progress

src/pt_backtest.py

@@ -49,7 +49,7 @@ def run_all_pairs(config: Dict, datafile: str, price_column: str, bt_result: Bac
     pairs_trades = []
     strategy = StaticFitStrategy()
     for pair in _create_pairs(config):
-        single_pair_trades = strategy.run_pair(pair=pair, bt_result=bt_result)
+        single_pair_trades = strategy.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

src/strategies.py

@@ -5,22 +5,10 @@ from typing import Dict, Optional
 
 import pandas as pd
 
-# ============= statsmodels ===================
-
-from backtest_configs import CRYPTO_CONFIG
 from tools.trading_pair import TradingPair
 from results import BacktestResult
 
 NanoPerMin = 1e9
-UNSET_FLOAT: float = sys.float_info.max
-UNSET_INT: int = sys.maxsize
-
-
-CONFIG = CRYPTO_CONFIG
-# CONFIG = EQT_CONFIG
-
-
-
 
 class PairsTradingStrategy(ABC):
     TRADES_COLUMNS = [
@@ -38,8 +26,8 @@ class PairsTradingStrategy(ABC):
 
 class StaticFitStrategy(PairsTradingStrategy):
     
-    def run_pair(self, pair: TradingPair, bt_result: BacktestResult) -> Optional[pd.DataFrame]: # abstractmethod
+    def run_pair(self, config: Dict, pair: TradingPair, bt_result: BacktestResult) -> Optional[pd.DataFrame]: # abstractmethod
-        pair.get_datasets(training_minutes=CONFIG["training_minutes"])
+        pair.get_datasets(training_minutes=config["training_minutes"])
         try:
             is_cointegrated = pair.train_pair()
             if not is_cointegrated:
@@ -55,7 +43,7 @@ class StaticFitStrategy(PairsTradingStrategy):
             print(f"{pair}: Prediction failed: {str(e)}")
             return None
             
-        pair_trades = self.create_trading_signals(pair=pair, config=CONFIG, result=bt_result)
+        pair_trades = self.create_trading_signals(pair=pair, config=config, result=bt_result)
 
         return pair_trades
 
@@ -211,3 +199,42 @@ class StaticFitStrategy(PairsTradingStrategy):
             columns=self.TRADES_COLUMNS,
         )
 
+class SlidingFitStrategy(PairsTradingStrategy):
+    def __init__(self):
+        super().__init__()
+        self.curr_training_start_idx_ = 0 
+           
+    def run_pair(self, config: Dict, pair: TradingPair, bt_result: BacktestResult) -> Optional[pd.DataFrame]: 
+        pair.user_data_['is_position_open'] = False
+        training_minutes = config["training_minutes"]
+        while True:
+            pair.get_datasets(
+                training_minutes=training_minutes, 
+                training_start_index=self.curr_training_start_idx_, 
+                testing_size=1
+            )
+            
+            if len(pair.training_df_) < training_minutes:
+                print(f"{pair}: Not enough training data. Completing the job.")
+                break
+            
+            try:
+                is_cointegrated = pair.train_pair()
+                if not is_cointegrated:
+                    print(f"{pair} IS NOT COINTEGRATED")
+                    return None
+            except Exception as e:
+                print(f"{pair}: Training failed: {str(e)}")
+                return None
+
+            try:
+                pair.predict()
+            except Exception as e:
+                print(f"{pair}: Prediction failed: {str(e)}")
+                return None
+        
+
+            pair_trades = self.create_trading_signals(pair=pair, config=config, result=bt_result)
+
+        return pair_trades
+