progress

__DELETE__/strategy/pair_strategy.py

@@ -0,0 +1,101 @@
+import argparse
+import asyncio
+import glob
+import importlib
+import os
+from datetime import date, datetime
+from typing import Any, Dict, List, Optional
+
+import hjson
+import pandas as pd
+
+from tools.data_loader import get_available_instruments_from_db, load_market_data
+from pt_trading.results import (
+    BacktestResult,
+    create_result_database,
+    store_config_in_database,
+    store_results_in_database,
+)
+from pt_trading.fit_methods import PairsTradingFitMethod
+from pt_trading.trading_pair import TradingPair
+
+
+def run_strategy(
+    config: Dict,
+    datafile: str,
+    fit_method: PairsTradingFitMethod,
+    instruments: List[str],
+) -> BacktestResult:
+    """
+    Run backtest for all pairs using the specified instruments.
+    """
+    bt_result: BacktestResult = BacktestResult(config=config)
+
+    def _create_pairs(config: Dict, instruments: List[str]) -> List[TradingPair]:
+        nonlocal datafile
+        all_indexes = range(len(instruments))
+        unique_index_pairs = [(i, j) for i in all_indexes for j in all_indexes if i < j]
+        pairs = []
+
+        # Update config to use the specified instruments
+        config_copy = config.copy()
+        config_copy["instruments"] = instruments
+
+        market_data_df = load_market_data(
+            datafile=datafile,
+            exchange_id=config_copy["exchange_id"],
+            instruments=config_copy["instruments"],
+            instrument_id_pfx=config_copy["instrument_id_pfx"],
+            db_table_name=config_copy["db_table_name"],
+            trading_hours=config_copy["trading_hours"],
+        )
+
+        for a_index, b_index in unique_index_pairs:
+            pair = fit_method.create_trading_pair(
+                market_data=market_data_df,
+                symbol_a=instruments[a_index],
+                symbol_b=instruments[b_index],
+            )
+            pairs.append(pair)
+        return pairs
+
+    pairs_trades = []
+    for pair in _create_pairs(config, instruments):
+        single_pair_trades = fit_method.run_pair(
+            pair=pair, config=config, bt_result=bt_result
+        )
+        if single_pair_trades is not None and len(single_pair_trades) > 0:
+            pairs_trades.append(single_pair_trades)
+
+    # Check if result_list has any data before concatenating
+    if len(pairs_trades) == 0:
+        print("No trading signals found for any pairs")
+        return bt_result
+
+    result = pd.concat(pairs_trades, ignore_index=True)
+    result["time"] = pd.to_datetime(result["time"])
+    result = result.set_index("time").sort_index()
+
+    bt_result.collect_single_day_results(result)
+    return bt_result
+
+
+def main() -> None:
+    # Load config
+    # Subscribe to CVTT market data
+    # On snapshot (with historical data) - create trading strategy with market data dateframe
+    
+    async def on_message(message_type: MessageTypeT, subscr_id: SubscriptionIdT, message: Dict, instrument_id: str) -> None:
+        print(f"{message_type=} {subscr_id=} {instrument_id}")
+        if message_type == "md_aggregate":
+            aggr = message.get("md_aggregate", [])
+            print(f"[{aggr['tstmp'][:19]}] *** RLTM ***  {message}")
+        elif message_type == "historical_md_aggregate":
+            for aggr in message.get("historical_data", []):
+                print(f"[{aggr['tstmp'][:19]}] *** HIST *** {aggr}")
+        else:
+            print(f"Unknown message type: {message_type}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())