102 lines
3.4 KiB
Python
102 lines
3.4 KiB
Python
import argparse
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import asyncio
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import glob
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import importlib
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import os
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from datetime import date, datetime
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from typing import Any, Dict, List, Optional
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import hjson
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import pandas as pd
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from tools.data_loader import get_available_instruments_from_db, load_market_data
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from pt_trading.results import (
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BacktestResult,
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create_result_database,
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store_config_in_database,
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store_results_in_database,
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)
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from pt_trading.fit_methods import PairsTradingFitMethod
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from pt_trading.trading_pair import TradingPair
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def run_strategy(
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config: Dict,
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datafile: str,
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fit_method: PairsTradingFitMethod,
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instruments: List[str],
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) -> BacktestResult:
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"""
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Run backtest for all pairs using the specified instruments.
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"""
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bt_result: BacktestResult = BacktestResult(config=config)
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def _create_pairs(config: Dict, instruments: List[str]) -> List[TradingPair]:
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nonlocal datafile
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all_indexes = range(len(instruments))
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unique_index_pairs = [(i, j) for i in all_indexes for j in all_indexes if i < j]
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pairs = []
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# Update config to use the specified instruments
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config_copy = config.copy()
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config_copy["instruments"] = instruments
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market_data_df = load_market_data(
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datafile=datafile,
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exchange_id=config_copy["exchange_id"],
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instruments=config_copy["instruments"],
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instrument_id_pfx=config_copy["instrument_id_pfx"],
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db_table_name=config_copy["db_table_name"],
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trading_hours=config_copy["trading_hours"],
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)
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for a_index, b_index in unique_index_pairs:
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pair = fit_method.create_trading_pair(
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market_data=market_data_df,
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symbol_a=instruments[a_index],
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symbol_b=instruments[b_index],
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)
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pairs.append(pair)
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return pairs
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pairs_trades = []
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for pair in _create_pairs(config, instruments):
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single_pair_trades = fit_method.run_pair(
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pair=pair, config=config, bt_result=bt_result
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)
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if single_pair_trades is not None and len(single_pair_trades) > 0:
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pairs_trades.append(single_pair_trades)
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# Check if result_list has any data before concatenating
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if len(pairs_trades) == 0:
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print("No trading signals found for any pairs")
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return bt_result
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result = pd.concat(pairs_trades, ignore_index=True)
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result["time"] = pd.to_datetime(result["time"])
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result = result.set_index("time").sort_index()
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bt_result.collect_single_day_results(result)
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return bt_result
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def main() -> None:
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# Load config
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# Subscribe to CVTT market data
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# On snapshot (with historical data) - create trading strategy with market data dateframe
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async def on_message(message_type: MessageTypeT, subscr_id: SubscriptionIdT, message: Dict, instrument_id: str) -> None:
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print(f"{message_type=} {subscr_id=} {instrument_id}")
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if message_type == "md_aggregate":
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aggr = message.get("md_aggregate", [])
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print(f"[{aggr['tstamp'][:19]}] *** RLTM *** {message}")
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elif message_type == "historical_md_aggregate":
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for aggr in message.get("historical_data", []):
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print(f"[{aggr['tstamp'][:19]}] *** HIST *** {aggr}")
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else:
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print(f"Unknown message type: {message_type}")
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if __name__ == "__main__":
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asyncio.run(main())
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