Implement RSI Strategy using backtrader Fix issue #5

scripts/backtest_runner.py

@@ -0,0 +1,103 @@
+import pandas as pd
+from sqlalchemy import create_engine
+import backtrader as bt
+import os
+
+# RDS connection information
+rds_host = os.getenv('PG_HOST')
+rds_port = os.getenv('PG_PORT')
+rds_db = os.getenv('PG_DATABASE')
+rds_user = os.getenv('PG_USER')
+rds_password = os.getenv('PG_PASSWORD')
+
+engine = create_engine(f'postgresql+psycopg2://{rds_user}:{rds_password}@{rds_host}:{rds_port}/{rds_db}')
+
+def fetch_data(symbol, start_date, end_date):
+    query = f"""
+        SELECT timestamp AS date, open AS open, high AS high, low AS low, close AS close, volume AS volume 
+        FROM public."ohlcv_{symbol.replace('/', '_')}"
+        WHERE timestamp >= '{start_date}' AND timestamp <= '{end_date}';
+    """
+    try:
+        print(f"Executing query:\n{query}\n")  # Print the SQL query for debugging purposes
+
+        data = pd.read_sql(query, con=engine)
+        print(f"Fetched data:\n{data.head()}\n")  # Print the first few rows of fetched data for debugging
+
+        # Check if data is empty
+        if data.empty:
+            raise ValueError("No data returned from query.")
+
+        # Convert 'date' column to datetime
+        data['date'] = pd.to_datetime(data['date'], format='%Y-%m-%d')
+
+        # Set 'date' column as index
+        data.set_index('date', inplace=True)
+
+        # Ensure column names are correctly capitalized for Backtrader
+        data.rename(columns={'open': 'Open', 'high': 'High', 'low': 'Low', 'close': 'Close', 'volume': 'Volume'}, inplace=True)
+
+        return data
+    except Exception as e:
+        print(f"Error fetching data: {e}")
+        raise
+
+class RsiBollingerBandsStrategy(bt.Strategy):
+    params = (
+        ('rsi_period', 14),
+        ('bb_period', 20),
+        ('bb_dev', 2),
+        ('oversold', 30),
+        ('overbought', 70),
+    )
+
+    def __init__(self):
+        self.rsi = bt.indicators.RelativeStrengthIndex(period=self.params.rsi_period)
+        self.bbands = bt.indicators.BollingerBands(period=self.params.bb_period, devfactor=self.params.bb_dev)
+
+    def next(self):
+        if not self.position:
+            if self.rsi < self.params.oversold and self.data.close <= self.bbands.lines.bot:
+                self.buy()
+        else:
+            if self.rsi > self.params.overbought or self.data.close >= self.bbands.lines.top:
+                self.sell()
+
+def run_backtest(strategy, symbol, start_date, end_date):
+    data = fetch_data(symbol, start_date, end_date)
+
+    # Create a data feed
+    data_feed = bt.feeds.PandasData(dataname=data)
+
+    # Initialize cerebro
+    cerebro = bt.Cerebro()
+    cerebro.addstrategy(strategy)
+    cerebro.adddata(data_feed)
+    cerebro.broker.set_cash(10000)
+    cerebro.broker.setcommission(commission=0.002)
+
+    # Print starting conditions
+    print(f'Starting Portfolio Value: {cerebro.broker.getvalue():.2f}')
+
+    # Run backtest
+    cerebro.run()
+
+    # Print ending conditions
+    print(f'Ending Portfolio Value: {cerebro.broker.getvalue():.2f}')
+
+    # Plot the results
+    cerebro.plot()
+
+if __name__ == "__main__":
+    symbol = 'BTC/USDT'
+    start_date = '2023-06-20'
+    end_date = '2024-06-20'
+
+    for strategy in [RsiBollingerBandsStrategy]:
+        run_backtest(strategy, symbol, start_date, end_date)
+
+    try:
+        data = fetch_data(symbol, start_date, end_date)
+        print(data.head())  
+    except Exception as e:
+        print(f"Error running backtest: {e}")