109009 OPEN\n", - "1 2025-06-05 16:03:00 OPEN SOL-USDT SELL 150.844181 -2.109009 2.109009 -2.109009 OPEN\n", + "0 2025-09-10 16:12:00 OPEN ADA-USDT BUY 0.883518 -0.002233 2.232956 -2.232956 OPEN\n", + "1 2025-09-10 16:12:00 OPEN SOL-USDT SELL 222.807572 -0.002233 2.232956 -2.232956 OPEN\n", "CLOSE TRADES:\n", " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 16:27:00 CLOSE ADA-USDT SELL 0.663392 -0.340001 0.340001 -0.340001 CLOSE\n", - "1 2025-06-05 16:27:00 CLOSE SOL-USDT BUY 149.116981 -0.340001 0.340001 -0.340001 CLOSE\n", - "OPEN_TRADES: 2025-06-05 16:40:00 scaled_disequilibrium=-2.104262608340289\n", + "0 2025-09-10 16:31:00 CLOSE ADA-USDT SELL 0.883613 -0.000878 0.923953 -0.923953 CLOSE\n", + "1 2025-09-10 16:31:00 CLOSE SOL-USDT BUY 222.768019 -0.000878 0.923953 -0.923953 CLOSE\n", + "OPEN_TRADES: 2025-09-10 17:08:00 scaled_disequilibrium=np.float64(1.9116229424018232)\n", "OPEN TRADES:\n", " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 16:40:00 OPEN ADA-USDT BUY 0.660896 -2.104263 2.104263 -2.104263 OPEN\n", - "1 2025-06-05 16:40:00 OPEN SOL-USDT SELL 149.051567 -2.104263 2.104263 -2.104263 OPEN\n", + "0 2025-09-10 17:08:00 OPEN ADA-USDT SELL 0.892403 0.002847 1.911623 1.911623 OPEN\n", + "1 2025-09-10 17:08:00 OPEN SOL-USDT BUY 223.490975 0.002847 1.911623 1.911623 OPEN\n", "CLOSE TRADES:\n", " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 16:47:00 CLOSE ADA-USDT SELL 0.660624 -0.448926 0.448926 -0.448926 CLOSE\n", - "1 2025-06-05 16:47:00 CLOSE SOL-USDT BUY 148.878845 -0.448926 0.448926 -0.448926 CLOSE\n", - "OPEN_TRADES: 2025-06-05 17:17:00 scaled_disequilibrium=-2.363830112535802\n", + "0 2025-09-10 17:26:00 CLOSE ADA-USDT BUY 0.886084 0.001716 0.822214 0.822214 CLOSE\n", + "1 2025-09-10 17:26:00 CLOSE SOL-USDT SELL 222.226735 0.001716 0.822214 0.822214 CLOSE\n", + "OPEN_TRADES: 2025-09-10 18:36:00 scaled_disequilibrium=np.float64(-1.854279101806788)\n", "OPEN TRADES:\n", " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 17:17:00 OPEN ADA-USDT BUY 0.663076 -2.36383 2.36383 -2.36383 OPEN\n", - "1 2025-06-05 17:17:00 OPEN SOL-USDT SELL 149.702783 -2.36383 2.36383 -2.36383 OPEN\n", + "0 2025-09-10 18:36:00 OPEN ADA-USDT BUY 0.883996 -0.002391 1.854279 -1.854279 OPEN\n", + "1 2025-09-10 18:36:00 OPEN SOL-USDT SELL 222.436718 -0.002391 1.854279 -1.854279 OPEN\n", "CLOSE TRADES:\n", " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 17:41:00 CLOSE ADA-USDT SELL 0.663472 -0.201384 0.201384 -0.201384 CLOSE\n", - "1 2025-06-05 17:41:00 CLOSE SOL-USDT BUY 149.425867 -0.201384 0.201384 -0.201384 CLOSE\n", - "OPEN_TRADES: 2025-06-05 18:02:00 scaled_disequilibrium=-2.242955179241669\n", + "0 2025-09-10 18:44:00 CLOSE ADA-USDT SELL 0.882792 -0.001566 0.613392 -0.613392 CLOSE\n", + "1 2025-09-10 18:44:00 CLOSE SOL-USDT BUY 222.285842 -0.001566 0.613392 -0.613392 CLOSE\n", + "OPEN_TRADES: 2025-09-10 18:59:00 scaled_disequilibrium=np.float64(-2.197312757794817)\n", "OPEN TRADES:\n", " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 18:02:00 OPEN ADA-USDT BUY 0.660815 -2.242955 2.242955 -2.242955 OPEN\n", - "1 2025-06-05 18:02:00 OPEN SOL-USDT SELL 149.455464 -2.242955 2.242955 -2.242955 OPEN\n", + "0 2025-09-10 18:59:00 OPEN ADA-USDT BUY 0.882966 -0.003766 2.197313 -2.197313 OPEN\n", + "1 2025-09-10 18:59:00 OPEN SOL-USDT SELL 222.784979 -0.003766 2.197313 -2.197313 OPEN\n", "CLOSE TRADES:\n", " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 18:36:00 CLOSE ADA-USDT SELL 0.663326 -0.409435 0.409435 -0.409435 CLOSE\n", - "1 2025-06-05 18:36:00 CLOSE SOL-USDT BUY 149.863517 -0.409435 0.409435 -0.409435 CLOSE\n", - "OPEN_TRADES: 2025-06-05 19:03:00 scaled_disequilibrium=-2.5413086373281155\n", + "0 2025-09-10 19:32:00 CLOSE ADA-USDT SELL 0.877003 0.001427 0.903187 -0.903187 CLOSE\n", + "1 2025-09-10 19:32:00 CLOSE SOL-USDT BUY 221.177898 0.001427 0.903187 -0.903187 CLOSE\n", + "OPEN_TRADES: 2025-09-10 20:56:00 scaled_disequilibrium=np.float64(-1.8300787048118858)\n", "OPEN TRADES:\n", " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 19:03:00 OPEN ADA-USDT BUY 0.657905 -2.541309 2.541309 -2.541309 OPEN\n", - "1 2025-06-05 19:03:00 OPEN SOL-USDT SELL 149.240433 -2.541309 2.541309 -2.541309 OPEN\n", + "0 2025-09-10 20:56:00 OPEN ADA-USDT BUY 0.879164 -0.001831 1.830079 -1.830079 OPEN\n", + "1 2025-09-10 20:56:00 OPEN SOL-USDT SELL 222.529393 -0.001831 1.830079 -1.830079 OPEN\n", "CLOSE TRADES:\n", " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 19:19:00 CLOSE ADA-USDT SELL 0.638560 -0.044278 0.044278 -0.044278 CLOSE\n", - "1 2025-06-05 19:19:00 CLOSE SOL-USDT BUY 144.915997 -0.044278 0.044278 -0.044278 CLOSE\n", - "OPEN_TRADES: 2025-06-05 20:02:00 scaled_disequilibrium=-2.0824957059190754\n", - "OPEN TRADES:\n", - " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 20:02:00 OPEN ADA-USDT BUY 0.641034 -2.082496 2.082496 -2.082496 OPEN\n", - "1 2025-06-05 20:02:00 OPEN SOL-USDT SELL 146.100694 -2.082496 2.082496 -2.082496 OPEN\n", - "CLOSE TRADES:\n", - " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 20:13:00 CLOSE ADA-USDT SELL 0.637171 -0.443037 0.443037 -0.443037 CLOSE\n", - "1 2025-06-05 20:13:00 CLOSE SOL-USDT BUY 145.392057 -0.443037 0.443037 -0.443037 CLOSE\n", - "OPEN_TRADES: 2025-06-05 21:24:00 scaled_disequilibrium=-2.2040356379182975\n", - "OPEN TRADES:\n", - " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 21:24:00 OPEN ADA-USDT BUY 0.623426 -2.204036 2.204036 -2.204036 OPEN\n", - "1 2025-06-05 21:24:00 OPEN SOL-USDT SELL 143.260214 -2.204036 2.204036 -2.204036 OPEN\n", - "CLOSE TRADES:\n", - " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 21:46:00 CLOSE ADA-USDT SELL 0.627175 -0.353691 0.353691 -0.353691 CLOSE\n", - "1 2025-06-05 21:46:00 CLOSE SOL-USDT BUY 143.784983 -0.353691 0.353691 -0.353691 CLOSE\n", - "OPEN_TRADES: 2025-06-05 22:13:00 scaled_disequilibrium=-2.3383272565498383\n", - "OPEN TRADES:\n", - " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 22:13:00 OPEN ADA-USDT BUY 0.622229 -2.338327 2.338327 -2.338327 OPEN\n", - "1 2025-06-05 22:13:00 OPEN SOL-USDT SELL 143.277122 -2.338327 2.338327 -2.338327 OPEN\n", - ": *** Position is NOT CLOSED. ***\n", - "CLOSE_POSITION TRADES:\n", - " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 22:27:00 CLOSE ADA-USDT SELL 0.623272 0.0 0.0 0.0 CLOSE_POSITION\n", - "1 2025-06-05 22:27:00 CLOSE SOL-USDT BUY 143.996271 0.0 0.0 0.0 CLOSE_POSITION\n", - "\n", - "Created trading pair: \n", - "Market data shape: (120, 7)\n", + "0 2025-09-10 21:03:00 CLOSE ADA-USDT SELL 0.882105 -0.000235 0.004402 0.004402 CLOSE\n", + "1 2025-09-10 21:03:00 CLOSE SOL-USDT BUY 222.892964 -0.000235 0.004402 0.004402 CLOSE\n", + "538\n", + "Created trading pair: ResearchTradingPair: symbol_a=ADA-USDT, symbol_b=SOL-USDT, model=VECMModel\n", + "Market data shape: (71, 7)\n", "Column names: ['close_ADA-USDT', 'close_SOL-USDT']\n", "\n", "Sample data:\n" @@ -550,54 +560,54 @@ " \n", " \n", " \n", - " 538\n", - " 2025-06-05 20:28:00\n", - " 0.6341\n", - " 145.00\n", - " 0.634859\n", - " 145.040510\n", - " 0.633001\n", - " 144.849478\n", + " 587\n", + " 2025-09-10 21:18:00\n", + " 0.8833\n", + " 222.86\n", + " 0.883344\n", + " 222.933113\n", + " 0.883340\n", + " 222.974782\n", " \n", " \n", - " 539\n", - " 2025-06-05 20:29:00\n", - " 0.6325\n", - " 144.70\n", - " 0.633001\n", - " 144.849478\n", - " 0.631404\n", - " 144.555341\n", + " 588\n", + " 2025-09-10 21:19:00\n", + " 0.8832\n", + " 223.04\n", + " 0.883340\n", + " 222.974782\n", + " 0.882884\n", + " 223.022564\n", " \n", " \n", - " 540\n", - " 2025-06-05 20:30:00\n", - " 0.6306\n", - " 144.29\n", - " 0.631404\n", - " 144.555341\n", - " 0.630358\n", - " 144.199642\n", + " 589\n", + " 2025-09-10 21:20:00\n", + " 0.8828\n", + " 223.01\n", + " 0.882884\n", + " 223.022564\n", + " 0.883016\n", + " 222.963271\n", " \n", " \n", - " 541\n", - " 2025-06-05 20:31:00\n", - " 0.6299\n", - " 144.17\n", - " 0.630358\n", - " 144.199642\n", - " 0.629908\n", - " 144.265002\n", + " 590\n", + " 2025-09-10 21:21:00\n", + " 0.8829\n", + " 222.92\n", + " 0.883016\n", + " 222.963271\n", + " 0.882924\n", + " 222.895714\n", " \n", " \n", - " 542\n", - " 2025-06-05 20:32:00\n", - " 0.6296\n", - " 144.12\n", - " 0.629908\n", - " 144.265002\n", - " 0.627896\n", - " 143.279860\n", + " 591\n", + " 2025-09-10 21:22:00\n", + " 0.8830\n", + " 222.86\n", + " 0.882924\n", + " 222.895714\n", + " 0.882534\n", + " 222.882527\n", " \n", " \n", "\n", @@ -605,11 +615,11 @@ ], "text/plain": [ " tstamp close_ADA-USDT close_SOL-USDT vwap_ADA-USDT vwap_SOL-USDT exec_price_ADA-USDT exec_price_SOL-USDT\n", - "538 2025-06-05 20:28:00 0.6341 145.00 0.634859 145.040510 0.633001 144.849478\n", - "539 2025-06-05 20:29:00 0.6325 144.70 0.633001 144.849478 0.631404 144.555341\n", - "540 2025-06-05 20:30:00 0.6306 144.29 0.631404 144.555341 0.630358 144.199642\n", - "541 2025-06-05 20:31:00 0.6299 144.17 0.630358 144.199642 0.629908 144.265002\n", - "542 2025-06-05 20:32:00 0.6296 144.12 0.629908 144.265002 0.627896 143.279860" + "587 2025-09-10 21:18:00 0.8833 222.86 0.883344 222.933113 0.883340 222.974782\n", + "588 2025-09-10 21:19:00 0.8832 223.04 0.883340 222.974782 0.882884 223.022564\n", + "589 2025-09-10 21:20:00 0.8828 223.01 0.882884 223.022564 0.883016 222.963271\n", + "590 2025-09-10 21:21:00 0.8829 222.92 0.883016 222.963271 0.882924 222.895714\n", + "591 2025-09-10 21:22:00 0.8830 222.86 0.882924 222.895714 0.882534 222.882527" ] }, "metadata": {}, @@ -648,53 +658,53 @@ " \n", " \n", " 653\n", - " 2025-06-05 22:24:00\n", - " 0.6235\n", - " 143.84\n", - " 0.623885\n", - " 143.878271\n", - " 0.623162\n", - " 143.873115\n", + " 2025-09-10 22:24:00\n", + " 0.8848\n", + " 223.27\n", + " 0.884698\n", + " 223.240547\n", + " 0.884810\n", + " 223.331089\n", " \n", " \n", " 654\n", - " 2025-06-05 22:25:00\n", - " 0.6226\n", - " 143.86\n", - " 0.623162\n", - " 143.873115\n", - " 0.623348\n", - " 143.924337\n", + " 2025-09-10 22:25:00\n", + " 0.8852\n", + " 223.41\n", + " 0.884810\n", + " 223.331089\n", + " 0.885393\n", + " 223.542908\n", " \n", " \n", " 655\n", - " 2025-06-05 22:26:00\n", - " 0.6241\n", - " 143.93\n", - " 0.623348\n", - " 143.924337\n", - " 0.623569\n", - " 143.876044\n", + " 2025-09-10 22:26:00\n", + " 0.8856\n", + " 223.67\n", + " 0.885393\n", + " 223.542908\n", + " 0.885579\n", + " 223.676085\n", " \n", " \n", " 656\n", - " 2025-06-05 22:27:00\n", - " 0.6236\n", - " 143.88\n", - " 0.623569\n", - " 143.876044\n", - " 0.623272\n", - " 143.996271\n", + " 2025-09-10 22:27:00\n", + " 0.8857\n", + " 223.69\n", + " 0.885579\n", + " 223.676085\n", + " 0.885577\n", + " 223.739131\n", " \n", " \n", " 657\n", - " 2025-06-05 22:28:00\n", - " 0.6232\n", - " 144.04\n", - " 0.623272\n", - " 143.996271\n", - " 0.622659\n", - " 143.887948\n", + " 2025-09-10 22:28:00\n", + " 0.8855\n", + " 223.72\n", + " 0.885577\n", + " 223.739131\n", + " 0.885378\n", + " 223.716529\n", " \n", " \n", "\n", @@ -702,11 +712,11 @@ ], "text/plain": [ " tstamp close_ADA-USDT close_SOL-USDT vwap_ADA-USDT vwap_SOL-USDT exec_price_ADA-USDT exec_price_SOL-USDT\n", - "653 2025-06-05 22:24:00 0.6235 143.84 0.623885 143.878271 0.623162 143.873115\n", - "654 2025-06-05 22:25:00 0.6226 143.86 0.623162 143.873115 0.623348 143.924337\n", - "655 2025-06-05 22:26:00 0.6241 143.93 0.623348 143.924337 0.623569 143.876044\n", - "656 2025-06-05 22:27:00 0.6236 143.88 0.623569 143.876044 0.623272 143.996271\n", - "657 2025-06-05 22:28:00 0.6232 144.04 0.623272 143.996271 0.622659 143.887948" + "653 2025-09-10 22:24:00 0.8848 223.27 0.884698 223.240547 0.884810 223.331089\n", + "654 2025-09-10 22:25:00 0.8852 223.41 0.884810 223.331089 0.885393 223.542908\n", + "655 2025-09-10 22:26:00 0.8856 223.67 0.885393 223.542908 0.885579 223.676085\n", + "656 2025-09-10 22:27:00 0.8857 223.69 0.885579 223.676085 0.885577 223.739131\n", + "657 2025-09-10 22:28:00 0.8855 223.72 0.885577 223.739131 0.885378 223.716529" ] }, "metadata": {}, @@ -714,7 +724,7 @@ }, { "data": { - "image/png": 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I6OjoiKzlxRdf5Msvv6RDhw5cccUV2O12Nm3axO+//07p0qXDib9jbrzxRmrVqoVpmhw8eJAlS5bw7rvvMnLkSN566y2aNWsGwNChQzPc98MPPzBnzpxM7RUrVjxhfNWqVeOWW24BYO/evYwZM4Z7772XZ599luuuu+6E95YsWZKlS5dmSDrllX/HnZKSwsaNG5k0aRLffPMNN998MwMHDjytcT/66CO6dOmS64m/gwcPMn78eF555ZUM7YMGDaJIkSJceeWVlChRgjVr1vDFF18wa9Ysvv/+ezweT7jvrFmzuOeee2jcuDGDBg1i7dq1fPDBBxw4cIDnnnsu3O/VV1/lyJEjXHLJJZQrV45t27bxxRdfMHPmTMaPH09CQkKGGIoVK8ZDDz2Uoe2/CcLsmKbJHXfcwZo1a7jtttuIi4tj9OjR3HjjjYwbN45y5cqF+yYlJXHDDTewe/durrnmGsqUKcPBgwdZtGgRfr//pIm/lJQU+vbtS1JSEv3798fpdDJq1ChuuOEGxo8fT1xcXIb+LVq0oFu3bhnaqlevnul1zZo1+eSTTzL93RERERERkZNT4k9ERERERE7qww8/JF++fIwdOzZT1dOBAwcyvH7llVdYsGABgwYN4oYbbgi3X3/99Xz55Zc8//zzDBkyJENiJK/s37+f0aNH07t3b1544YUM1yzL4uDBg5nuadiwIZdcckmGttWrV3Prrbdy3333MXHiRIoUKZIpofH3338zZ86cTO0nU7Ro0Qz3XHXVVXTu3JlRo0Zlm/gLBoOYponL5cLtdp/SfLnlv3EDPPLIIzz88MOMGjWKsmXLcv3110cktqz8+OOP2O122rVrl6H9nXfeyVSRWbNmTQYMGMCECRPo1atXuH3o0KEkJibyySefhJOtMTExfPTRR/Tt2zec5B04cCANGjTAZjt+2karVq244YYb+OKLL3jwwQczzJcvX75Tft8cM2nSJJYsWcLbb78dft927dqVLl268O677/L666+H+77++uvs3LmTcePGZarQy4nRo0ezefNmvv32W2rXrh1e1xVXXMHIkSMzJS/LlSuXo3V17dqVd999l5SUFGJiYk45LhERERGRi5nO+BMRERERkZPaunUrlSpVynKrw0KFCoV/v3v3bsaOHUvTpk0zJP2O6dOnD02aNGHs2LHs3r37rMacle3bt2NZFvXr1890zTCMDGs5kapVq/LEE09w9OhRvvzyy9wOM4OEhAQqVKgQ3krz2Dl+I0aMYNSoUXTs2JFatWqxYcOGbM/427BhA/fffz9Nmzaldu3adOnShTfffDNDnz179jBw4ECaN29OzZo1ueyyyxg7duwZxe7xeBg6dCgFCxbkww8/xLKs8LURI0Zw7bXX0qRJE2rXrk2PHj2YNGlShvsTExNJTU3l+++/JzExkcTERB5//HEAduzYwbPPPkuXLl2oXbs2TZo04b777mP79u05im3q1KnUrl07U2Ipq21Yj1UbbtiwIdy2fv161q9fT+/evTNUWF5//fVYlsXkyZPDbY0aNcqQ9DvWVrBgwfBWuP8VDAZJSUnJ0Vr+bfLkyRQuXJjOnTuH2+Lj4+natSvTpk3D7/cD6duBjhs3jt69e1O6dGn8fn/42qnMVatWrXDSD9IrWps1a8Yvv/yS5T1erxefz3fCcZs3b05qaipz5849pXhERERERESJPxERERERyYGSJUuyYsUK1q5de8J+v/32G6FQiKuuuirbPldddRXBYJDff/89l6M8uRIlSgDpVVFpaWlnNFaXLl3weDzMnj07N0LLViAQYPfu3RQsWDBD+7hx4/jiiy/o3bs3AwYMoECBAlnev3r1anr37s28efPo3bs3Tz75JB07dmT69OnhPvv376d379788ccf9OnThyeffJIyZcrw5JNPMmrUqDOKPyYmho4dO7Jnzx7Wr18fbv/ss8+oVq0a9913Hw899BB2u53777+fmTNnhvsMHToUl8tFw4YNGTp0KEOHDuWaa64BYNmyZSxZsoTLLruMp556imuvvZZ58+bRt2/fk35tA4EAy5Yty/LMu6zs378fIMPWlStXrgSgVq1aGfoWLVqUYsWKsWrVqhOOmZKSQkpKSqbtMAE2b95M3bp1qV+/Pi1atOCtt94iEAjkKNZVq1ZRvXr1TInGWrVqkZaWxqZNmwBYtGgRPp+PsmXLct9991G3bl1q167Ntddee9LYIX1L0TVr1lCzZs1M12rVqsXWrVtJTk7O0P7999+H57n00kuZMGFClmNXqlQJj8fD4sWLc7RmERERERE5Tlt9ioiIiIjISd16663cfvvtXHXVVdSuXZsGDRrQrFkzmjRpgtPpDPc7ltipWrVqtmMdu/bv6qm8UqRIEa666irGjx9PmzZtaNy4MfXr16dNmzYnPXvvv5xOZ/i8ttwUDAbDW47u3buX4cOHs3///gznKEJ6deWUKVOIj48Pt2VV7fbiiy9iWRbff/99OPEJ6dtwHvPmm28SCoWYMGFCOBF13XXX8dBDDzFs2DCuvfbaDGfbnarKlSsD6ZWjx34/eeQ3iPgAAPOlSURBVPLkDGP26dOHHj16MHLkSNq2bQtAt27dePbZZyldunSmLSLbtm2baQvWdu3acc011zB58uQTJp937dqF1+ulVKlSOYr/448/xm6306VLl3Dbvn37ADKdz3esbe/evScc89NPPyUQCNC1a9cM7aVLl6ZJkyZUqVKF1NRUJk+ezAcffMDmzZt56623Thrrvn37aNiwYab2Y2cE7t27l8TERLZs2QKkb/dZpkwZhgwZQlJSEu+99x433XQTP/300wnPFTx8+DB+vz/b9R+bKzY2FoB69erRtWtXSpUqxd69exk9ejSPPPIISUlJmbaAdTgcFCtWLEOiWEREREREckaJPxEREREROakWLVrw9ddfM3z4cGbPns2SJUv43//+R3x8PC+++CIdOnQACG9NeKJzuY5d+281UF4ZPHgwtWvX5rvvvmPKlClMmTKFIUOG0LRpU4YOHUrRokVzPFZ0dPRpbcd4IrNnz6ZZs2bh13a7nW7dumVI1AF07tw5Q9IvKwcPHmThwoX07ds3Q9IP0rc2hfSzDX/99Ve6du2a6ZzDli1bMnHiRFasWEGDBg1Oe03Hvub//rP6d9LvyJEjhEIhGjRowMSJE3M05r/vDwQCJCcnU6ZMGfLnz8/KlStPmPg7fPgwQJZb1/7XhAkTGDt2LP369aNcuXLhdq/XC4DL5cp0j9vtPuH7e+HChbz33nt07do1w9ca4OWXX87w+qqrrmLQoEF888033HzzzdStW/eE8Xq93ixjOtZ2bJvNY18LwzAYNWpU+GtUvXp1rrnmGr788stMZw/+27Fxslv/v/sAfP311xn69OzZk549e/Lmm2/So0ePTInlAgUKcOjQoROuVUREREREMlPiT0REREREcqR27doMGzYMv9/P6tWrmTp1KqNGjeL+++9n/PjxVKpUKcsEz3/lJDn4X4cPH86w1aHH4yFfvnw5vv9YkgvAZrPRp08f+vTpw6FDh1i8eDFff/01v/32Gw8++CCjR4/O8bipqamntI6cqFOnDg888ACGYeDxeKhYsWKWCaqcVKsdq0asUqVKtn0OHjzI0aNHGTNmDGPGjMm2z5nI6ms+Y8YMPvjgA1atWpXhbLl/f61OxOv18tFHHzFu3Dj27NmT4fzApKSkHI3x73uy8ueff/Lkk0/SsmXLTEmwY4mqrM7F8/l82VZIbtiwgXvvvZfKlSvz4osv5ijOW265hW+++Ya5c+dSt25d/H4/R44cydAnPj4eu92Ox+PJMqZjbceScsfia9euXYavS926dSlVqhRLliwB0v+c//vnmZCQEB4nu/X/e66suFwu+vTpwzPPPMPy5cszVSlalpXj94KIiIiIiBynxJ+IiIiIiJwSl8tF7dq1qV27NuXKlWPgwIFMmjSJe++9N7xd5po1a6hWrVqW969ZswZIP8crp/7v//6PBQsWhF93796dV155JZxYOFZ99V/HznrLLgERFxdHhw4d6NChAzfeeCMLFixgx44dlCxZ8qQxBQIBNm/eHN66MrfExcXRvHnzk/Y7k603/800TQCuvPJKunfvnmWfxMTEM5pj3bp1AJQtWxZIT6jdddddNGrUiGeeeYaEhAScTiffffcdP/30U47GfOGFFxg3bhw33XQTdevWJV++fBiGwYMPPnjShN6x8xKPHj2abZ/Vq1dz1113UblyZd555x0cjoz/+3xsO8t9+/ZRvHjxDNf27dtH7dq1M425a9cubrvtNmJjYxk+fHh4G8yTOTb+sWTfkiVL6Nu3b4Y+06ZNo1SpUiQkJIS3If23Y1uPHtu+89h/CxcunKlvoUKFwn82P//8MwMHDsxwfc2aNRQsWBCXy5XlXMfaTrRVaFbr+rejR4+G3y8iIiIiIpJzSvyJiIiIiMhpq1mzJnA8qdC6dWvsdjs//PBDtlstjh8/HofDQatWrXI8z4ABAzIkaY4lFOLj44mKimLTpk1Z3rdp0yaioqLC59adbC0LFixg3759OUr8TZ48Ga/XS8uWLXO4irxXunRpANauXZttn/j4eGJiYjBNM0cJx1OVkpLC1KlTKV68eDgxPHnyZNxuNyNGjMiwVeR3332X43GPneP3+OOPh9t8Pl+Oqv2KFy+Ox+PJ8kxESD+LsF+/fsTHx/Pxxx9nWdV5LLG9bNmyDEm+PXv2sHv3bnr37p2h/6FDh7j11lvx+/2MHj36pEmxfztWuXlsa9eqVasycuTIDH2OJSKrVq3KokWLME0Tm80Wvr506VKioqIoX748ADVq1AjH+1979+6lQoUKQPp2r/+dC9IrZ6tUqcLy5cszXVu6dCmlS5c+aWLzv+s6JhgMsmvXLtq3b3/C+0VEREREJDPbybuIiIiIiMjFbt68eVlWUc2aNQsgnCQoXrw4PXr0YO7cuVlumfnVV18xb948evbsSbFixXI8f82aNWnevHn417FqQbvdTosWLZgxYwY7d+7McM/OnTuZMWMGLVq0wG63A+mVSOvXr880vt/v548//sBms1GmTJmTxrN69WpefvllChQoQJ8+fXK8jrwWHx9Po0aN+O677zL9+Rz7etrtdrp06cLkyZOzTBCeyTafXq+Xxx57jMOHD3PnnXeGt2602+0YhkEoFAr33b59O9OmTcs0RnR0dJaVece+pv/2+eefZxgzO06nk5o1a2aZtNq3bx+33norhmEwYsSIbM9RrFy5MhUqVOCbb77JMOdXX32FYRhccskl4bbU1FTuuOMO9uzZw/DhwzOcFfhvycnJmbbOtCyLDz74ACCcZC5QoECGvw/NmzcPV7Vecskl7N+/n19//TU8xsGDB5k0aRLt2rULJ1orVKhA1apVmTZtWoav8ezZs9m1a1c4CVykSJFMcx3TpUsXli1bxrJly8JtGzduZN68eRnWn9V7KDk5mU8//ZS4uLhwEvKY9evX4/P5qFevXpZ/TiIiIiIikj1V/ImIiIiIyEm9+OKLpKWl0alTJypUqEAgEGDx4sX88ssvlCxZkh49eoT7Dhw4kI0bN/Lcc8/x+++/hyv7Zs+ezbRp02jcuHGGKq1jtmzZwvvvv5+pvXr16rRt2zbb2B566CF69+5N9+7dueaaayhZsiQ7duxgzJgxGIbBQw89FO67e/duevXqRdOmTWnWrBmFCxfmwIEDTJw4kdWrV3PTTTdlSvT8+eef+Hw+TNPk8OHDLF68mOnTpxMbG8uwYcPClVbnqqeeeorrrrsu/OdTqlQpduzYwcyZM/nhhx8AePjhh5k/fz69e/emV69eVKpUiSNHjrBixQr++OOPDNusZmfPnj3h8VJTU9mwYQOTJk0KJ9KuvfbacN82bdowcuRI+vXrx+WXX86BAwcYPXo0ZcqUCW8Fe0yNGjX4448/GDlyJEWKFKFUqVLUqVOHtm3b8sMPPxAbG0ulSpX466+/mDt3bngbz5Pp0KEDb775JsnJyRkq0/r168e2bdvo168fixYtYtGiReFrhQsXpkWLFuHXjz32GHfddRe33norl112GWvXruXLL7+kV69e4epGgEceeYSlS5fSs2dPNmzYwIYNG8LXYmJi6NixIwArVqzg4Ycf5rLLLqNMmTL4fD6mTJnC4sWLueaaazIlyLLSpUsX6taty8CBA1m/fj1xcXF89dVXhEIh/u///i9D34EDB3Lrrbdy/fXXc+2115KUlMTIkSMpV64c11133Unnuv766/n222/p378/t956Kw6Hg1GjRlGoUCFuvfXWcL8vv/ySqVOn0q5dO0qUKMHevXsZN24cO3fuZOjQoRmqPgHmzp1LVFTUWalAFRERERG50BnWyQ4/EBERERGRi95vv/3GpEmTWLJkCbt37yYQCFCiRAlat27NXXfdRaFChTL0P7ad4Y8//simTZuwLIsKFSrQrVs3rr/+epxOZ4b+7du3Z8eOHVnOffXVV/PSSy+dML4NGzYwbNgw5s+fz5EjRyhQoABNmzblnnvuyZCASU5OZty4ccyaNYv169dz4MABXC4XVapUoWfPnlx99dXhqrT58+dnOEfN6XSSL18+KlasSMuWLendu3e21WAAzz//PF9++WWmRNaJtG/fnsqVK/PRRx9l22f79u106NCBxx57jNtuuy3La4MHD86QjF23bh1vv/028+fPx+fzUaJECbp27cr9998f7nPgwAHee+89pk+fzv79+ylYsCCVKlXi0ksvzbRtZVZxH/v6GYZBTEwMxYsXp169evTq1SvL8+7Gjh3Lxx9/zM6dOylVqhS33347O3bsYNiwYRn+zDZu3MjTTz/NsmXL8Hq94fMdjx49yuDBg5kxYwY+n4/69evz5JNP0q9fPxo3bswrr7xywpgPHDhA69atefnll+nWrVu4/UTnGTZu3JjPP/88Q9vUqVMZNmwYGzZsID4+nu7du3PPPfdkeI+f6P1dsmRJpk+fDqRvffnaa6+xbNky9u/fj81mo0KFCvTu3Ztrrrkm/N48mSNHjjB06FCmTp2Kz+ejVq1aPPbYY9SqVStT37lz5/L222+zatUqoqKiaNOmDY8++miOE9q7d+/m5ZdfZs6cOZimSZMmTRg4cGCG8/nmzJnDiBEjWLt2LYcPHyYqKoratWvTr18/mjVrlmnM3r17U7ZsWV599dUcxSAiIiIiIscp8SciIiIiIiIXpSeeeILNmzdnuS2tRMaqVavo3r0733//ffgcRRERERERyTmd8SciIiIiIiIXpXvvvZdly5Zl2M5TImv48OF06dJFST8RERERkdOkij8RERERERERERERERGRC4Aq/kREREREREREREREREQuAEr8iYiIiIiIiIiIiIiIiFwAlPgTERERERERERERERERuQAo8SciIiIiIiIiIiIiIiJyAVDiT0REREREREREREREROQCoMSfiIiIiIiIiIiIiIiIyAXAEekAzmX79iVFOgS5gNhsBvHxMRw8mIJpWpEOR0QuQHrOiEhe0LNGRPKCnjUikhf0rBGRvKBnjeSWhIR8Oeqnij+RPGKzGRiGgc1mRDoUEblA6TkjInlBzxoRyQt61ohIXtCzRkTygp41kteU+BMRERERERERERERERG5ACjxJyIiIiIiIiIiIiIiInIBUOJPRERERERERERERERE5AKgxJ+IiIiIiIiIiIiIiIjIBUCJPxEREREREREREREREZELgBJ/IiIiIiIiIiIiIiIiIhcAJf5ERERERERERERERERELgBK/ImIiIiIiIiIiIiIiIhcAJT4ExEREREREREREREREbkAKPEnIiIiIiIiIiIiIiIicgFQ4k9ERERERERERERERETkAuCIdAAiIiIiIiIiIiIiIiJy4Tp06BAjRnzI3LmzOXToIPny5adSpcrcfHM/ateuC8CyZX/z6acjWL58GX6/j1KlSnPppVfQq9d12O328FgtWzbk5Zdfo3Xrtjma+95776By5UTuv//hDO0//zyBd955nUmTZgLg9XoZNep/TJ8+hf379xEdHU25chW45prradWqbXisv/5aDIDT6aRAgYJUqVKVyy67gjZt2ofHffnl504Y07ff/kjx4iVyFP+pUuJPREREREREREREREREzpqnnnqMQCDAU089R4kSJTl48ACLFi3k6NEjAMyaNYOnn36cSy+9knffvYfY2Hz8+ecC3n//HZYvX8YLL7yCYRhnNcZXX32ZlSuX8+CDj1KuXAWOHDnC8uV/c+TIkQz9rriiO/369ScUCrF3715++20GzzzzBF27XsGAAU/SoUMnmjRpFu7/5JOPUb58Rfr16x9uK1gw7qytQ4k/EREREREREREREREROSuSkpL4++8lvPvuR9Sr1wCAYsWKU716TQDS0tIYOvRFWrZszYABT4bvu+KKq4iLi+fxxx9i+vQpdOjQ+azGOWfOb9x//yM0a9YSgOLFS1C1arVM/TweD4UKFQagSJGi1KxZi7JlyzF48PO0b9+RRo2a4HZ7wv0dDkeGe842nfEnIiIiIiIiIiIiIiIiZ0VUVBRRUdH8/vtM/H5/pusLFszjyJEjXHfdjZmutWzZmtKlyzB16uSzHmd8fCH++GMOqakpp3xv166Xky9ffmbNmnEWIjs1qvgTERERERERERERERE5Txl79mCcRrLqdFnRMVhFi+a4v8Ph4Mknn2HIkJcYP34ciYmJ1K3bgA4dOlOpUmW2bdsCQNmy5bO8v2zZcmzbtjVXYj+Rxx57kuefH8Sll3agUqUq1K5dh7ZtO4TPIDwRm81G6dJl2L1751mP82SU+BMRuUgYhw7i+XwUtt27SHnqOYiOznDdOXc27u+/I/mFweDxZDOKiIiIiIiIiIiInCuMpKPke+Q+sKy8m9RmI+m94Vj58uf4lrZtO9CsWUuWLl3CihXLmTdvLqNHf8aAAU+F+1hnuIa//17CI4/cF3796KNP0Llz1xzfX7dufb755gdWrFjGsmV/s2jRQr799mtuu60/N9/c76T3W5Z11s8hzAkl/kRELlC2PbvxfD4Ky+XGKlgQ5+xZYHdg+P1EfT6StP73HO9sWbi/+xbbnl24ZkzD3/WyyAUuIiIiIiIiIiIiOWLly0/Sa+/kfcXfKST9jnG73TRq1JRGjZpy8839eOWVFxgx4iPuu+9hALZs2UStWnUy3bd582bKl8+6GvDfqlatxsiRo8Ov4+PjAYiJiSElJTlT/+TkJGJiYjO0ORwO6tSpR5069bjhhpsZNep/jBr1P/r0uQmn05nt3KFQiO3bt1GtWvWTxnm2KfEnIhIBxt69WAkJcLY+AeLzEf3WaxgpKYSKFce+ZRPBRk3wXncDjsWLiBr+PoE69Qk2bQaAY9FCbHt2ESpfEffEH/F36AQu19mJTURERERERERERHKNVbQoeVjvl2vKlSvP77/PpHHjpuTPX4Cvv/4iU+Jv9uxZbN++ldtvv/Ok47ndHkqVKp2pvUyZcixYMC9T+5o1qylduswJxyxfvgKhUAi/33fCxN8vv/xEUtJR2rbtcNI4zzYl/kRE8ph943pinn4C32VX4rvuhtwbOBQCmw2AqJEfY9u9m+TnXsIsUzZDt0CrNjj+WkzUyOGklCyJWboM7okTCCVWI61ff2IfexDXbzPwd+yS87kt6+wlMUVEREREREREROS8deTIYQYNepzLLruSihUrEx0dzerVqxg9+nNatmxDVFQUjz46kGeffZIhQ16iZ8/exMTEsGjRAt577x3atu1A+/adMoy5a9cO1q1bk6GtVKkyREVFZZr/qqt68t133/DWW69y+eVX4XI5mTt3NlOnTmbIkDfD/e699w46duxC1arVKVCgAJs3b+Sjj96jfv2GGSoDvV4vBw7sJxQKsXfvXn77bQbffDOaq666mvr1G+byn96pU+JPRORUBYNgmuGKOCPpKJ6vv8TfvBWhGjVPervzt1ngcOKe+CNm0aIE/vOP1mlJTibfE49iJCVhxsVh27uHtDvvzZT0Sw/YwHvr7cS89ByxzzyJr/Ml2NetIfWhxzCLlyDQpDmuCT/gb9sBHCf5ZyIlBc/XX+KcP5fkl15Nr2LMZbZNGzFCIUKVKuf62CIiIiIiIiIiInJ2RUVFU716TcaMGc3OndsJBoMUKVKUK664ir59bwGgXbuOxMcX4tNPP+Gee/rh9/spVao0ffveSu/e12U6O+/dd9/MNM977/2POnXqZmovWbIU7703nOHD3+eBB+4mGAxQpkw5XnhhCE2bNg/3a9KkGZMmTWT48Pfxer0ULlyY5s1bccstGc/3mzDheyZM+B6n00n+/AVITKzGc88Npk2bdrnwp3XmDOtMT0u8gO3blxTpEOQC4nDYiIuL4dChFIJBM9LhyBnwjPwfzj9m4+96OcEqVYn+6D2MgwewCsaRNOQNiInJ/uZAgHz/1x9/2w4Yfj+uqZNJfeRxgrXrnlFMUR9/gGPBfHxX9cR28AChkiVPnlD0eoka+T+cc37DLF6S5KFvgGFg276N2IGPEGjdlrRb7wC7Pcvb7atWEv3e2xhpaQD4Ol+C75rrz2gd/2XbvYuYQQMxvGl4e1+H//JuYFnYdu7ALF4i29guVnrOiEhe0LNGRPKCnjUikhf0rBGRvKBnjeSWhIR8OepnO8txnJaFCxdy55130rJlSxITE5k6dWqG648//jiJiYkZft12221ZjuX3++nWrRuJiYmsWrUqL8IXkQucfdNGrKho3D98T8zg5zHj4kl59iXw+fB89fkJ73UsWYyRnEygVRu8N9xEsGZtoj56H5IzHy6b43iWL8M5awbe6/rgv+wKvDfenLMqQo+HtDvvIfXeB0m7657wVp1mqdKk3XE3zt9nEf326+DzZb43ECDqo/cwE4qQNPRN/K3b4po5Pb0aMrd4vUS/9RpWgYL4LrsSz5jRxD7xKPnuvJXYxx/G9cvE3JtLRERERERERERE5AJwTib+UlNTSUxM5Jlnnsm2T6tWrZg9e3b41xtvvJFlv6FDh1KkSJGzFaqIXGwsC9vunfg7dCLp9XdIu+NuUgY9R6hSZbzX9cE1czr25cuyvd01exah8hUxS5YCm420fv3B7yfqJAnDbHm9RI34iFC1GgTadTz1+w2DYNNmhCpUytAcaNWG1IcH4Fi+jOh330w/w+/f65g5DduB/aT1649VqBD+Dp0wko7iXDj/9NbxX5ZF1Ijh2PbuJfWBh/Fd24fUhwdgFimaXmlZszau32ZkiktERERERERERETkYnZOJv7atGnDgw8+SKdO2VesuFwuEhISwr8KFCiQqc+sWbOYM2cOAwYMOJvhishFxEhOwkhNxSxaHKtQIQKt24bPwQu060ioanViXh9C1AfDsK9amfHeo0dw/LWEQKvW4TYrvhDe627AOWsG9mVLTy0Yv5/oN4diO3o0PYH4n32uz1SwTj1S77kPx1+Lcc6dffyCz4d7/DgCzVulJzBJrxIMVa2Oa9qU9OtjRhP1/rsYyae+ZbKRdJTooS/jnDeHtNvvxCxVOj2eeg1IffBRfN2vxn/p5dh27sC+aUOurFVERERERERERETkQuCIdACna8GCBTRr1oz8+fPTtGlTHnjgAeLi4sLX9+/fz6BBg3jvvffweDynNYfNZmCz5e4P0uXiZbfbMvxXzk+2vbsxDANb6ZI4HJm/lr5HHsM5bQrOmdNxzf2dYNt2+G7pB8Eg7tGfY9gNzJatMtxrdeqEuWAuMZ8MJ/WlwZA/8wcZjjG2b8Pw+bAKFcL94fvY168jbcAT2EqWODuf5GjShFDzlkR/MYqUenUhfwGck6ZgS0km2PuaDOsIde6M+923yf/4wxhHDoHThXPQGrwPPoxZoWKOpjN27iTq5RcwfF68A5/Cql0n63+o6taF+Hjcc37DX6VKbqz0gqDnjIjkBT1rRCQv6FkjInlBzxoRyQt61kheMyzr3N4nLTExkffee4+OHY9vYTdx4kQ8Hg+lSpVi27ZtvPHGG0RHRzNmzBjsdjuWZXH77bdTv3597r77brZv306HDh0YP3481apVy/HclmVh5HIFjYic56ZNg7fegrFjwe3Ovp9lwdSp8OGHUKJE+hl+yclwxx2QVTXz3r3w0ENQvDi89BK4XMe3sTz2HPrjDxg8+Hi7ywVPPw116uTqEjM5cgTuugvKlIGoKFi6FNq3h3vuydgvGIT+/SEhAf7v/8DphFdegY0boWpVqF0bLrsMsqjQDnv1VVi9Ov2+hIQTxzVyJEyZAp99Fq66FBEREREREREREbmYnZc/Kb3sssvCv09MTCQxMZGOHTuGqwA///xzUlJS6N+//xnNc/Bgiir+JNfY7Tby54/i6NE0QiEz0uHIaXKt24QjX0FSU4OQGjxx54bNsT1VHM87b2IWLYFvYD+shCJwKCVzX2cMtvsfIer5Zwg9/xJmQhGcv8/Cio3Fe3t/cLmJevkVgvUbEriiG8a+vVglSmKWKZv1eLnKgeOGm3F//BGhipUIXdGdQOdLsp73lTfAbj+erHz8aRwzp+NYvgz7mG8JrtuI774Hs5zFOHiA6Jm/4e9zIwFH9EnXZTRsRvSYb/FO+41Q4yZnusgLgp4zIpIX9KwRkbygZ42I5AU9a0QkL+hZI7klLi4mR/3Oy8Tff5UuXZq4uDi2bNlCs2bNmDdvHn/99Re1atXK0K9nz55cccUVDBkyJEfjmqaFaZ7TBZFyHgqFTIJBPeDPV84dOwkWLZbzr2GpsviHvHk8EXai+8pVxLzr/4h+5w2M2Hz4WrbBvmE9nuefBbeHYJlypNxxT3qlX9kKJx8vFwUbNcPbqNl/GrOa2wYhCzhWrWgn2K4TtOuEa8J4POPGEkxKSa8c/A/3pEmYDidpLdrkbF3FShIsVx77zBn46jc61SVd0PScEZG8oGeNiOQFPWtEJC/oWSMieUHPGskrF0Tib/fu3Rw+fJiEf7aFe+qpp3jggQfC1/fu3cttt93Gm2++SZ2zvSWeiJy3jH37iHnlBczSZfC3aUewdt306rV/se3eSahi5VMcOOeVw8FGTUh6/V2s+Pj07SstC9e0X3EsWUxa/7vTk37nqUDTFnjGjMa5aCGBlq0zXvT7cU2fSqB1W4iOzvGY/nYdiBr5P4x9+7BOtjWoiIiIiIiIiIiIyAXunEz8paSksHXr1vDr7du3s2rVKgoUKECBAgUYNmwYXbp0oXDhwmzbto1XX32VsmXL0qpVKwBKlCiRYbzof36IXKZMGYoVK5Z3CxGR84dpEv3hMAy/H9ue3US/PoRA0xak3Xv/8T6WhX33bgIt25zVUKwiRY6/MAz8Hbvg79jlrM6ZF6yEBEJVquKcOztT4s/5xxyMlGT8nS85pTEDLVrjGTMa95RJeK+/MTfDFRERERERERERETnvnJOJv+XLl9O3b9/w68GDBwPQvXt3nn32WdauXcv48eNJSkqiSJEitGjRgvvvvx/XeVwJIyJnl2vSz7imTwHAcrnwXncjoRo1j1//6Qfsa1eT8sQzhKpWw/XrJDxfjMLXsxdm8fQPExiHDoLfh6kPEJy2QIuWeD79BOPoEaz8BdIbU1Jw/zCOYJ16mMWKn9qAbjf+dh1xTZ+Ct0cv8HhyP2gRERERERERERGR88Q5mfhr0qQJa9asyfb6iBEjTmm8UqVKnXA8EbmAWRae0Z/j+uUnAk1bYMXFYd+wnpihL5N2170E6tbHOfd3PGO/wXd5N0LVqgPpW0i6fxiH6+ef8N52BwC23bsBwolAOXWBxk3xfDoS57y5+Dt3Bcsi+qP3MJKT8N5482mN6e/QGffEH3HNnnVBVEaKiIiIiIiIiIiInK5zMvEnIpJbPCP/h2vGVLx9b0lPNAEEg0QN/4CoYW8R5faA30egYWN8PXsfv9Hlwt+lK+7vv8N3dW+sAgWx7d4JNhtmQpGsJ5OTsvLlJ1i7Dq5JP4PdjrFvH47Ff5L68ADMoqdXSWklJBBo2BjX5En4O3Q+pTMVRURERERERERERC4ktkgHICJythiHD6Un/a694XjSD8DhIO2ue/H2uQnf5VeS9MYw0u5/GBwZPwvh69AZ7HZcv04CwL57d3rSz6HPTJwJb8/eWPkL4Pl0JO6ffsDXrQfBeg3OaEx/18ux7dqBc87vuRSliIiIiIiIiIiIyPlHP70WkfOSbesWoj56j0DrdvjbdwSnM1Mf5x9zwWbH36Zd5gEMA3/Xy048SWws/rbtcU2ZRLBeA2y7d512VZocZ5avQMqzL0JaGvYd2wlVrHTGY4aqJBJo3AzP6M8J1GsAMTG5EKmIiIiIiIiIiIjI+UUVfyJyXnL/PAH77t14vhhFvofvw7FoYaY+zrmzCdapC7Gxpz2P76oemMVLEvPCM9hXrcQsVvwMopYMoqIIVaqca1tzevv0xfD58Hw/NlfGExERERERERERETnfqOJPRPKeZeEeMxqzXHkCTZuf8u1GchLOeX/g7dmLYMPGeL78jOg3X8V3eTd8va4Fux3b7l3YN20g9bIHzyzUfPlJGfQcntGf4/r1F0KlSp/ReHL2WIUK4b2qJ55vvyJYsxbBOvXAsnD+MQfnrBkYfn96v9hYzCJFCVWukv7+05mAIiIiIiIiIiIicoFQ4k9E8pxryiTcP/1AsEbNEyf+LAvj4EGsQoUyNDt/mwWWRaBNO6z8BUh9eACun3/CM+ZLHBvWk3rPfTjnzsbyRBGsf2ZnxwHgcODtewv+tu0xS5Q88/HkrPF3vQznnwuIfu2V9G1Z7XZsO3cQrFkLs2TJ9PfU0aM4li/F9esvOBYuIO32OyEqKtKhi4iIiIiIiIiIiJwxJf5EJE/Z163F8+XnWAUKYt+0ESwr24or58zpRH0ynJQnniFUrXp6o2XhmjaFQKMmWPkLpLcZBv7LriBUoSLRw94i9qnHwTAINmoMLleuxW6WKZtrY8lZ4nCQ8uyL2FevwjVrOobXS9odd6dvKfrfrvPnEfXxB8Q+/QQpzzyPFZsvAgGLiIiIiIiIiIiI5B6d8SciZ52RdBT3+O+I+vgDot8YSqhCRdJuvR0jNRXb3j3Z3uf8Yw5YFtEfvAspKQDYVyzHtmcX/o6dM/UPVatO8ktDMIsVxzh0EH/zVmdtTXIOMwxC1aqTdue9pD7wSJZJP4Bgk6akPPcStl07cCz9O4+DFBEREREREREREcl9qvgTkbPO8+VnOOfPI1SqNMHadfFeez3Y7QDYNm1K35LxP4ykozhWr8R3ZXdcUycTNWI4ocSquH8Yh1m6DKHEqlnOZRWMI2XgIOwbN2Sb8BE5xixZCiu+ELZtWyMdioiIiIiIiIiIiMgZU+JPRM4uvx/nwgX4ruiGr0evDJes+ELYN28k2LRZptsci/4Ey8LfpStm6TJEvfc2zoXzCLRsjbfnNdluDwqA3U6ocpXcXolcoEKlSmNX4k9EREREREREREQuAEr8iUiWbHt245r0M95e10J09GmP41i8CHxeAs1bZroWKlce+6YN4df25cvSq/Q8HpwL5xNKrIZVoCCBZi2wDBtm2bKYxUucdiwiWTFLlcaxYF6kwxARERERERERERE5YzrjT0Sy5Jr0M64pk4h5dTB4vWBZOP5ajH3F8lMbZ+7vhMpXxCxWPNO1UPkK2DdvAsvCvnYNMa+8QMzQlzEOHcSxfBmBRk3CfYNNmynpJ2dFqHQZbPv3QVpapEMREREREREREREROSOq+BORzEwT54J5BGvVwb5uLTFDXoJgML06z+UmacgbWAkJANh27cSMLwRud6ZhjOQkHH//hfe6G7KcJlS+AkZKCsbevbgm/4IVF499y2ZiBw2EUJBAw8ZndZkikL7VJ4B9x3adCykiIiIiIiIiIiLnNVX8iUgm9tWrMI4cxtezN6mPPYF96xaw20l9eABWbCxRIz5MrwD8cwGxAx4i5uXnM1ZL+f3p1xfMAzNEIIsz/CA98QfgXPwnzoXz8F3ejZRHB2KkphKqWBmrUKG8WK5c5MySpcAwsOmcPxERERERERERETnPqeJPRDJxzv8Ds1BhQhUrgWFw9IP/gdMJhkGazUb0q4PxfDIc12+zCNaohX39OmJee4W0G27C/dOPOOfPBbcHyzAI1qiJVTAuy3msAgWx4uJxf/cNlsuNv3VbiIoi+YXB4NDjSfKIy4VZpBj27dsIRDoWERERERERERERkTOgn6yLSEahEM4F8wi0agOGkd7mcoUvB+vUI9CiNa4Z0wg2aETq/z2IfeMGYoa8ROygxzELFcbb5yYwTWwH9hNo3vLE05WvgGPxn/i7XApRUcA/FVgieShUpgy27ar4ExERERERERERkfObEn8ikoF91UqMpKPZbs8JkNb3FkJVquBv0x4cDkJVEkl58mlsW7cSaNEqvTowh0IVKuJYsgh/50tyI3yR02KWLIVr+tRIhyEiIiIiIiIiIiJyRpT4ExEAjP37cSxfimv6VMwiRQmVr5h955gY/B06Z2gKVahEqEKlU57X37EzoYqVMIsWO+V7RXJLqFQZjKNHMI4ewcpfINLhiIiIiIiIiIiIiJwWJf5ELnZeL55x3+L65ScAQuXK473hpuPbfJ5lVmw+grXq5MlcItkxy5QBwLZtG6EaSvyJiIiIiIiIiIjI+UmJP5GLmG3HdqJfewXb4cN4e1+Hv11HiI2NdFgiec4sWgzsDuzbtxGqUTO90bJwfz8Wf5v2WIUKRTZAERERERERERERkRxQ4k/kIub+cTxYFsmDX8UsVjzS4YhEjt1OqFQp7Bs3hJscy5fiHvcttu3bSLvvoQgGJyIiIiIiIiIiIpIztkgHICIRkpaGc+F8Au06KOknAgQbN8W5YB5GchIAzhnTwenCuWAe9rVrIhydiIiIiIiIiIiIyMkp8SdykXIunA8BP/4WrSMdisg5wd+uA1gWzhnTMJKO4ly0EO/V1xAqWw7Pl5+BZUU6RBEREREREREREZETUuJP5CLl+n0WwWo1sAoXjnQoIucEK38BAs1b4J4yGedvswAItGqN9/q+2DeswzF/XoQjFBERERERERERETkxJf5ELkLGvn3YV60g0KpNpEMROaf4OnfFOHgAz9gxBBo0wspfgFCNmgTrNyTq0xEYBw9EOkQRERERERERERGRbCnxJ3KxSE7G/cM4XL9MxDPuG3B7CDRqEumoRM4pZrnyhKpWh4CfQLv24fa0fv3B6ST6nTchGIxghCIiIiIiIiIiIiLZc0Q6ABE5+2ybNxH99uvYDh9Obwj48bdtDx5PROMSORd5e/bG9esvBGvUCrdZ+QuQet9DxLzwDJ7Rn+Pte0sEIxQRERERERERERHJmhJ/Ihc4x99LiH7zNUKlS5P0xDNYhQtjHD2CFRMb6dBEzkmhatVJq1Y9c3ulynivvxHP5yMJtGxFqEKlCEQnIiIiIiIiIiIikj1t9SlyIQsG8Xw2kmBiIimDnsdKSADDwCpQEBzK+4ucKn+nLphFi+P+4ftIhyIiIiIiIiIiIiKSiRJ/Ihcw5++zsO3Zjff6vuByRTockfOfzYbvyqtwLFqIbeuWSEcjIiIiIiIiIiIikoESfyIXqkAAz/djCTRpjlm2XKSjEblgBFq0wiycgHv8uEiHIiIiIiIiIiIiIpKBEn8iFyjX9KkYhw7i69kr0qGIXFgcDvxXdMO5cB62nTsiHY2IiIiIiIiIiIhImBJ/IhcSy8Ixfx7Rr7yA54tRBFq3xSxRMtJRiVxw/K3bgcOJ4++/Ih2KiIiIiIiIiIiISJgj0gGISO5xTRiP55uvCFVOJO22/gSat4x0SCIXJqcTs1BhbAcPRDoSERERERERERERkTAl/kQuEPbly/B8+zW+K7vj631dpMMRueCZ8fEYBw9GOgwRERERERERERGRMCX+RM4zRnISrimTCZUrTzCxGths2HdsI/q9twnWqInv6msiHaLIRcGKi8e2d0+kwxAREREREREREREJU+JP5Dzj/nYMrmm/pr8wDLAsAMxChUm7+z6w6ehOkbxgxsdjX7Mq0mGIiIiIiIiIiIiIhCnxJ3Iese3YjmvGVLzX3UiwYSPsq1aCw4FZpCih0mUgKirSIYpcNKz4eGyHDqUn3w0j0uGIiIiIiIiIiIiIKPEncj7xfPUFZqHC+DtfAk4nZtFikQ5J5KJlxheCUBDj6BGsAgUjHY6IiIiIiIiIiIgI2hNQ5DxhX7Ecx1+L8V7TB5zOSIcjctEz4+IBMA4ciHAkIiIiIiIiIiIiIumU+BM5T3jGjiFUoRLBJk0jHYqIkL7VJ4Dt0MEIRyIiIiIiIiIiIiKSTok/kdxgWRjJSdh27QTTzPXh7WvXYF+3Bl+37jpLTOQcYRUoCDa7En8iIiIiIiIiIiJyztAZfyJnyPnbTDxfjMJITQXAio4mVLU6lt2Obd9eMM3013XrQvtWpzWHe+KPmMVKEKzfMBcjF5EzYhiY8fHa6lNERERERERERETOGUr8iZwJy8I97ltCFSrib9sRKyYGx/q12FetxLAZhMpXwDBNHH8txj5lEqQegZbtT2kK266dOBb/Sdqtd6jaT+QcY8XFq+JPREREREREREREzhlK/ImcAfuqldj27yPtrv8jlFgVgFCt2tA9c9/oz0bg+uwzjMSaEFcYx8L5OP9aTNpNt4HLlfUEwSDun37AypefQIvTqxYUkbPHjIvHOKjEn4iIiIiIiIiIiJwblPgTORWWhbF/P1ZCAgCu2bMwixQlVCXxpLf6r+1DzPK/cQ//EKN+QzyfjQTLgjQvaf/3AHi9RH32CfZ16wAw/D6MQwfBsvBec332yUERiRgrPh771i2RDkNEREREREREREQEUOJPJGuWleW2mu5vv8b94/ek3XE3gcZNcc6fh++yK3K2BWd0NNxzD/annsazbCn+Sy4jWKUq0e++Af/7EPuaNRiHDxFo2x7Lbge7HbNwAmbRYoSq1zgLixSRM2XGF0rf6jObZ4aIiIiIiIiIiIhIXlLiT+Q/nDOn4/n6C3xXX4O/Q+fwD/Mdixbi/vF7zBIliRoxHPu6teDz4m/ZJueDN2yI/+rehKJj8HfsAoaB9/q+eL78FLNUaVJeGIxZvMRZWpmI5DYzvhD4vJCaCjExkQ5HRERERERERERELnJK/In8i23nDqI+/QQzIQHPqBE4584h0Kw5Vr78eD4ZTrB+Q1Lve4jo1wbjmjGVUNXqWEWKnNIcgZ69CAbN8Gv/JZcSKleeUPkK4PHk9pJE5Cyy4uMBsB08gKnEn4iIiIiIiIiIiESYEn8ixwSDRL3/DmahwiQ/Pxj7xg14Rn+G54vPIBTELFaC1P73gMNB6v89RPQH7+Lv1OXM5zUMQtWqn/k4IpLnzLh/En+HDmKWLhPhaERERERERERERORid04m/hYuXMiIESNYvnw5+/bt47333qNjx47h648//jjff/99hntatmzJiBEjANi+fTvvv/8+8+bNY//+/RQpUoQrr7ySO++8E5fLladrudjZV68i+q3XCCVWxd+mHUZyMq6Z0zGSk0h++VVwnBtvQdvWLbjHj8O+dSvJz74IHg+h6jVIeXEImCbGoUNY+fLBsfdPTAypjzwe2aBFJOKsuDgwDIyDByMdioiIiIiIiIiIiMi5mfhLTU0lMTGRnj17cu+992bZp1WrVgwePDj8+t8JvY0bN2JZFs8//zxly5Zl7dq1DBo0iLS0NAYMGHDW45d0tl07iX7rVcyEohj79hL9xlAAQlWrY9u5A+e8uQRats7TmIyjR3As/RvHyuXYduwAy8JIS8O2awdWvvyk3XYHZoWK/1mIDatQoTyNU0TOEw4HVr782A4eiHQkIiIiIiIiIiIiIudm4q9Nmza0adPmhH1cLhcJCQlZXmvdujWtWx9PKJUuXZpNmzbx1VdfKfGXR4wjh4l+dTBWvgKkDHgSYmKwbduKFRWNlZBA9Csv4pr8C4EWrcAwzn5AloVr2q+4vx6N4U3DLF2GUPkKWHY72OwEr72eYJ1650wFooicP8xChTCU+BMREREREREREZFzwHmb5ViwYAHNmjUjf/78NG3alAceeIC4uLhs+yclJVGgQIFTmsNmM7DZ8iApdSFJTcX5y0RcEydgOZ2kvfAyjoL5069VKB/uFrr0MjyvvoJr03rMsuXwvP0G9uVL/zOYQahGTQJt22MVLox95QqMw4fx97gaYmJOHktyMo4/5mLbuwf7qpXYNqwn2KEj/l7XYBUomKn72f7LYLfbMvxXRC4MRqFCuJb+hf29t7AKFMR//Q3HtwXOY3rOiEhe0LNGRPKCnjUikhf0rBGRvKBnjeQ1w7IsK9JBnEhiYmKmM/4mTpyIx+OhVKlSbNu2jTfeeIPo6GjGjBmD3W7PNMaWLVvo0aMHAwYMoHfv3jme27IsjLyoRruQPPssLF0Kl14KV18NBQtm3c+yoH9/KFcOvF5YuRKuuw7c7uN9fD6YOxfWrk1/7XKBzQZly8ILL0BUVPZxWBY88wz8/TcUKQIlSkCvXlCzZi4tVETkH3Pnwi+/pP9+2TK46Sbo3j2yMYmIiIiIiIiIiMhF6bxM/P3Xtm3b6NixI6NGjaJZs2YZru3Zs4cbbriBxo0b89JLL53S3AcOJKvi7xQZu3eD24UVF3/Svs5JP+P6dCQ4nXgHPEGoRtZJOWP7NoyUFMyKlbBt2UzUS89jli1H2oAnwOPJ8h77/Hl43nod76OPE6rf4IzWlFvsdhv580dx9GgaoZAZ6XBE5Cxw/+8jHPPnkfL2exAdnefz6zkjInlBzxoRyQt61ohIXtCzRkTygp41klvi4nKwEyLn8Vaf/1a6dGni4uLYsmVLhsTfnj176Nu3L/Xq1eOFF1445XFN08I0z+m86LmncJH0/wZP/gALtmiD8ddf+Lt0JZhYPft7ipU8/vuyFQg9+gQxr7yIZ8AjpN16R+aEodeL57NRBOrUw1e7Xo5iyUuhkEnwHItJRHJH6Ioe5Js5E/vEn/B1vzpyceg5IyJ5QM8aEckLetaISF7Qs0ZE8oKeNZJXLohNZXfv3s3hw4dJSEgItx1L+tWoUYPBgwdjs10QS72wREWR+sjjBGvVOaXbQpWrkPziK1hx8cQMfp6oYW9jX7USLAvj4AE8X36G7cgR0m685SwFLiKSNatQIfwdO+P6+SeM5KRIhyMiIiIiIiIiIiIXmXOy4i8lJYWtW7eGX2/fvp1Vq1ZRoEABChQowLBhw+jSpQuFCxdm27ZtvPrqq5QtW5ZWrVoB6Um/G2+8kRIlSjBgwAAOHjwYHuvfyUE5f5nFS5Dy5DM4Z0zD/dMPxMybgxUTg5GSAoD32huwihaNcJQicjHyXXkVrhnTcE3+BV/PnJ8rKyIiIiIiIiIiInKmzsnE3/Lly+nbt2/49eDBgwHo3r07zz77LGvXrmX8+PEkJSVRpEgRWrRowf3334/L5QJgzpw5bNmyhS1bttC6desMY69ZsybvFiJnl2EQaN+RQLsO2FetxLF8KaEy5QhVr46Vv0CkoxORi5SVvwD+Fq1wzZiGr1sPcJyT/9SKiIiIiIiIiIjIBciwLEuH2GVj3z5t0ya5x+GwERcXw6FDKdrLWeQCZ9uymdgnHyP1vocJNm6SZ/PqOSMieUHPGhHJC3rWiEhe0LNGRPKCnjWSWxIS8uWonw6+ExERyWVm2XKEKlXBNf3XSIciIiIiIiIiIiIiFxEl/kRERM4Cf8fOOJYvw7Z7V6RDERERERERERERkYuEEn8iIiJnQaBxU6zYWFy/TgLtqi0iIiIiIiIiIiJ5QIk/ERGRs8Hlwt/pEly//kLMy89jX7sm0hGJiIiIiIiIiIjIBU6JPxERkbPE16MXqQ89BinJxDw/CPvyZZEOSURERERERERERC5gSvyJiIicLYZBsH5DUl4aSqhyIlFffgqmGemo5BwS9fEHuKb9Gukw5F+cc2cT89QA7CuWRzoUEREREREREZFTpsSfiIjI2WYYePv0xbZtK87Zv0U6GjmHOJb+jXPmjEiHIcf4/XhGf45tzx5iBj+P538fgtcbmVhSUnQ+qIiIiIiIiIicMkekAxAREbkYhCpVJtCkOZ5vviLQpBm43ZEOSSLNsjCSkrAfPoRx9AhW/gKRjuii55oyGePoUZJffRP7imVEffk59i1bSH308bz7+lgWnk8+xjVjKrjchEqUIO3eBzCLFc+b+UVERERERETkvKaKPxERkTziveZ6jKQkXFO1taMAPh8EA2BZOHT+Y0QYhw8R8/QT6dutpqbinjAef5t2mEWLEWjfieRBz2E7eICY5wZh27M7T2JyTRiPa8ZUfD174736GmwHD+KaOCFP5hYRERERERGR858SfyIiInnEKlKEYLXqONasinQocg4wjh795zcGjqV/RTSWi5Vj8Z/YN23AM/J/5Hv0AQyvF99VPcPXzXLlSX7mRcAg5tmnsG3aeFbjcc7+Dc83X+HrfjW+7lfjv/Ry/B0745o7G1JTT2tM48ABbNu25vyGUEhbjIqIiIiIiIicx5T4ExERyUNmmbKn9kN4uWDZktMTf8EaNXEsW6pkSwQ4li0lVKkKKQOfxoqJwXfZFViFCmXoYxUpQsozz2MWTiD2xWexL1ua63EYyUlEfTCMqA+HEWjVBl+PXuFr/rbtIeDHNef0zgf1fDGKmCEvgWmevHMoRMygx8l3/924v/0aY//+05pTRERERERERCJHiT8REZE8FCpTFtu+vaddvSMXDiMpCYBAi9YYRw5j27olwhFdZIJBHMuXEaxdh1CNmiQPfRNfr2uz7GrlL0DKk88QTKxKzKuDcf0yMdcStbZNG4l99EEcS/4k7fa7SLvjbjCM43PHFyJYv2H6FsGnOuc/azQOH8K+auVJuztnTce+bSvBajVw/TqJ2GefzFnCUERERERERETOGUr8iYiI5KFQmbIA2Ldvi3AkEmnhxF+DRuBy41j6d4QjurjYN6zHSEslWLtOzm7weEh96DH8l1yK58tPiXr3LfB6zygG25bNxAx5ETOhCMlD3yTQpl2GpN8xvg6dse3Yjn3tmlMa/9gacblxzf39xJ1TU/F8O4ZAi1ak3XUvqQ8+inH4kCqURURERERERM4zSvyJiIjkIbNESbDZsW/dHOlQJMKMo0fB7YHo6PSzH5cp8ZeXHEv/woqNJVS+4inc5MB7/Y2k3vcwzr8W4xn9eeY+poln1AgcixaecCjb5k3EvPIiZuEEUgY8iVUwLtu+oZq1MIsWxzN2DASDOQ/3nzX6unTFsXA+BALZ9nX/9AOG14u313Xpc1aqDHaHziQVEREREREROc8o8SciIpKXHA7MkiWxbdG2jhc7I+koZr58AAQaNMSxagW2PbvzNgjLwrZr5xlXrp2PHEv/JlijNthO/dvhYOMmeK+/Adf0KdhXrshwzTVjKq6pk4l+6zWc06dkvjkQwD12DLFPP4EZH0/q409BTMyJJzQM0m67A/vaNUSN/DjHW346lv5NsGYdAi1bY6Sm4vh7Seah9+/H/f1Y3L9MxNf1suNnHLpchMpXwL7m1KoMRURERERERCSyHJEOQERE5GITKlMOu7bPu+gZyUlY+fIDEGjZBs/Yb3BNGI+33515Mrfny89wLP0b48hhAo2bknbfQ2d93nOFkXQU++aN+Dt2Pu0x/B0645w7h6gRH5H88qvgdmMkHcX9zVcEWrXBioom6pOPsW/cQLBRE8xixXHOm4tz5nRsBw/iu/IqfN16gNOZo/lC1WuQ1q8/UR+9R6hoMfxXds/ZGjt1wSxZilDZcjjnzibYsDEEAjgXLcQ5czqOFcvA5cbfsjW+/4wZTKyKa87v6YnGLLYgFREREREREZFzjxJ/IiIieSxUugzOPxfoh+kXOdvRo1j/VPzhcuG77Eo833yF76qrsQoXPnsTBwJEv/U6tu1b8bftAKRv8+jbtBGzfAWwLBwLFxAqXwErIeHM5goGsa9aSahmrXPqve5Yshgsi2Ct2qc/iGGQdvudxA58lOj338HbrQeuGVPBsvBedwNWvvyYhRNw//ITrpnT0+9xugg0aUrqZVdili5zylMGWrXBtncPnm++wixdhmC9Btn2dSxflmGNgeat8HzzFfaH78O2fz+EgoQqJ5J2W38CTZuDx5NpjFCVRIyJP2Ls24dVpMgpxysiIiIiIiIieU+JPxERkTxmlikDPi+2vXswixaLdDgSIUZSEmbC8WSKv0Mn3BO+xz3xR7w33Xp2JrUsov73Efb160h54mlCVRIhFML550I8335N6mNP4P7mK9wTxoNhEKxRE1+3noSqVT+t6VyTf8Hz1eek3XkvgZatc3ctp8rrxb5zO66fJ+KcP5dg9ZpY8YXOaEizeAnS+vXH8/WXxD49MH2avrdg5S8AgP/Sy/F3vQzb7l3Ydu4gWLX6ybf1PAlfj17Yt2wm6oN3SX5hCFZsLJ5vvkqf+/obwe0G0s/3M0uXwYqLByDQug327VvTE5JFihCsXjP9zNETCCVWTR9r7WoCSvyJiIiIiIiInBeU+BMREcljoX8qfWxbtyjxdxEzkpKwKlQ83uDx4O96Oe7vv8PXrTtWwbgznsO2aydmseLhajvXhPE45/xG2r0PpCf9AOx2fFf3JmrYW3hG/g/XtF/x9boWs2AcrqmTiXnlRdL6302gectTmzw1FfeE78HhxPPNVwQaNwWX64zXdKpsO7YT/epgbPv3AWDFxZN2Sz8CrdvlyviBlq0JNGuBY+lf2Lduwd/hP9uHGgZm8RKYxUvkynwYBqn97yH26YHEvPYKRloqeL0YoRCOtatJu+V27GtW4fhzIYF2HcK3Wfnyk9b/nlOayorNh1miJPY1qyOfuBURERERERGRHLFFOgAREZGLjVUwDis2H/atWyIdikSQkXQUM3/+DG2+jl3ADOFY/OcZj+/4azGxjz6A65eJANg3rMMzdgy+K7unb+34L4EmzTBLl8E17Vf8HTqn92nTjpRnXiTQvAVR778THien3JN/xvD6SHnsCYzDh3FNOrX7c4v7u28ASLvzXlIGPU/S6+8QaN8JHLn4+Te7nWC9Buln9tntuTdudmJiSL3/YWwHDxAqX4HkIW+Q/NxL4A8Q8/wgPOPGEqzfEN/lV57xVMHEajjWrMqFoEVEREREREQkL6jiT0REJK8ZBqGyZbFv2xrpSCRSTBMjJRkrNl/G9pgYQuUr4li5Mj05dQYcSxaDYeD56nOs/Plxfz+WULkK+Hr0ytzZMEjr1x/HwgX4el17/Dw+h4O0O+7GzF8Az5efEipTllCNmied20hOwvXzT/g7diZUvQb+Tl1w/zieQNv24W0w84Jtx3acC+eTdusdF1zFmlmmLEc/HAFOJwBWoUIkvzAYx+qVBBOrnfGWoseEEqvimjEVI+koVr78J79BRERERERERCJKFX8iIiIRYJYui00VfxctIyUZLAsrX75M14LVquNYvRIsK+cDWhbRrw/BvmxpuMmx7G/87TsRaNSUqA+HYTt8mLS7/y/bSrdQxcr4ru2TuWLNMPBd24dQ1epEfTIcfL6ThuOa/AtGKITvim4A+Lr3BJuB+9sxOV9TLnD/OB4rLp5AqzZ5Om+e+SfpFxYdTbB+w1xL+kF6xR/8k0gWERERERERkXOeEn8iIiIRECpREtu+vRAIRDoUiQAjKQkgy+q3ULXqGIcPYdu9K8fj2deuwbFkEe6fxgNg27Mb2949BGvXIe3Oewg0a0nq7Xeln/d3WgEbpN12B7aDB/H8s3XmiThWriBQtz5WgYJA+llxvp7X4Jo5DfvG9acXwymy7dmNc+7v6dtd5ua2nhcZKyGBYN36uH/64dSS0f9iHDqIfcVy8HpzOToRERERERER+S8l/kRERCLALFoMLAvb/n2RDkXOhlAI57y5kJKS5WXj6FGArCv+EquBzYZ91Yr0BsvCvmwpUcPeJv8tN+CYPy/TPc55cwFwrFiOsXcvjqV/gc1OsHpNcLlIu+c+gk2bndGSzOIl8PboheuXn7Bt3JB9R8vCvnkTofLlMzT7O3bGLFUaz6hPTjuB9F/O6VNwTfo584VAAM/Ij7HyF8DftkOuzHUx813VE9vOHTgWzM98MSXlhF9P+8b1xD7xGDGDnyd//1uJfuUFjKNHzmK0IiIiIiIiIhc3Jf5EREQi4Fjl1alUdcn5w7HoT6KGvUW+h+7FNWE8pKZmuG4kZZ/4w+MJn/MH4PrpB2KGvIh9y2bMYsXwfDcmY6LFNHEumIe/XUesqGhcs6bjWPo3oSqJEBWVq+vyX3o5ZvESeL4ZHW6zb1hH9NCXwe8HwLZrJ/i8hMpVyHiz3U7azf2wb1yPc+b0M47FvmY1USP/h+eLURmTocEg0e++iWP1alLvvBdcrjOe62IXqlSZYM1auH/47vh7z+/HNeYr8t/VLz2Zt2dPpvscy/4m5qXnMYsUJeXZl/D2uRH75s1EffxhriV/RURERERERCQjJf5EREQiwIqPB4cTWxY/LJfzn33jeqwCBQk0a4ln7Dfkv7c/UR+9Fz7X0UhKAsPAionN8v5gteo4Vq3A2LcPz7ix+LtcSvLQN0i7rX+myiv76lUYRw4TaNOOQNPmuH6bmb7VZp26Z2FhdrxXX4tj+TLsq1aC30/UB+/hWPoX9rVr0rts2giA+Z+KP4BQYlUCLVsT9cWn2NevO/04UlKI+uBdQpWqEGjcjOjh72PbuQPbxg1Ev/Uajr//IvWBhwnVqn36c0gGvm49sW/dgnvMaFxfj4b77sP50w/4O3XBtmcP+R5/GOdvM8P9jQMHiH7jVYJVq5EycBChSpXxd+5K2h134ViyCOeMqZFbjIiIiIiIiMgFTIk/ERGRSDAMzCJFVPF3gbJv3ECwSiLem28j6Y138XXrjn3VSmJeHQyWhZGclJ70s2X9rVioeg2MI4eJfucNrJgYvFdfA4aRZeWVc95czEKFCVWsRKBde4xDB8HnJVirzllZW7BRY0Jly+H59mvc34/Ftm8vVnQ0juVL09e+aSNmQhGs2CyqGYG0m/sRKlOW6KEvYfsnSZgjloWxZw/2ZUuJHv4+RnIyqXf9H2l33IVZqBCxTw4g9umB2DdvIvX+hwjWrZ8by5V/hKpVJ1ijJu6JP+KY/TuULEnq4Nfw3ngzya+8TqBxU6JGDMe2YzsAnm+/wvJ4SL33AfB4wuME6zfE364jUZ9/ml4dKiIiIiIiIiK5yhHpAERERC5WZrHi2PbsjnQYkttME/vGDfi6dQfAKlQIX7cehCpUJHrIS+mVaUePYuXLn+0QwSpVwWbHvmkDaXffl2HLTl+3nsS89CzOP+YQaNgY58L5BFq1SU8Mlq+IWboMxuHDmGXLnZ31GQa+XtcS/dor2NetwdejF7Zdu3AsX4qPPv+c71ch+/s9HlIeHUjMkJeIGfIiyS8OxSpcOPvpkpNwzpiOa9YMbLv/SRTZHaTdeQ9WkSIApD74KK6fJxCs35Bg7bpgt+figuWY1AFPgWni8Lhwx8VgHUqBoAkeD2m33YF9w3qiPv4Qb9+bcc75He/Nt2W53ay3T18cS//C/dMPpN1+VwRWIiIiIiIiInLhUuJPREQkQsxixXEsWhjpMCSX2XbtxPCmEapQKUN7sHIi2B04VizDSErCyp994g+Ph1BiVSzDINCsRYZLoWrVCVavSdT773AspRJo2iz9N4ZB2i23Yxw5DIaRe4v6j2CdeoSqVoe0VHxXXIVz7myi/piNcfQIts2bCPyT9MxWdDQpjw4k3yP34Z4wHu8t/bLv+vYb2NetJdCoCd4+NxIqUQqrUCFwHP821ixeAu9t/XNreZIdmy3bKlVcLtJuv5OYF54meujLmMVL4G/bIeu+Hk94W1pMM/sxRUREREREROSUKfEnIiISIWbRotj27YVgMEMSQ85v9g3r06vvyv3njDuPh1ClyjhWLIdAACtf1lthHpPy4KPplWtZJPBSHx6Afd3a9PePZREqXzF8LVQlMVfWcUKGQcpjT6T/3uEgWLMWWBau6VPTk57lTlDxd0xsLP6ul+MeNxbfVT2w4uIzT5N0FPvqlaTd1p9A2/a5vAjJbaHEqvg7dsE1dTJp/e85YeVlsEEj3BN/xL5+Xd68Z0VEREREREQuEvp4rYiISISEihQD08R2YH+kQ5FcZN+wHrN4CYiJyXQtWKMm9lUrMI4ewTxJ4o/oaHC7s77mdhOqWYtAuw4E2nc8q9V92XK50n8BVnwhzBIlcU36GQCzfPkT3Rnm69gFy+3CPXFCltcdy5aCZRGsUzdXQpazz3v9jaQMfPqkZyyGKlXGypdfVc8iIiIiIiIiuUyJPxERkQgxixUHwLZ7V4QjyQVeL8bRI5GO4pxg37iBUMVKWV4LVq+JkZqKfcvmE57xdz4K1qyNkZyEWTgBK/YkSc1jYmLwd+6Ka9qULN8/jr+WECpbLstqQDlHuVyEatQ8eTLaZiPQoCHOPxeCZeVNbCIiIiIiIiIXASX+REREIsQqVAjsDmy7dwMQ9eEw3OO/i3BUpyf67deJHfAwxp49kQ4lsvx+7Fu3ZJv4C1WqDC43WNYFmPirBUCofA62+fwX/yWXgs2GZ/TnGRNApolj6RKCderlZphyDgk2aIRtzy5sO3dEOhQRERERERGRC4YSfyIiIpFis2EWKYptz25se3bjnP0brmlTzonqF+PQQRzz54Fphtvs69Zi37g+U1/7+nU4lv0NoSAxrw7GSE7Ky1DPKfatWyAUJFShYtYdHA6CiVUBTnrG3/kmWLU62B2EKmSd9MyOFZuPtFv64ZzzO55PPwm//+0bN2AkJ590y0g5fwVr1AK35+TbfZomjgXzwefLm8BEREREREREzmOOSAcgIiJyMTOLpif+XNOmgGFgHDqIfdOGU06e5Cb7iuVED3sLI+kooYqV8fbpi/O3GbhmTge7g7S77iXQtHm4v3v8d5jFS5L60KPEPPcU0W+9TsrAQWC3R2wNkWLfsD49+VWmXLZ9gtVr4lj29wWX+CM6muTnXgpvYXsqAi1bg99P1CfDwWbDe/2NOP5ajBUTk231pFwAXC4Ctevg/nUShs9HsHpNQpWrhM+OBMDvJ/r9d3D8uQB/h854b+kXuXhFREREREREzgNK/ImIiESQWaw4jj8XYN+wDn+nS3DO+Q3HnwsjlvhzTp9C1Mj/EaxeA/8ll+EZ/QUxzw/C8kThvfk27OvWEfXe2xgHDuDv0hXb9m04/lpM2p33YhYvQer/PUTM4OdxLPv7oqzUsq9bS6hceXBk/y1WsE5d+PYrzCJF8y6wPGKWK3/a9wbad8QwQ3g+G4lj5XIIBAjWqntRJpAvJr7e18G3X+OaNgX3D+PA4SRYJRGzXHnMhASc8/7AvnEDgRatcU37lUCzFoSqVot02CIiIiIiIiLnLCX+REREIsgsWhTb/n0A+DtfgpGSgnPxn+k/DD9FxqGD8NWn0PM6sJ3GP/GhEJ5vviLQvBVp/e8Gm43kmrVxzp1NsGbt9DMJO3TGLFgQz1ef4/7pB6x8+TCLFiPQrEX6ENVrYJYoiXPunIsv8WdZOFatwN+qzQm7mWXKcvT9/0FsbB4Fdv7wd+xCsFIVov73Ifbt2/B1vzrSIclZZhYvQdp9D4FlYdu2FceK5ThWrcCxaCG2/fuxoqJIGTiIUKXK2PbuIerjD0ke/GrGqkARERERERERCVPiT0REJIKObYsYrFkLs1hxAg0a4ZzzG7Y9uzGLFsv+Rssi6qP38LfrSOifM+OcP02AKb9gr1WfYNUaJ588EMDwpmHlyw+AfdVKjORk/F0uAds/xwA7nQTatDt+j2Hgu+4GAi1a4Zo1A+f8P/D26Xu8KsswCLRohfvH8aR5veDxnPKfyfnKtnMHxpHDhGrUPHlnJf2yZZYrT8pzL+NYuTz9DDi5OBgGZpmy+MuUxd/1svQ200z/9U8FbVq//sQ+8RjuCePx9ewdwWBFREREREREzl22SAcgIiJyMQuVKAU2G/5OlwAQrF0HnC4ci/484X3GkcM4Z/+G57NPwLLA68U5czoAtjWrTzxpMIhz+hTyPXwfsY8+ACkpADgXzscsnECofMWTxm2WKYv3xptJGvZRuNrvGH/TFuDz4lyy6KTjXEgcK5aB3UGwStVIh3L+s9sJ1qpzPAEtFyebLcO2uWbJUvjbtMP5+6z0556IiIiIiIiIZKKfpoiIiESQVagQSe98QLBBo/QGj4dgjZo4F8xLr3TJhm37dgDsWzbjWDAf1+xZ4PVC+fLY16454ZzRrw1OP8evUhWMNC+uab+CZeH8cwHBho3BMM5sTUWLEqpUBeec389onPONY8VyQpWrgNsd6VBELljBRo2x7d+HbeuWSIciIiIiIiIick5S4k9ERCTCrIJxGV77W7XFvn4tsQMfwbFgfpaVLfbt28DhJFizFp7vxuCa9AvBRo2hZUvs69ZmmzQ09uzBsXwZabffRdp9D+Jv2x73zz/hWPY3xpHDBBo3zZU1BZq3wLH0b4yko7ky3jnPNLGvWkGweg62WBWR0xasVgMrKhrn4hNXRYuIiIiIiIhcrJT4ExEROccEmzQl5dmXMOPiiX7ndRx/Lc7Ux7ZjG6GSJfH1vg7bzh3Ydu8k0KUrVK0KaWnYtm/LcmznnwvA4Qwn+HyXd8NITSVq+AdYBePSK9ZyQaBpc8BKr1y8CNg2b8JITdWZdCJnm8NBsE49HH8uiHQkIiIiIiIiIuckJf5ERETOQaFKlUl9/CmsgnHpFXz/Yd++HbNkaUIVKhFo3IxQhUqYVatBlSpgs+FYl/V2n84F89LPEfR4ALASEgi0bIVx+BCBBo3OeJvPY6z8BQjWrI1zzuxcGe9c5Jo6mdhHHsC+bCmOFcvB5SZUsVKkwxK54AUbNsK+ZTPGvn2RDkVERERERETknKPEn4iIyDksVKp0+rae/2ZZ6RV/pUoBkHb3/5Hy1LPpSTuPB7NsOexrMycLjQMHsG9YR6BRkwztvm49sKKjCbRqk6uxB5q3xL529YX3w3nLwv3t13hGjQDLJGboS7h/+YlgYlVwOCIdncgFL1C7Ltgd2u5TREREREREJAtK/ImIiJzDzNJlsO3YnqHNOHgQIzUVs2R64g+HA1yu8PVQlUTsWVT8ORctAJudQL0GGecoWoykj0YSqlQ5V2MPNGgEThfOeXNyddxIc3/3De4fxuG9pg/Jr76F76qeGElHCdauG+nQRC4O0dEEq9fAsWhhpCMREREREREROeco8SciInIOC5UqjW3vHvB6w232Hdv+uVYmy3vMxERse/dgHD6Uod25cAHBGjUhNjbzTbm0xWcGUVEE6jfENfcC2u7TNHFNm4K/c1f8V3QDmw1fz94kvfYO/s6XRDo6kYtGoFETHKtWYN+4PtKhiIiIiIiIiJxTlPgTERE5h5mlS4NlYd95vOrPtn07uNxYRYpkeU+oSiJAhu0+jaNHsK9emWmbz7Mt0KIltm1bsW3dkqfzni329eswko4SaNo8Q7tVtCjY7RGKSuTiE2jdllC5CkS9PyzDByNERERERERELnZK/ImIiJzDQiVKgWFg23b8nD/79q2ESpbMtkrPKlQYM6EIjhXLwm2OJYsBCDZoeHYD/o9g7bpYsbE45/yep/MCYJp4PvkYx99Lcm1Ix6KFWPny5/q2qCJyihwO0u7+P2wHD+D58rNIRyMiIiIiIiJyzlDiT0RE5Fzm8WAWKYp9+/HEn237dsxSpU94W7BeA5yL/wTLAsDx12JCFSphFSh4NqPNzOEg0LwV7ok/EvvQ/+H55GPw+fJkateUybimTyFqxPDcmdOycP65kGD9BmDTt1AikWYWL0HaDX1xzZiKfcXySIcjIiIiIiIick44J39qtXDhQu68805atmxJYmIiU6dOzXD98ccfJzExMcOv2267LUOfw4cP8/DDD1O/fn0aNmzIE088QUpKSl4uQ0REJFeYJUth2/bPVpmWhX3HdkIlT5z4CzRohHHoIPZNGyAQwLn07/SEVQR4r7+R1AceIVStOq7pU7Bv3HDW5zT27cPzzVcE6zfEOHIE96SJZzymbecObHt2EWjYOBciFJHcEGjXEbNESVyzZkQ6FBEREREREZFzwjmZ+EtNTSUxMZFnnnkm2z6tWrVi9uzZ4V9vvPFGhuuPPPII69evZ+TIkXz44Yf8+eefPP3002c7dBERkVwXKl0G+/b0M/6M/fvB58UsVerE91SthhUTg2PRnzhWrwSfl0C9yCT+cDgINmxMWp+bALAdPnR257Msoj4ZjhUTQ+qd9+Lv1AX3j+Mxjhw+o2EdixaC20OwRq3ciVNEzpxhEGjWAueiheD3RzoaERERERERkYg7JxN/bdq04cEHH6RTp07Z9nG5XCQkJIR/FShQIHxtw4YN/P7777z44ovUqVOHhg0b8tRTTzFx4kT27NmTF0sQERHJNWbpMhiHD2EkJ+HYsA7gpBV/2O0E6zbAuWghjsWLMAsVxixdJg+iPYGoKHB7MA6dpcRfSgquCT8Q++iDOJb9Tdqtt0N0NL6remDZbbjHjT2j4Z2L/iRQuw64XLkUsIjkhkCTZuDz5up5niIiIiIiIiLnq3My8ZcTCxYsoFmzZnTp0oVnnnmGQ//6IeKSJUvInz8/tWod/0R+8+bNsdlsLF26NBLhioiInLbQP+f52VevwvPlZwRr1MQqXPik9wUaNMK2fRvOub8TrFsfDONsh3pihoEZF3/WKv6i330Dz3ffECpfgZQnn01fM2DF5sPXrSeuGdOw7dl9WmMbyUnYN6wjGKmqSRHJllmiJGbpMjjn/RHpUEREREREREQizhHpAE5Hq1at6NSpE6VKlWLbtm288cYb3H777YwZMwa73c7+/fuJj4/PcI/D4aBAgQLs27cvx/PYbAY2W4R/SCoXDLvdluG/IiI5VqokhtNBzIiPwLLw3n0vDqc9U7dMz5n69TBcLozUVKxGjXA4zoHnT6F47IcPnXIs9sWLCNWoCW53ltdtK5fjXLEc74OPEGrcBIOM3+SYXbvC5IlEjf8O3z3/l/HedWtxLF6E/5rrsp9/+1YMw4DExHPjz1Ekgs7F72lCzVvgGj+OQCiQ7XNCRM4v5+Kz5nxlX7YUs2RJrPhCObvB79cOB3LR0LNGRPKCnjWS187LxN9ll10W/n1iYiKJiYl07NgxXAWYW+LjY9J/yCeSi/Lnj4p0CCJyPipXFrZsgQEDcFUqe8Kux58zMdCoASxbhqtF43PjBzglisKBA0THxeT8nr174a1X4cYboXfvzNctC374DqpXxdW5XTaVjTFwYx/48EOib+oDpf+1VepfC2HiBGJ694D/fHAobP8uyBeDq3olsOkbdRE4x76n6doJvv8W1/qV0LJlpKMRkVx0Tj1rzkf79sGrL0N0NNx8M1xySfa7QASD8NlnMGECDB0KlSvnaagikaRnjYjkBT1rJK/kauJv165d7Nq1i6pVqxIdHZ2bQ59Q6dKliYuLY8uWLTRr1ozChQtz8ODBDH2CwSBHjhwhISEhx+MePJiiij/JNXa7jfz5ozh6NI1QyIx0OCJynnE2bIqRWAN/jXpwKCXLPlk9Z2xX9sRo1JxQSgBSAnkZcpZc7hgcO1eQms0asuL4YyHuQAjrl8mkdrw00w+r7EsW41m6HO/jTxI6nJr9QI1aED16DObHn+B98JFws2fNOuyBEL7f5hJs0y7LW91LV2IrXoq0I2k5jlvkQnVOfk/jyU9UyTKYU6bjq1Ev0tGISC44J5815yHnpKm4MAjWa4jj7XcJzf4D70OPZvogk3HoIJ533sK2bi1ERREc/Q2++x6ITNAieUjPGhHJC3rWSG6Jy+EH6XMl8TdmzBiGDRvG/v37ARg7diw1atTgnnvuoXHjxtx00025MU22du/ezeHDh8NJvXr16nH06FGWL19OzZo1AZg3bx6maVK7du0cj2uaFqZpnZWY5eIVCpkEg3rAi8ipCV7W7Z/fnPz5keE5U7JM+q9z5LljKxCH4+AhgoFQjs8cdK5YgeVwws6dWGvWEqpUGduunbi/HYPh92HfuoVg5UR81WudZJ020rpfTdTw9zG3bccsXgIAY9t2LMvCWPIXwRZtsrzTs3Ejgdp19PwW+Zdz7Xsaf/2GuCZOIOj1g+O83NhERLJwrj1rzimhUPqvE+zq4J47l0CtuqTedieOug2Ifus17N9+g6/n8V0UbDt3ED3kJQiFSH7iGewbN+AZ/Tmha/vkfHtQkfOcnjUikhf0rJG8csZ7VY0aNYoXXniBq666ihEjRmBZxxNljRs3ZtKkSac8ZkpKCqtWrWLVqlUAbN++nVWrVrFz505SUlIYMmQIf/31F9u3b+ePP/7g7rvvpmzZsrRq1QqAihUr0qpVKwYNGsTSpUtZtGgRL7zwApdddhlFixY90yWLiIjIaTLj4sHvg9QTVOb9h331avyt2mDFF8L520wwTaI+fA/HujVgsxGsVJm0W2/PUSIx0KgJGAb2tWsAMJKTMI4cxixaHMfyv8HM4hvwtDRse3YRKlc+xzGLSN4L1KmH4U0L//0+Gc/oz3EsWXSWoxIRyX3u774h9oF7yH9LH/Lddxd4vVn2M/buxb5xPYGmzQEINmiEr2dv3OO/w/H3EvD7sS9fRszzg8DjIfm5lwlVScTfqg04nbimTcnLZYmIiIhILjnjj8J+8cUX3H333dx9992EQqEM18qXL8+mTZtOeczly5fTt2/f8OvBgwcD0L17d5599lnWrl3L+PHjSUpKokiRIrRo0YL7778f178+5fbaa6/xwgsvcNNNN2Gz2ejcuTNPPfXUaa5SREREcoMVFweA7fAhzJiTb09gHDqIbc8ugr2uxYqOxjV9CmZCAvaN60kZ9DyhKomnFkBUFGbxEtg3biDQph22HTsA8He9FM+oEdg3byRUoVKGW+xbt4BlESpb7tTmEpE8ZZavgJW/AI6lfxGqXuPEnYNBXJN/wbF4Ecl16+e4AllEJNJsWzbj/n4sgRat8VeoiOfLT3H9PhN/p0sy9XXO/wOcLgL1GoTbfN16YF+/jujXh4Q/8BSqUpWUhx6D2Nj0TjEx+Nu0wzV9Kr5uPc6Nc6JFREREJMfOOPG3Z88e6tXL+hwNp9NJ6il8ov+YJk2asGZN9p/UHTFixEnHKFiwIK+//vopzy0iIiJnj1kwPfFnHDwIJUudtL9jzWoAQomJmGXK4P7pBzxjRuPv3PXUk37/CFWoiH3jBgBsO7aBzYa/ZRvcX4/GsfTvzIm/zZvA7sDMQbwiEkGGQbBOXZx/LcZ3bZ8TdrXt2gmhILbdO3Es/pNgg0Z5FKSIyJnxjB2DWbQYabffCQ4H9jWrcU2ehL9jl0wfYnDOn0ugXn3weI43Ggapd/0frt9mYsXEYCYUIVS5SqYtkv2duuD69Recc2cTaNs+L5YmIiIiIrnkjLf6LFGiBMuWLcvy2t9//025cuXOdAoRERG5QPy74i8n7KtWYhYtjhUXj1miJKGKlTELJ+Dtfd1pxxCqUDG9ii8YxL59O2aRYuDxEKpeA8fSvzPHsHkjoTJldWaYyHkgUKc+tu3bMP45ezw79m1bAQiVKYv7px+PX0hLO5vhiYicEfv6dTiWLEo/n++f70v8l1ya/iGGpX9l6GvbuQP75k0EmjTPPFBMDP6ulxFo3ZZQtepZfo9jFi9BsH5D3BPGQzB4FlZDtluUioiIiMiZOePEX+/evfnggw/49ttvSU5OBiAYDDJz5kxGjBjBNddcc8ZBioiIyAXC5cKKicHIYeLPsWYVwWrVwq9TH3qUlOdeyvjJ9VMUqlApvdJn6xZsO7djlkqv5AvWroN9/VpIScnQ3755k873EzlPBGvWApsNx9IlJ+xn27oFK74Qvp69sa9bg2PJIqI+eo/8d9yMbeuWPIpWRCQbwSBRHwzDOT3jGXvusV9jliwVPrMPIFS5CqFy5XFN/iXcZl+zmpiXn8eKL0SwbtY7NOWEt2dvbHt2p5+xnMucc2eT/65+2P7ZhUFEREREcs8Zf3T9tttuY9euXTz99NM888wzAFx3Xfqn8K+//nr69DnxNjsiIiJycbHi4rEdOnniz0hOwrZ9G6HLux2/t0DBM54/VKYs2OzYN2/Evn07/jbtgPRKIY/1Ce5ffsJ39T8fXPL7se3YTqhTlzOeV0TyQGwsocqJOP9aQqB9p2y72bdvI1SqNMH6DTGLlyT69SFY0dHp1zZuwCxTNq8ilkhKTcXz1RfYt27BdmA/Zlw8wRo1sfLlx7F6JbZtW0m7+77T3lo6S5Z1fDvGUAjX5F9wzZxGyiMDsYoUyb155NxnWdjXrsH453sis1gxzH8+aOT55iucc37DOfd3zGIlCFWvgeunH3EsX0bqA4+A7V+f4TYM/F0uJeqj94ga9jaYJs4/5xOqUpXUe+4Dt/u0QzTLliPQpDme8d8RaNk69876S0nB88WnEPAT9dUXpDzxtM5aFREREclFubJn1VNPPcVNN93E3LlzOXToEAUKFKBZs2ba5lNEREQyMQvGYRw6eNJ+9lUrAQgmVjtJz1PkchEqXRrHsqUYhw9hlioNgJWQgK9HL9zjviVUuQrBOvWwb98KpolZtlzuxiAiZ02gbj0848dBIABOZ5Z9bNu2EmjWAgwD74034Vi4AF+Pq4l58VnsO3cQyOOYJTJcM6bh+m0mgeYtCNaqjW3PHly/z8JISSFYJRGiooh6/x2SX34V/kkMn5FgkNgBD4FlEaxeA/uWLdg3bwSHE/fPE/DefBsA9hXLcf/0A1gmOF2k3XYH1j9n5MqFwb5iOZ6xY7CvW5Oh3d+hM6EKFXH9PAHvdTfi+HsJ0e++ib9DJ9zjv8PXrQfBho0zjRdo2hzHkkXhrdR9V3bH1/1qsNvPOFbf1b1xPvYg7h+/J1SxEsahg1j5C2AmFEk///g0tkL3jPsWw+cj7dbbifrkYxxLFhGs3/CMYxURERGRdLl2WE3p0qW1raeIiIiclBUXh23nzpP2c/4xF7NESayEhFyPIVS+Aq7ff0v/fYmS4XbfVT2xb1hP1Pvv4O90Cc45v4PLTai0qn9EzhfBeg1gzGgcy5em/x7A58MI+LFi80FKSnp1V+ky6f1r1yVYuy6QfqaVbeeO8FjGwQPY168n2LhJXi9DzjbLwjVrOoGGjUnrf0+GdkwT7HaMvXuJfeJRoj77hLQbbsb98wRs+/eTdte9p1Wd5PhzIbY9uwm0aYdj3Vosl5uUZ17EsfQv3BN+wNezF5bDSfQH72LFxhIqUQrnkkU4f5uJ/8ru2Y5rX7US28EDBBo2Tq/usixse/dgJhTJWBkm5wTHkkVEvz6EUPmKpD46kGDlxPT345zf8Iz5Cqb9SqBJc/yXXk6gVWtinxyQnvS7vNvxHQn+y+kk7b6Hzkq8ZvESBFq3xT3+u0zXrPhCeK/qSaB12xwnAG0bN+CaMglvr+sItOuIc/4feEZ/QXLtupnHME08n35CsHYdgg0anfliRERERC4SZ5z4+/nnn9m5cyf9+vXLdG3EiBGUKFGCrl27nuk0IiIicoEw4+Kxr1xxwj5G0lGcixbivfbsbBkeqlARZk4Hw8AsXuJfExuk3nkvsU8PxP3zTwSaNCW10yW5t7WViJx1ZslSmMVK4Fw4P5z4ixoxHPvGDSS/+ib27dsACP2T+Mtwb4mSOP5cEH7t+nUS7p8ncHTE59lWD8r5yb5uLbadO0i78ZaMFwwjXCVlFSmCt+8tRA1/H+fCBRAMQiiIv10HQtWqn/Kc7mm/EqpSlbTb78rQbhYtinvCD7im/gpeL0ZKCsnPvJj+wZdhb+OaOzv7xF9qKtFvv4aRnIwnKppQ5SrYN67HSE7Ge/Nt+Dtqq+pzjfvnnwhVqkLKMy9kSCD7O3clUL8Rrjm/4etyKRgGVv4CpDw6EPv6tQTadYzYdphpN96Cv20HzEKFsArGYSQdxbZ7N64pk4n6ZDiuGVNJeX5wtvEZBw/gnvQzjr8WY9u5A7NESfxdL0uvur7uRmIHPY77x+/x9eiV4T732DG4pv2Kff3aU078GQcOgJGenBQRERG52Jxx4m/48OH06NEjy2sej4ePP/5YiT8REREJs+LisB0+nPGco/9wzv4dgEDLVmclhlD5igCYRYplTurFxpL84pD02KKizsr8InIWGQaBRo1xzZgKoRBGchLO+X9AKIh9+TLse3aBzY75r2rfY0IlSuLatxf8fnC5sG/cAKaJbddOnft3gXHNmo5ZOIFQzVon7Bdo1Qbbzh0YwSC+y68k5oVncM2cTtopJv5sO3dgX7WCtLvvy3TNypcff5t2uH75CcPrw9fj6nC1e6BFS5yvD8G2dUuW70H3pIkYXh8pg57HsfQv7BvW4+/YBcfyZTjn/XHBJP6MvXtx/TYD5+zfCDRvia/3dZEO6bTYtm5Jfx/c+0CW3wNZhQvj65bx5ytmmbKRf/54PIQqVwm/tAoUJFSgIGmJVQk0akL0u2+kPyf/+1xNScHz/VhcU3/F8rgJNGpCqPvVBP5V3WeWK5++1fp332BFRacnBAHH4j9x//g9wZq1cCxfhm3H9vStRXPAMe8Poj/+AMvlImXQc1k+70VEREQuZGec+Nu8eTOVK1fO8lrFihXZtGnTmU4hIiIiFxAzLh5CQYyko1j5C2TuYFm4Zk4j0KARVr78ZyeG0mXA4cQsmc0PgnLjLCcRiZhAoya4J4zHvmoljg3rwGbDLFwc97RfMQsUxCxePMtt6cwSJdO3Sdy9C7NU6fTEH2Dfvi3yP3iX3JOWhnPeH/guv/LkFVSGge9f1ef+tu3xjBtLWt9bICYmx1O6pk3BypefQKOst431db0c17RfMYsUxXfpFeH2YK06WLGxOOfOxvef96CRnITrl4n4O3YmlFiVUGLV8DWzcAJRIz7COHok639rAefs37Dt3HHOJNGMpKMZ/90PBGDWLDw//oRt+XIsTxRm0aK4fp2E78ru4PFELtjT5J78M1ZcfPq2rBeIYO06YBjYV6/KkGCzbd5E9LtvYhw5gq9b9/Qqxmy+v/Jd1RN8Pjxffop962bw+XAs/Ztg/Yak3vsA+e69A+ec30/+Xg0G8Xz1Ba7JPxNo0hz7jm3EvPw8KU89i1mseC6uWkREROTcdsYb/rvdbg4cOJDltX379uE4jYOeRURE5MJlxcUBYBw8mOV1+4b12HZsJ9Cu/dkLwuHA36r1BfWDNxE5zixfAbNwAs75f+CcPpVAs+b4L+mKY/GfOJYvy/bcTrNE+ta/9p07sO3aieFNA9KrdOTC4fxjDvh9+Fu3O+V7Ay1bQyiI64/ZGS/8UxmaJZ8P5+8z8bdpl+2WsVbRoqT1v4fU+x7KWInucBBo3AzX3NnplfL/4vrpRwzTxHflVZnGCzZomH77v7au/Tfj0EE8o0bg/ukHjKNHso47D9nXryPfXf2IeudNjCOHsa9ZTfTjj8Brr4Fpkdb/HpKGfUTqg49h+Lw456bvDGAcPUL0y+nVjucky8I1cQKOhfMxDh3EOXcOvk5dcnwe3nkhKopQ2XI41q4ONzkWzCf2uUFYHg/JL7+Kr/vVJ/5QlWHgu+Z6fN16YF+7BiM5mUDrtqT2vwdcLgKNm6b/vf3P34EMQxw4QMyLz+Ka+ivevreQdu/9pAwchBUVTczLz4PXm5urFhERETmnnXHir1GjRgwfPpzU1NQM7ampqfzvf/+jcWP9QE1ERESOMwvGA2A7fCjL685Z0zELFSZYs/ZZjcN7W38Crdue1TlEJEIMg2CjJrhmTcd2YD/+Dp3wt2gNThe2PbsIlcl8vh+AFZsPK1/+9G0ZN6wHwyBUqUr4XEC5AIRCuCdOIFivAVahUz/7y4qLJ1i3Ps6Z0zO0uyeMJ3bAQ+nniv1H+nacXvztOp5w7EDL1phly2Vub9EK4+AB7GuOJ1Zsu3bi/nUSvi5ds6zos/LlJ1itBs4F8wFwLFlE7MP3YV+xHADPV1/+k3wycM6be7Jln3WOhfOxoqNxrFxO7MP3E/PC01jRMfDuu3iffo5Aqzbg8WAVLkywbn1c06aAZeH5/FMcK5cT/fYb2LZsjvQyMvF89QWerz4n+u3XyffAvQAE2nWIcFS5L5RYDfvaNekvLAvPl58SrF6DlGdexCpSJGeDGAa+XteS/Po7pD7xNN5/VdUGmrXEtm8v9vXrsrzVsfhPYp8agO3gAVIGPYe/c9f0MxILFCT1kQH/JF1/z42lioiIiJwXzjjx9+CDD7Jr1y46derE888/z4cffsjzzz9Pp06d2LVrFw899FBuxCkiIiIXCKtAATAMjENZJP4sC+fiRQSaNj/59msiIicQaNQETJNQufKEKlSC6Gj8zVsC/2z3mw2zZClsO9ITf2bxEoSqJGJT4u/ckpKS7SXHwvkZkm/G0SM4584G0wTA+fssbHt24e3R67Sn97dph33zpuNJCK8X1y8/gWninPNbhr62nTtwjxuL79IrsIoWPa35QlUSMQsn4PnmK0hNBa+X6Ldfx4wvhO/ybtneF2zUGMfKFdg3rifq/Xcxko4SM/Rl3F9/iXPu73ivu4Fg7To45845rbhyk3PxIoKNmpD86psEWrRKr9h67kUoVy5TX3/Hzti3bMY9dgzOP2bjvaUfoRIliHntlSwTr5HimjoZ188T8N54C8kvv4q/Uxe81/U5a9uYR1KwSlVse/dgHDqIfe0abAf2p783/3uO8mkKVauOFRef/nf5X4yjR4h69y2i3xhKqEJFkl98hVCljEfRmEWLEWzQCPekn09YMSgiIiJyITnjxF/FihUZO3YsTZs25ddff2XYsGH8+uuvNG/enG+//ZaKFSvmRpwiIiJyoXA40itqsqj4+3/27ju+qvr+4/j7jDsy2CEhARJ22CBDFBmi1q0oVqt11eJAa22tdbVVW60/tdNaW20dVbR11r1wICg4GCLK3puEPTLvPeP3x4VAGkbGzb1JeD0fDx9wv+d7vt/PiXBq88nn8zULNsrYuUNu7z5JCAxAU+J27yE3v5fKzzq34gcJIqeeLq9DR7ldux38vuwcWRvWyVqxXG6XrnI75srcslkqLU1U6DgEY9dONb/+GtlzZle5Zs+aEausuuVGBT94T4Fpnyj9lhuV8veHlPL4o1IkotCrLyt69LHyOnWudQzOwEFyc/OU8s+/S5GIgh99IKOkVG6vPgp+MnVfcsH3lfLYo/IyMlReh0SjDEOl1/5Y5ro1Srv310r5x99kbtqkkp/edMj2idEhR0ueq7R775bfvIWK/viQokcfo9Bbr8vt2l3RUccretxIWcuWyCgslKJRpTz6sOzZM2sf637M9esUfONVpd5/j0IvPnfweYUFMjeuV/SowfKbNVfZFVfGKrbMA3+7wuk/UF5GW4Vef0VO/4GKnPAdlfzsFvmmqdS/P3To5I7vy9hW/8lBa+EChZ9+UpFTTlfklNPk5eap7JLLY8/VBLn5+ZIka/FiBT6bJr91G7k9e8VvA9NU5LiRCk6ZrODbb0quq8CnU5V+y42y53+j0mt/rJKf33bQ8yzLTzk9Vsk979v4xQQAANCAxaWxfF5env74xz/GYykAAHAE8DKzZG6oehaStXC+ZJpyevRMQlQAmhTDUPEdv6k05LXvoKL7D/3/W7z2HWR+GkveREeNltuhoyTJWr+uSiVJlS23b5NcT35GRo1CDXw6VcGPP1LpVRPkZedU/75pnyj48Ucqvu1XBz07rqmxFi2SohEFpk+Tc9TgfReKi5Xy1BOxpFCbDIWfflJSrEWg26OHwhP/JWvlCpnbtqrkll/UMQhLpdfdoPQ7blf4mX8pMHuWoiNHKXrMcKU+cK+sFcvkdu2u4KR3ZS1drOJf/rrOlU9ufk8V/+o3Svv9fbJWr1Lpj34ib8+fzYPxW7WW2z1f1upVKvnpTfKbNVfpdT+W07uPnN59JcNQ9KjBSgmFFfx8msz16xX4fJqMHdvlDB5ap3iN3buU/qvbJNOU16aN7EVvqfz0s6T0dElS8P135eT3kpfXSfZXsyU7UP0W34ahyGlnKvTKiyq94qpYS8dWrVV69XVKu+9uBaZ/GjuL8QDCzz2r4Ltvqeju++R17lKnZzwo31f42afkdummsosvq589Ghi/ZSt5We1kz/9WgZlfKHL8iXHv3FB+7ndlOI7Czz8bO5ty9y5Fh49U2SWXHTTht5fbs5e8jrkKTXpHJf3qt5U8AABAQ9CETpQGAACNhdulq+xv5lYZtxcskNu5q5SSkoSoAEDycnIkJypJcrt2k9e+g2QYMtetjSX+HCf2DW3LqnJvyqMPy4hEVXzXPTXaM/jRB7KWLVH6r25TydXXyRl2zGHvseZ9q5R/PiJ5ruyF8+X0H1ijPRsre9kSSVJgzmyVRiIVCbXwc89IZWUqHX+N/DZtYme4lpfL7dtPkuQHgkp5/NHYOXrtO9Q5Dq9DR5VdeLHCz/wrdjbZ2efKa5sZa0f4yVQZJSUK/2eiIqecLrdX7zrvJ0lebp6KfnOvrNWrKic9D6H0muuk0tJ97W0No/IZc+GwooOHKvTqfyXXkdO3n+xFi6T9vra1Yc+cITlR7X74H5LnqdkN1yow43NFT/iOzBXLFZ74L3kZbVV07+9kz5ktp3cfKRyu9vqRU05T5PgTpFCoYszt01fRo49V+D/PKHrU4Irz4fba23pTobBCb7+p0ut/UuvnO5TAtE9krV6l4rt+e9CqxabI7ZGv4KdTJSeq6J62ynEVCqnskssVPWa4gm+/oejxJ8gZcFT17jUMlZ9yulKe+IfMgo3y2mXHPz4AAIAGpFaJvwkTJui2225Tp06dNGHChEPONQxDjzzySK2CAwAATZPbuYuC778bO6dp7zfmfF/2wvmKjByd3OAAHNHcnD1JIcuW2zFPCgTkZWXLWrtGUd9X2r2/kZeZpdJrr690n7Frp+wF8yXDlMrLKyUkJMXGotGKiqf977OWL1XZpVfIWrJYqX/9k0qdHyt63MiDxmiuX6fUh/4op09fmQUbZc+aecQk/qzFi+TmdZK1epXsed/IGTRE1vx5Ck6ZrNIfXiW/TRtJsVav+4sef4K83Nx9/37jIHLyqbKWL5PfooW8rHaxseNGKjj5AwWmfyqn3wCVff/SuO0nSX7rNnJat6n2/OokOKIjR8XO/PvexXIGDFT6L26OfZ3rUBkV+PIzOb37yG/RUpLk9Bug4CdTFT3hOwq9/ab81m1kFBUp5fFHZS9aqLLLflDzTf7375iksosvU7NbblT4lZdUdum+Ne0vPq9ovellZSn87NMq23SR/MxMmWtWyygqik+b8fJyhV98TtGjj63yZ7Cpc/J7KfDpVHntOxzyHNW6crt1V+lPbqrxfdHhIxR+5SWlPvgHFf/yriZ51iIAAMBetfrxs+LiYrmuW/H7Q/1TVFQU14ABAEDj53aJnQFsrVpZMWZu3MD5fgCSzm/TRgqG5OZ1qmif6XbsKHPdGgW++EzW0sUKzJoRq4jajz17VuxsMc+VtXxZlXXDL/xH6XffUeX8MfvrObG2osccq9Lrf6LoiFFKefwfMtesPmiM4aeflN+ylUp+fKOcwUMV+GrWoc81ayoiEVmrVio6eoy8nPYKzPxSchylPP2E3O75io456ZC3u1261aiq7LAMQ6XX/bhSO8foyNEySkrkZWWp5PqfHrAytKFx+g1Q0R8fUuTMs+V1zJXfvIXs+bU/C21vEjw67NiKseio42UtWyL7m68VmPG5ys8aq7IfjI/9O/RcRQcMisejyG/TRmXnflfBSe8o9Q/3y5o/TykP/0WpD/9Z0aHHqOziyxQZNUZ+aqpC770ta/lSpd19p1If+Wtc9g+997aMXbtU/r2L4rJeY+Lmx9q0R44bGfc2n3ERDKr41l/K2LlTqff/VuJ7VQAAoAmrVcXfM888c8DfAwAAVIeXnSOFwrJWLJfbp68kyV44XzItzvcDkFyGIadHj1iSaA+vfQcFP3xf5gv/kdu5q6yVy2V/87WcIUdXzAnM/FJufi+Za1fLXrKoyg8xWMuXydywXtaihZVaP9pffyW3S7eKyqjSK66StXqVUv/yRxX95v+qVAgqGpW9dInKLrhISk1VdPBQBd97u+JcuabMWrki1o6ye76MnTtjrRuzc2Ru3KCi3z7QIJINXvsOKrnx5lhb2EbUtnpvxaIkOX37y573jcp1ca3WCsz4Ivb3aOiwirHooCEKp6Yq5eEH5aelKTJqjBQMyl4wT+amTfLbtq3zM+wVOeMs+a1bK/Tfl5R2393y09NVes2PYuf+GYYUDity0ikKvfOWAtOmSrYlY/s2GUW75ac3q/W+xs4dCr3xmiInn1rp63mk8Nplq/S6G2JtVhsor30HFd9+h9L+7zdKu/8eldx8e8W7twrfV2Dqx7LnzpG9ZLGig4eq7IorG8R7BgAA4HDq1HC+vLxcZ599tqZNmxaveAAAwJHANOV27hL7Ju4e1oIFsUrAeFZjAEAtlNz6K5Wff2HFZ7dDroyi3TK3bVXpdT+W16GjAjNn7LuhuFj2/HmKHn2M3O75shYtrLyg78tat1aSFJwyed+448j+Zq6cQft9ozwUUslPfy5j9y41v3a8mt1wrVIeebiios9auUKKRuTm58di65EvPz1d9qyZ8f0iNEDWksVSKCwvN0/RocNkFBcr/NLzinznVHl5nZIdXgVn8NCDJxMaAadvP1mrV8nYvUuSKn6trsCXX8jp3bdyK8VgUNFhx8ooKVHkpFNibToNQ6VXX6fi2++IZ/ixcwyHj1DR7/6kklt/qaLf/VnRkaMrJWwiJ58q+b68rGyV/Px2SZK5Zk2dtg399yX5tqXysefWaZ1Ga8/XvaEnvL3cPBX/4i6Z27cr7e47ZRYWHHBeYMpkpTz+qMydOxUdNETBjz9U+MnHjozqagAA0OjVKfEXCoVUWFgo8wg6sBoAAMRHLPG3PPZhz/l+zn5VMACQNIZRKUng5cbOq4qc8B152TmKDh0me84syXEkSYE5syXXUXTo0XLye8peukTaczSCJJmbCqXyMrm9+sSqoYqLJUnWwgUyykoVHVi5zaGX1U7F99yv0vH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", 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" ] @@ -738,13 +748,13 @@ "text": [ "\n", "Price Statistics:\n", - " ADA-USDT: Mean=$0.66, Std=$0.02\n", - " SOL-USDT: Mean=$148.99, Std=$3.42\n", + " ADA-USDT: Mean=$0.88, Std=$0.01\n", + " SOL-USDT: Mean=$222.64, Std=$1.18\n", " Price Ratio: Mean=0.00, Std=0.00\n", - " Correlation: 0.9902\n", + " Correlation: 0.8707\n", "\n", - "Created trading pair: \n", - "Market data shape: (120, 7)\n", + "Created trading pair: ResearchTradingPair: symbol_a=ADA-USDT, symbol_b=SOL-USDT, model=VECMModel\n", + "Market data shape: (71, 7)\n", "Column names: ['close_ADA-USDT', 'close_SOL-USDT']\n" ] }, @@ -769,57 +779,45 @@ "=== SLIDING FIT INTERACTIVE VISUALIZATION ===\n", "Note: Rolling Fit strategy visualization with interactive plotly charts\n", "Using consistent timeline with 659 timestamps\n", - "Timeline range: 2025-06-05 11:30:00 to 2025-06-05 22:29:00\n", + "Timeline range: 2025-09-10 11:30:00 to 2025-09-10 22:29:00\n", "\n", "Symbol_A trades:\n", - " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", - "0 2025-06-05 13:32:00 OPEN ADA-USDT BUY 0.682562 -2.446056 2.446056 -2.446056 OPEN\n", - "2 2025-06-05 13:41:00 CLOSE ADA-USDT SELL 0.683371 -0.329524 0.329524 -0.329524 CLOSE\n", - "4 2025-06-05 14:36:00 OPEN ADA-USDT BUY 0.670864 -2.065667 2.065667 -2.065667 OPEN\n", - "6 2025-06-05 14:47:00 CLOSE ADA-USDT SELL 0.677909 0.449403 0.449403 0.449403 CLOSE\n", - "8 2025-06-05 14:55:00 OPEN ADA-USDT BUY 0.673174 -2.013410 2.013410 -2.013410 OPEN\n", - "10 2025-06-05 15:22:00 CLOSE ADA-USDT SELL 0.675208 -0.182443 0.182443 -0.182443 CLOSE\n", - "12 2025-06-05 16:03:00 OPEN ADA-USDT BUY 0.671655 -2.109009 2.109009 -2.109009 OPEN\n", - "14 2025-06-05 16:27:00 CLOSE ADA-USDT SELL 0.663392 -0.340001 0.340001 -0.340001 CLOSE\n", - "16 2025-06-05 16:40:00 OPEN ADA-USDT BUY 0.660896 -2.104263 2.104263 -2.104263 OPEN\n", - "18 2025-06-05 16:47:00 CLOSE ADA-USDT SELL 0.660624 -0.448926 0.448926 -0.448926 CLOSE\n", - "20 2025-06-05 17:17:00 OPEN ADA-USDT BUY 0.663076 -2.363830 2.363830 -2.363830 OPEN\n", - "22 2025-06-05 17:41:00 CLOSE ADA-USDT SELL 0.663472 -0.201384 0.201384 -0.201384 CLOSE\n", - "24 2025-06-05 18:02:00 OPEN ADA-USDT BUY 0.660815 -2.242955 2.242955 -2.242955 OPEN\n", - "26 2025-06-05 18:36:00 CLOSE ADA-USDT SELL 0.663326 -0.409435 0.409435 -0.409435 CLOSE\n", - "28 2025-06-05 19:03:00 OPEN ADA-USDT BUY 0.657905 -2.541309 2.541309 -2.541309 OPEN\n", - "30 2025-06-05 19:19:00 CLOSE ADA-USDT SELL 0.638560 -0.044278 0.044278 -0.044278 CLOSE\n", - "32 2025-06-05 20:02:00 OPEN ADA-USDT BUY 0.641034 -2.082496 2.082496 -2.082496 OPEN\n", - "34 2025-06-05 20:13:00 CLOSE ADA-USDT SELL 0.637171 -0.443037 0.443037 -0.443037 CLOSE\n", - "36 2025-06-05 21:24:00 OPEN ADA-USDT BUY 0.623426 -2.204036 2.204036 -2.204036 OPEN\n", - "38 2025-06-05 21:46:00 CLOSE ADA-USDT SELL 0.627175 -0.353691 0.353691 -0.353691 CLOSE\n", - "40 2025-06-05 22:13:00 OPEN ADA-USDT BUY 0.622229 -2.338327 2.338327 -2.338327 OPEN\n", - "42 2025-06-05 22:27:00 CLOSE ADA-USDT SELL 0.623272 0.000000 0.000000 0.000000 CLOSE_POSITION\n", + " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", + "0 2025-09-10 13:50:00 OPEN ADA-USDT SELL 0.892900 0.001712 1.929225 1.929225 OPEN\n", + "2 2025-09-10 14:04:00 CLOSE ADA-USDT BUY 0.893018 0.001066 0.859822 0.859822 CLOSE\n", + "4 2025-09-10 14:08:00 OPEN ADA-USDT SELL 0.894122 0.002284 1.771450 1.771450 OPEN\n", + "6 2025-09-10 14:39:00 CLOSE ADA-USDT BUY 0.887826 0.000860 0.719625 0.719625 CLOSE\n", + "8 2025-09-10 15:36:00 OPEN ADA-USDT BUY 0.887343 -0.001469 1.892487 -1.892487 OPEN\n", + "10 2025-09-10 15:47:00 CLOSE ADA-USDT SELL 0.889067 0.001095 0.532319 0.532319 CLOSE\n", + "12 2025-09-10 16:12:00 OPEN ADA-USDT BUY 0.883518 -0.002233 2.232956 -2.232956 OPEN\n", + "14 2025-09-10 16:31:00 CLOSE ADA-USDT SELL 0.883613 -0.000878 0.923953 -0.923953 CLOSE\n", + "16 2025-09-10 17:08:00 OPEN ADA-USDT SELL 0.892403 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CLOSE\n", - "5 2025-06-05 14:36:00 OPEN SOL-USDT SELL 149.937010 -2.065667 2.065667 -2.065667 OPEN\n", - "7 2025-06-05 14:47:00 CLOSE SOL-USDT BUY 151.278572 0.449403 0.449403 0.449403 CLOSE\n", - "9 2025-06-05 14:55:00 OPEN SOL-USDT SELL 150.812932 -2.013410 2.013410 -2.013410 OPEN\n", - "11 2025-06-05 15:22:00 CLOSE SOL-USDT BUY 150.984110 -0.182443 0.182443 -0.182443 CLOSE\n", - "13 2025-06-05 16:03:00 OPEN SOL-USDT SELL 150.844181 -2.109009 2.109009 -2.109009 OPEN\n", - "15 2025-06-05 16:27:00 CLOSE SOL-USDT BUY 149.116981 -0.340001 0.340001 -0.340001 CLOSE\n", - "17 2025-06-05 16:40:00 OPEN SOL-USDT SELL 149.051567 -2.104263 2.104263 -2.104263 OPEN\n", - "19 2025-06-05 16:47:00 CLOSE SOL-USDT BUY 148.878845 -0.448926 0.448926 -0.448926 CLOSE\n", - "21 2025-06-05 17:17:00 OPEN SOL-USDT SELL 149.702783 -2.363830 2.363830 -2.363830 OPEN\n", - "23 2025-06-05 17:41:00 CLOSE SOL-USDT BUY 149.425867 -0.201384 0.201384 -0.201384 CLOSE\n", - "25 2025-06-05 18:02:00 OPEN SOL-USDT SELL 149.455464 -2.242955 2.242955 -2.242955 OPEN\n", - "27 2025-06-05 18:36:00 CLOSE SOL-USDT BUY 149.863517 -0.409435 0.409435 -0.409435 CLOSE\n", - "29 2025-06-05 19:03:00 OPEN SOL-USDT SELL 149.240433 -2.541309 2.541309 -2.541309 OPEN\n", - "31 2025-06-05 19:19:00 CLOSE SOL-USDT BUY 144.915997 -0.044278 0.044278 -0.044278 CLOSE\n", - "33 2025-06-05 20:02:00 OPEN SOL-USDT SELL 146.100694 -2.082496 2.082496 -2.082496 OPEN\n", - "35 2025-06-05 20:13:00 CLOSE SOL-USDT BUY 145.392057 -0.443037 0.443037 -0.443037 CLOSE\n", - "37 2025-06-05 21:24:00 OPEN SOL-USDT SELL 143.260214 -2.204036 2.204036 -2.204036 OPEN\n", - "39 2025-06-05 21:46:00 CLOSE SOL-USDT BUY 143.784983 -0.353691 0.353691 -0.353691 CLOSE\n", - "41 2025-06-05 22:13:00 OPEN SOL-USDT SELL 143.277122 -2.338327 2.338327 -2.338327 OPEN\n", - "43 2025-06-05 22:27:00 CLOSE SOL-USDT BUY 143.996271 0.000000 0.000000 0.000000 CLOSE_POSITION\n" + " time action symbol side price disequilibrium scaled_disequilibrium signed_scaled_disequilibrium status\n", + "1 2025-09-10 13:50:00 OPEN SOL-USDT BUY 224.156429 0.001712 1.929225 1.929225 OPEN\n", + "3 2025-09-10 14:04:00 CLOSE SOL-USDT SELL 224.700367 0.001066 0.859822 0.859822 CLOSE\n", + "5 2025-09-10 14:08:00 OPEN SOL-USDT BUY 224.398883 0.002284 1.771450 1.771450 OPEN\n", + "7 2025-09-10 14:39:00 CLOSE SOL-USDT SELL 222.863446 0.000860 0.719625 0.719625 CLOSE\n", + "9 2025-09-10 15:36:00 OPEN SOL-USDT SELL 223.411486 -0.001469 1.892487 -1.892487 OPEN\n", + "11 2025-09-10 15:47:00 CLOSE SOL-USDT BUY 223.034736 0.001095 0.532319 0.532319 CLOSE\n", + "13 2025-09-10 16:12:00 OPEN SOL-USDT SELL 222.807572 -0.002233 2.232956 -2.232956 OPEN\n", + "15 2025-09-10 16:31:00 CLOSE SOL-USDT BUY 222.768019 -0.000878 0.923953 -0.923953 CLOSE\n", + "17 2025-09-10 17:08:00 OPEN SOL-USDT BUY 223.490975 0.002847 1.911623 1.911623 OPEN\n", + "19 2025-09-10 17:26:00 CLOSE SOL-USDT SELL 222.226735 0.001716 0.822214 0.822214 CLOSE\n", + "21 2025-09-10 18:36:00 OPEN SOL-USDT SELL 222.436718 -0.002391 1.854279 -1.854279 OPEN\n", + "23 2025-09-10 18:44:00 CLOSE SOL-USDT BUY 222.285842 -0.001566 0.613392 -0.613392 CLOSE\n", + "25 2025-09-10 18:59:00 OPEN SOL-USDT SELL 222.784979 -0.003766 2.197313 -2.197313 OPEN\n", + "27 2025-09-10 19:32:00 CLOSE SOL-USDT BUY 221.177898 0.001427 0.903187 -0.903187 CLOSE\n", + "29 2025-09-10 20:56:00 OPEN SOL-USDT SELL 222.529393 -0.001831 1.830079 -1.830079 OPEN\n", + "31 2025-09-10 21:03:00 CLOSE SOL-USDT BUY 222.892964 -0.000235 0.004402 0.004402 CLOSE\n" ] }, { @@ -838,669 +836,669 @@ "opacity": 0.8, "type": "scatter", "x": [ - "2025-06-05T11:30:00.000000000", - "2025-06-05T11:31:00.000000000", - "2025-06-05T11:32:00.000000000", - "2025-06-05T11:33:00.000000000", - "2025-06-05T11:34:00.000000000", - "2025-06-05T11:35:00.000000000", - "2025-06-05T11:36:00.000000000", - "2025-06-05T11:37:00.000000000", - "2025-06-05T11:38:00.000000000", - "2025-06-05T11:39:00.000000000", - "2025-06-05T11:40:00.000000000", - 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Time: 2025-09-10 14:08:00
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Time: 2025-09-10 17:08:00
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