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@ -13,6 +13,7 @@ from cvttpy_tools.logger import Log
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from cvttpy_trading.trading.instrument import ExchangeInstrument
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from cvttpy_trading.trading.active_instruments import Instruments
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from cvttpy_trading.trading.mkt_data.md_summary import MdTradesAggregate
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from cvttpy_trading.trading.exchange_config import ExchangeAccounts
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# ---
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from pairs_trading.lib.pt_strategy.live.live_strategy import PtLiveStrategy
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from pairs_trading.lib.live.mkt_data_client import CvttRestMktDataClient, MdSummary
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@ -42,7 +43,7 @@ UpdateMdCbT = Callable[[MdTradesAggregate], Coroutine]
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class PairsTrader(NamedObject):
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config_: CvttAppConfig
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instruments_: List[JsonDictT]
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instruments_: List[ExchangeInstrument]
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live_strategy_: PtLiveStrategy
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pricer_client_: CvttRestMktDataClient
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@ -72,20 +73,22 @@ class PairsTrader(NamedObject):
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if not instr_str:
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raise ValueError("Pair is required")
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instr_list = instr_str.split(",")
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assert len(instr_list) == 2, "Only two instruments are supported"
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for instr in instr_list:
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instr_parts = instr.split(":")
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if len(instr_parts) != 2:
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raise ValueError(f"Invalid pair format: {instr}")
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instrument_id = instr_parts[0]
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exch_acct = instr_parts[1]
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exch_inst = Instruments.instance()
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self.instruments_.append({
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"exch_acct": exch_acct,
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"instrument_id": instrument_id
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})
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exch_inst = ExchangeAccounts.instance().get_exchange_instrument(exch_acct=exch_acct, instrument_id=instrument_id)
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assert len(self.instruments_) == 2, "Only two instruments are supported"
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Log.info(f"{self.fname()} Instruments: {self.instruments_}")
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assert exch_inst is not None, f"No ExchangeInstrument for {instr}"
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exch_inst.user_data_["exch_acct"] = exch_acct
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self.instruments_.append(exch_inst)
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Log.info(f"{self.fname()} Instruments: {self.instruments_[0].details_short()} <==> {self.instruments_[1].details_short()}")
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# ------- CREATE CVTT CLIENT -------
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@ -95,7 +98,7 @@ class PairsTrader(NamedObject):
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# ------- CREATE STRATEGY -------
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strategy_config = self.config_.get_value("strategy_config", {})
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strategy_config = self.config_.get_subconfig("strategy_config", Config({}))
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self.live_strategy_ = PtLiveStrategy(
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config=strategy_config,
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instruments=self.instruments_,
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@ -104,7 +107,7 @@ class PairsTrader(NamedObject):
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Log.info(f"{self.fname()} Strategy created: {self.live_strategy_}")
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# # ------- CREATE PRICER CLIENT -------
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self.pricer_client_ = CvttRestMktDataClient(self.config_)
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self.pricer_client_ = CvttRestMktDataClient(config=self.config_)
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# ------- CREATE TRADER CLIENT -------
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# URGENT CREATE TRADER CLIENT
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@ -118,9 +121,10 @@ class PairsTrader(NamedObject):
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# URGENT CREATE REST SERVER for dashboard communications
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async def subscribe_md(self) -> None:
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for inst in self.instruments_:
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exch_acct = inst.get("exch_acct", "?exch_acct?")
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instrument_id = inst.get("instrument_id", "?instrument_id?")
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for exch_inst in self.instruments_:
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exch_acct = exch_inst.user_data_.get("exch_acct", "?exch_acct?")
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instrument_id = exch_inst.instrument_id()
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await self.pricer_client_.add_subscription(
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exch_acct=exch_acct,
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instrument_id=instrument_id,
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@ -129,7 +133,9 @@ class PairsTrader(NamedObject):
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callback=self._on_md_summary
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)
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def _on_md_summary(self, history: List[MdSummary]) -> None:
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async def _on_md_summary(self, history: List[MdSummary]) -> None:
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# depth = len(history)
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# if depth < 2:
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pass # URGENT
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async def run(self) -> None:
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@ -1,7 +1,7 @@
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from __future__ import annotations
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import asyncio
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from typing import Callable, Dict, Any, List, Optional, Set
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from typing import Callable, Coroutine, Dict, Any, List, Optional, Set
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import requests
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@ -60,7 +60,7 @@ class MdSummary(HistMdBar):
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)
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return res
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MdSummaryCallbackT = Callable[[List[MdSummary]], None]
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MdSummaryCallbackT = Callable[[List[MdSummary]], Coroutine]
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class MdSummaryCollector(NamedObject):
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sender_: RESTSender
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@ -134,7 +134,7 @@ class MdSummaryCollector(NamedObject):
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Log.error(f"{self.fname()}: Timer is already started")
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return
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self.history_ = self.get_history()
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self.run_callbacks()
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await self.run_callbacks()
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self.set_timer()
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def set_timer(self):
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@ -158,11 +158,11 @@ class MdSummaryCollector(NamedObject):
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Log.info(f"{self.fname()}: Received {last}. Already Have: {self.history_[-1]}")
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else:
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self.history_.append(last)
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self.run_callbacks()
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await self.run_callbacks()
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self.set_timer()
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def run_callbacks(self) -> None:
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[cb(self.history_) for cb in self.callbacks_]
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async def run_callbacks(self) -> None:
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[await cb(self.history_) for cb in self.callbacks_]
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def stop(self) -> None:
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if self.timer_:
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@ -203,7 +203,7 @@ if __name__ == "__main__":
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config = Config(json_src={"cvtt_base_url": "http://cvtt-tester-01.cvtt.vpn:23456"})
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# config = Config(json_src={"cvtt_base_url": "http://dev-server-02.cvtt.vpn:23456"})
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def _calback(history: List[MdSummary]) -> None:
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async def _calback(history: List[MdSummary]) -> None:
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Log.info(f"MdSummary Hist Length is {len(history)}. Last summary: {history[-1] if len(history) > 0 else '[]'}")
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@ -1,22 +1,28 @@
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import Any, Dict, List, Optional
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from typing import Any, Dict, List, Optional, cast
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from enum import Enum
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import pandas as pd
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# ---
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from cvttpy_tools.base import NamedObject
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from cvttpy_tools.app import App
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from cvttpy_tools.config import Config
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from cvttpy_tools.settings.cvtt_types import IntervalSecT
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from cvttpy_tools.timeutils import SecPerHour
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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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# ---
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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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@ -26,6 +32,7 @@ from pairs_trading.apps.pairs_trader import PairsTrader
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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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@ -34,7 +41,14 @@ class TradingInstruction(NamedObject):
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class PtLiveStrategy(NamedObject):
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config_: Dict[str, Any]
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config_: Config
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instruments_: List[ExchangeInstrument]
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interval_sec_: IntervalSecT
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history_depth_sec_: IntervalSecT
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open_threshold_: float
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close_threshold_: float
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trading_pair_: TradingPair
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model_data_policy_: ModelDataPolicy
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pairs_trader_: PairsTrader
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@ -42,46 +56,66 @@ class PtLiveStrategy(NamedObject):
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# ti_sender_: TradingInstructionsSender
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# for presentation: history of prediction values and trading signals
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predictions_: pd.DataFrame
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trading_signals_: pd.DataFrame
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predictions_df_: pd.DataFrame
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trading_signals_df_: pd.DataFrame
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def __init__(
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self,
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config: Dict[str, Any],
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instruments: List[Dict[str, str]],
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config: Config,
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instruments: List[ExchangeInstrument],
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pairs_trader: PairsTrader,
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):
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self.config_ = config
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self.trading_pair_ = TradingPair(config=config, instruments=instruments)
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self.predictions_ = pd.DataFrame()
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self.trading_signals_ = pd.DataFrame()
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self.trading_pair_ = TradingPair(
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config=cast(Dict[str, Any], config.data()),
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instruments=[{"instrument_id": ei.instrument_id()} for ei in instruments],
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)
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self.predictions_df_ = pd.DataFrame()
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self.trading_signals_df_ = pd.DataFrame()
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self.pairs_trader_ = pairs_trader
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import copy
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# modified config must be passed to PtMarketData
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config_copy = copy.deepcopy(config)
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config_copy["instruments"] = instruments
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self.config_ = config_copy
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self.config_ = Config(json_src=copy.deepcopy(config.data()))
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App.instance().add_call(stage=App.Stage.Config, func=self._on_config(), can_run_now=True)
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self.instruments_ = instruments
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App.instance().add_call(
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stage=App.Stage.Config, func=self._on_config(), can_run_now=True
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)
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async def _on_config(self) -> None:
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self.interval_sec_ = self.config_.get_value("interval_sec", 0)
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self.history_depth_sec_ = (
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self.config_.get_value("history_depth_hours", 0) * SecPerHour
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)
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await self.pairs_trader_.subscribe_md()
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self.model_data_policy_ = ModelDataPolicy.create(
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self.config_, is_real_time=True, pair=self.trading_pair_
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)
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self.open_threshold_ = self.config_.get("dis-equilibrium_open_trshld", 0.0)
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assert self.open_threshold_ > 0, "open_threshold must be greater than 0"
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self.close_threshold_ = self.config_.get("dis-equilibrium_close_trshld", 0.0)
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assert self.close_threshold_ > 0, "close_threshold must be greater than 0"
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self.open_threshold_ = self.config_.get_value(
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"dis-equilibrium_open_trshld", 0.0
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)
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self.close_threshold_ = self.config_.get_value(
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"dis-equilibrium_close_trshld", 0.0
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)
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assert (
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self.open_threshold_ > 0
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), "dis-equilibrium_open_trshld must be greater than 0"
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assert (
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self.close_threshold_ > 0
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), "dis-equilibrium_close_trshld must be greater than 0"
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def __repr__(self) -> str:
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return f"{self.classname()}: trading_pair={self.trading_pair_}, mdp={self.model_data_policy_.__class__.__name__}, "
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async def on_mkt_data_hist_snapshot(self, hist_aggr: List[MdTradesAggregate]) -> None:
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async def on_mkt_data_hist_snapshot(
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self, hist_aggr: List[MdTradesAggregate]
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) -> None:
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# Log.info(f"on_mkt_data_hist_snapshot: {aggr}")
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# await self.pt_mkt_data_.on_mkt_data_hist_snapshot(snapshot=aggr)
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pass # URGENT PtiveStrategy.on_mkt_data_hist_snapshot()
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@ -108,10 +142,10 @@ class PtLiveStrategy(NamedObject):
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pass # URGENT
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def interval_sec(self) -> IntervalSecT:
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return 60 # URGENT use config
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return self.interval_sec_
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def history_depth_sec(self) -> IntervalSecT:
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return 3600 * 60 * 2 # URGENT use config
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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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@ -135,7 +169,7 @@ class PtLiveStrategy(NamedObject):
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elif pair.is_open():
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if abs_scaled_disequilibrium <= self.close_threshold_:
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trd_instructions = self._create_close_trade_instructions(
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pair, row=last_row #, prediction=prediction
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pair, row=last_row # , prediction=prediction
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)
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elif pair.to_stop_close_conditions(predicted_row=last_row):
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trd_instructions = self._create_close_trade_instructions(
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@ -204,14 +238,13 @@ class PtLiveStrategy(NamedObject):
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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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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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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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@ -223,7 +256,7 @@ class PtLiveStrategy(NamedObject):
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if pair.user_data_["state"] == PairState.OPEN:
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print(f"{pair}: *** Position is NOT CLOSED. ***")
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# outstanding positions
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if self.config_["close_outstanding_positions"]:
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if self.config_.key_exists("close_outstanding_positions"):
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close_position_row = pd.Series(pair.market_data_.iloc[-2])
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# close_position_row["disequilibrium"] = 0.0
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# close_position_row["scaled_disequilibrium"] = 0.0
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@ -8,6 +8,7 @@ from typing import Any, Dict, Optional, cast
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import numpy as np
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import pandas as pd
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from cvttpy_tools.config import Config
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@dataclass
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class DataWindowParams:
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@ -16,22 +17,22 @@ class DataWindowParams:
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class ModelDataPolicy(ABC):
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config_: Dict[str, Any]
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config_: Config
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current_data_params_: DataWindowParams
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count_: int
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is_real_time_: bool
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def __init__(self, config: Dict[str, Any], *args: Any, **kwargs: Any):
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def __init__(self, config: Config, *args: Any, **kwargs: Any):
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self.config_ = config
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training_size = config.get("training_size", 120)
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training_size = config.get_value("training_size", 120)
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training_start_index = 0
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if kwargs.get("is_real_time", False):
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training_size = 120
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training_start_index = 0
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else:
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training_size = config.get("training_size", 120)
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training_size = config.get_value("training_size", 120)
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self.current_data_params_ = DataWindowParams(
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training_size=config.get("training_size", 120),
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training_size=config.get_value("training_size", 120),
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training_start_index=0,
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)
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self.count_ = 0
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@ -44,10 +45,10 @@ class ModelDataPolicy(ABC):
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return self.current_data_params_
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@staticmethod
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def create(config: Dict[str, Any], *args: Any, **kwargs: Any) -> ModelDataPolicy:
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def create(config: Config, *args: Any, **kwargs: Any) -> ModelDataPolicy:
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import importlib
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model_data_policy_class_name = config.get("model_data_policy_class", None)
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model_data_policy_class_name = config.get_value("model_data_policy_class", None)
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assert model_data_policy_class_name is not None
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module_name, class_name = model_data_policy_class_name.rsplit(".", 1)
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module = importlib.import_module(module_name)
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@ -58,7 +59,7 @@ class ModelDataPolicy(ABC):
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class RollingWindowDataPolicy(ModelDataPolicy):
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def __init__(self, config: Dict[str, Any], *args: Any, **kwargs: Any):
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def __init__(self, config: Config, *args: Any, **kwargs: Any):
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super().__init__(config, *args, **kwargs)
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self.count_ = 1
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@ -80,16 +81,16 @@ class OptimizedWndDataPolicy(ModelDataPolicy, ABC):
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prices_a_: np.ndarray
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prices_b_: np.ndarray
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def __init__(self, config: Dict[str, Any], *args: Any, **kwargs: Any):
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def __init__(self, config: Config, *args: Any, **kwargs: Any):
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super().__init__(config, *args, **kwargs)
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assert (
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kwargs.get("pair") is not None
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), "pair must be provided"
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assert (
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"min_training_size" in config and "max_training_size" in config
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"min_training_size" in config.data() and "max_training_size" in config.data()
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), "min_training_size and max_training_size must be provided"
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self.min_training_size_ = cast(int, config.get("min_training_size"))
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self.max_training_size_ = cast(int, config.get("max_training_size"))
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self.min_training_size_ = cast(int, config.get_value("min_training_size"))
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self.max_training_size_ = cast(int, config.get_value("max_training_size"))
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from pairs_trading.lib.pt_strategy.trading_pair import TradingPair
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self.pair_ = cast(TradingPair, kwargs.get("pair"))
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@ -133,7 +134,7 @@ class EGOptimizedWndDataPolicy(OptimizedWndDataPolicy):
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# Engle-Granger cointegration test
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*** VERY SLOW ***
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'''
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def __init__(self, config: Dict[str, Any], *args: Any, **kwargs: Any):
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def __init__(self, config: Config, *args: Any, **kwargs: Any):
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super().__init__(config, *args, **kwargs)
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def optimize_window_size(self) -> DataWindowParams:
|
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@ -162,7 +163,7 @@ class EGOptimizedWndDataPolicy(OptimizedWndDataPolicy):
|
||||
|
||||
class ADFOptimizedWndDataPolicy(OptimizedWndDataPolicy):
|
||||
# Augmented Dickey-Fuller test
|
||||
def __init__(self, config: Dict[str, Any], *args: Any, **kwargs: Any):
|
||||
def __init__(self, config: Config, *args: Any, **kwargs: Any):
|
||||
super().__init__(config, *args, **kwargs)
|
||||
|
||||
def optimize_window_size(self) -> DataWindowParams:
|
||||
@ -208,7 +209,7 @@ class ADFOptimizedWndDataPolicy(OptimizedWndDataPolicy):
|
||||
|
||||
class JohansenOptdWndDataPolicy(OptimizedWndDataPolicy):
|
||||
# Johansen test
|
||||
def __init__(self, config: Dict[str, Any], *args: Any, **kwargs: Any):
|
||||
def __init__(self, config: Config, *args: Any, **kwargs: Any):
|
||||
super().__init__(config, *args, **kwargs)
|
||||
|
||||
def optimize_window_size(self) -> DataWindowParams:
|
||||
|
||||
@ -3,6 +3,8 @@ from __future__ import annotations
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
import pandas as pd
|
||||
from cvttpy_tools.config import Config
|
||||
|
||||
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
|
||||
@ -41,7 +43,7 @@ class PtResearchStrategy:
|
||||
self.pt_mkt_data_ = ResearchMarketData(config=config_copy)
|
||||
self.pt_mkt_data_.load()
|
||||
self.model_data_policy_ = ModelDataPolicy.create(
|
||||
config, mkt_data=self.pt_mkt_data_.market_data_df_, pair=self.trading_pair_
|
||||
Config(config_copy), mkt_data=self.pt_mkt_data_.market_data_df_, pair=self.trading_pair_
|
||||
)
|
||||
|
||||
def outstanding_positions(self) -> List[Dict[str, Any]]:
|
||||
|
||||
Loading…
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Reference in New Issue
Block a user