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@ -34,6 +34,7 @@ class PairsTrader(NamedObject):
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live_strategy_: PtLiveStrategy
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pricer_client_: CvttRestMktDataClient
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ti_sender_: TradingInstructionsSender
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rest_service_: RestService
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def __init__(self) -> None:
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@ -100,8 +101,7 @@ class PairsTrader(NamedObject):
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# ------- CREATE TRADER CLIENT -------
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self.ti_sender_ = TradingInstructionsSender(config=self.config_, pairs_trader=self)
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Log.info(f"{self.fname()} TI client created: {self.ti_sender_}")
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Log.info(f"{self.fname()} TI sebder created: {self.ti_sender_}")
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# # ------- CREATE REST SERVER -------
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self.rest_service_ = RestService(
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@ -17,28 +17,29 @@ from cvttpy_tools.logger import Log
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# ---
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from cvttpy_trading.trading.instrument import ExchangeInstrument
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from cvttpy_trading.trading.mkt_data.md_summary import MdTradesAggregate
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from cvttpy_trading.trading.trading_instructions import TradingInstructions
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# ---
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from pairs_trading.lib.pt_strategy.model_data_policy import ModelDataPolicy
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from pairs_trading.lib.pt_strategy.pt_model import Prediction
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from pairs_trading.lib.pt_strategy.trading_pair import PairState, TradingPair
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from pairs_trading.apps.pairs_trader import PairsTrader
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"""
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--config=pair.cfg
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--pair=PAIR-BTC-USDT:COINBASE_AT,PAIR-ETH-USDT:COINBASE_AT
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"""
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class TradingInstructionType(Enum):
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TARGET_POSITION = "TARGET_POSITION"
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# class TradingInstructionType(Enum):
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# TARGET_POSITION = "TARGET_POSITION"
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@dataclass
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class TradingInstruction(NamedObject):
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type_: TradingInstructionType
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exch_instr_: ExchangeInstrument
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specifics_: Dict[str, Any]
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# @dataclass
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# class TradingInstruction(NamedObject):
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# type_: TradingInstructionType
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# exch_instr_: ExchangeInstrument
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# specifics_: Dict[str, Any]
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class PtLiveStrategy(NamedObject):
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@ -135,12 +136,12 @@ class PtLiveStrategy(NamedObject):
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[self.predictions_df_, prediction.to_df()], ignore_index=True
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)
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trading_instructions: List[TradingInstruction] = (
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trading_instructions: Optional[TradingInstructions] = (
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self._create_trading_instructions(
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prediction=prediction, last_row=market_data_df.iloc[-1]
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)
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)
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if len(trading_instructions) > 0:
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if trading_instructions is not None:
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await self._send_trading_instructions(trading_instructions)
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def _is_md_actual(self, hist_aggr: List[MdTradesAggregate]) -> bool:
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@ -156,15 +157,16 @@ class PtLiveStrategy(NamedObject):
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return self.history_depth_sec_
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async def _send_trading_instructions(
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self, trading_instructions: List[TradingInstruction]
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self, trading_instructions: TradingInstructions
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) -> None:
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await self.pairs_trader_.ti_sender_.send_trading_instructions(trading_instructions)
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pass # URGENT implement _send_trading_instructions
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def _create_trading_instructions(
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self, prediction: Prediction, last_row: pd.Series
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) -> List[TradingInstruction]:
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) -> Optional[TradingInstructions]:
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pair = self.trading_pair_
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trd_instructions: List[TradingInstruction] = []
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res: Optional[TradingInstructions]
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scaled_disequilibrium = prediction.scaled_disequilibrium_
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abs_scaled_disequilibrium = abs(scaled_disequilibrium)
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@ -188,73 +190,76 @@ class PtLiveStrategy(NamedObject):
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def _create_open_trade_instructions(
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self, pair: TradingPair, row: pd.Series, prediction: Prediction
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) -> List[TradingInstruction]:
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) -> Optional[TradingInstructions]:
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ti: Optional[TradingInstructions] = None
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scaled_disequilibrium = prediction.scaled_disequilibrium_
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if scaled_disequilibrium > 0:
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side_a = "SELL"
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trd_inst_a = TradingInstruction(
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type_=TradingInstructionType.TARGET_POSITION,
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exch_instr_=pair.get_instrument_a(),
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specifics_={"side": "SELL", "strength": -1},
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)
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side_b = "BUY"
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else:
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side_a = "BUY"
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side_b = "SELL"
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# if scaled_disequilibrium > 0:
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# side_a = "SELL"
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# trd_inst_a = TradingInstruction(
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# type_=TradingInstructionType.TARGET_POSITION,
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# exch_instr_=pair.get_instrument_a(),
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# specifics_={"side": "SELL", "strength": -1},
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# )
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# side_b = "BUY"
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# else:
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# side_a = "BUY"
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# side_b = "SELL"
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colname_a, colname_b = pair.exec_prices_colnames()
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px_a = row[f"{colname_a}"]
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px_b = row[f"{colname_b}"]
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# colname_a, colname_b = pair.exec_prices_colnames()
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# px_a = row[f"{colname_a}"]
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# px_b = row[f"{colname_b}"]
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tstamp = row["tstamp"]
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diseqlbrm = prediction.disequilibrium_
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scaled_disequilibrium = prediction.scaled_disequilibrium_
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# tstamp = row["tstamp"]
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# diseqlbrm = prediction.disequilibrium_
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# scaled_disequilibrium = prediction.scaled_disequilibrium_
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df = self._trades_df()
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# df = self._trades_df()
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# save closing sides
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pair.user_data_["open_side_a"] = side_a # used in oustanding positions
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pair.user_data_["open_side_b"] = side_b
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pair.user_data_["open_px_a"] = px_a
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pair.user_data_["open_px_b"] = px_b
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pair.user_data_["open_tstamp"] = tstamp
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# # save closing sides
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# pair.user_data_["open_side_a"] = side_a # used in oustanding positions
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# pair.user_data_["open_side_b"] = side_b
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# pair.user_data_["open_px_a"] = px_a
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# pair.user_data_["open_px_b"] = px_b
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# pair.user_data_["open_tstamp"] = tstamp
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pair.user_data_["close_side_a"] = side_b # used for closing trades
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pair.user_data_["close_side_b"] = side_a
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# pair.user_data_["close_side_a"] = side_b # used for closing trades
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# pair.user_data_["close_side_b"] = side_a
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# create opening trades
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df.loc[len(df)] = {
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"time": tstamp,
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"symbol": pair.symbol_a_,
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"side": side_a,
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"action": "OPEN",
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"price": px_a,
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"disequilibrium": diseqlbrm,
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"signed_scaled_disequilibrium": scaled_disequilibrium,
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"scaled_disequilibrium": abs(scaled_disequilibrium),
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# "pair": pair,
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}
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df.loc[len(df)] = {
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"time": tstamp,
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"symbol": pair.symbol_b_,
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"side": side_b,
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"action": "OPEN",
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"price": px_b,
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"disequilibrium": diseqlbrm,
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"scaled_disequilibrium": abs(scaled_disequilibrium),
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"signed_scaled_disequilibrium": scaled_disequilibrium,
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# "pair": pair,
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}
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ti: List[TradingInstruction] = self._create_trading_instructions(
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prediction=prediction, last_row=row
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)
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# # create opening trades
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# df.loc[len(df)] = {
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# "time": tstamp,
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# "symbol": pair.symbol_a_,
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# "side": side_a,
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# "action": "OPEN",
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# "price": px_a,
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# "disequilibrium": diseqlbrm,
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# "signed_scaled_disequilibrium": scaled_disequilibrium,
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# "scaled_disequilibrium": abs(scaled_disequilibrium),
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# # "pair": pair,
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# }
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# df.loc[len(df)] = {
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# "time": tstamp,
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# "symbol": pair.symbol_b_,
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# "side": side_b,
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# "action": "OPEN",
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# "price": px_b,
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# "disequilibrium": diseqlbrm,
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# "scaled_disequilibrium": abs(scaled_disequilibrium),
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# "signed_scaled_disequilibrium": scaled_disequilibrium,
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# # "pair": pair,
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# }
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# ti: List[TradingInstruction] = self._create_trading_instructions(
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# prediction=prediction, last_row=row
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# )
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return ti
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def _create_close_trade_instructions(
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self, pair: TradingPair, row: pd.Series # , prediction: Prediction
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) -> List[TradingInstruction]:
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return [] # URGENT implement _create_close_trade_instructions
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) -> Optional[TradingInstructions]:
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ti: Optional[TradingInstructions] = None
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# URGENT implement _create_close_trade_instructions
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return ti
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def _handle_outstanding_positions(self) -> Optional[pd.DataFrame]:
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trades = None
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