3a9dec543c
- Removed unused configuration for daily data and consolidated minute configuration into a single config dictionary. - Updated plotting logic to dynamically handle different strategies, ensuring appropriate bands and signals are displayed based on the selected strategy. - Improved error handling and logging for missing data in plots. - Enhanced the Bollinger Bands and RSI classes to support adaptive parameters based on market regimes, improving flexibility in strategy execution. - Added new CryptoTradingStrategy with multi-timeframe analysis and volume confirmation for better trading signal accuracy. - Updated documentation to reflect changes in strategy implementations and configuration requirements.
146 lines
7.4 KiB
Python
146 lines
7.4 KiB
Python
import logging
|
|
import seaborn as sns
|
|
import matplotlib.pyplot as plt
|
|
import pandas as pd
|
|
|
|
from cycles.utils.storage import Storage
|
|
from cycles.Analysis.strategies import Strategy
|
|
|
|
logging.basicConfig(
|
|
level=logging.INFO,
|
|
format="%(asctime)s [%(levelname)s] %(message)s",
|
|
handlers=[
|
|
logging.FileHandler("backtest.log"),
|
|
logging.StreamHandler()
|
|
]
|
|
)
|
|
|
|
config = {
|
|
"start_date": "2023-01-01",
|
|
"stop_date": "2024-01-01",
|
|
"data_file": "btcusd_1-min_data.csv"
|
|
}
|
|
|
|
config_strategy = {
|
|
"bb_width": 0.05,
|
|
"bb_period": 20,
|
|
"rsi_period": 14,
|
|
"trending": {
|
|
"rsi_threshold": [30, 70],
|
|
"bb_std_dev_multiplier": 2.5,
|
|
},
|
|
"sideways": {
|
|
"rsi_threshold": [40, 60],
|
|
"bb_std_dev_multiplier": 1.8,
|
|
},
|
|
"strategy_name": "MarketRegimeStrategy",
|
|
"SqueezeStrategy": True
|
|
}
|
|
|
|
IS_DAY = False
|
|
|
|
if __name__ == "__main__":
|
|
|
|
# Load data
|
|
storage = Storage(logging=logging)
|
|
data = storage.load_data(config["data_file"], config["start_date"], config["stop_date"])
|
|
|
|
# Run strategy
|
|
strategy = Strategy(config=config_strategy, logging=logging)
|
|
processed_data = strategy.run(data.copy(), config_strategy["strategy_name"])
|
|
|
|
# Get buy and sell signals
|
|
buy_condition = processed_data.get('BuySignal', pd.Series(False, index=processed_data.index)).astype(bool)
|
|
sell_condition = processed_data.get('SellSignal', pd.Series(False, index=processed_data.index)).astype(bool)
|
|
|
|
buy_signals = processed_data[buy_condition]
|
|
sell_signals = processed_data[sell_condition]
|
|
|
|
# Plot the data with seaborn library
|
|
if processed_data is not None and not processed_data.empty:
|
|
# Create a figure with two subplots, sharing the x-axis
|
|
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(16, 8), sharex=True)
|
|
|
|
strategy_name = config_strategy["strategy_name"]
|
|
|
|
# Plot 1: Close Price and Strategy-Specific Bands/Levels
|
|
sns.lineplot(x=processed_data.index, y='close', data=processed_data, label='Close Price', ax=ax1)
|
|
if strategy_name == "MarketRegimeStrategy":
|
|
if 'UpperBand' in processed_data.columns and 'LowerBand' in processed_data.columns:
|
|
sns.lineplot(x=processed_data.index, y='UpperBand', data=processed_data, label='Upper Band (BB)', ax=ax1)
|
|
sns.lineplot(x=processed_data.index, y='LowerBand', data=processed_data, label='Lower Band (BB)', ax=ax1)
|
|
else:
|
|
logging.warning("MarketRegimeStrategy: UpperBand or LowerBand not found for plotting.")
|
|
elif strategy_name == "CryptoTradingStrategy":
|
|
if 'UpperBand_15m' in processed_data.columns and 'LowerBand_15m' in processed_data.columns:
|
|
sns.lineplot(x=processed_data.index, y='UpperBand_15m', data=processed_data, label='Upper Band (15m)', ax=ax1)
|
|
sns.lineplot(x=processed_data.index, y='LowerBand_15m', data=processed_data, label='Lower Band (15m)', ax=ax1)
|
|
else:
|
|
logging.warning("CryptoTradingStrategy: UpperBand_15m or LowerBand_15m not found for plotting.")
|
|
if 'StopLoss' in processed_data.columns:
|
|
sns.lineplot(x=processed_data.index, y='StopLoss', data=processed_data, label='Stop Loss', ax=ax1, linestyle='--', color='orange')
|
|
if 'TakeProfit' in processed_data.columns:
|
|
sns.lineplot(x=processed_data.index, y='TakeProfit', data=processed_data, label='Take Profit', ax=ax1, linestyle='--', color='purple')
|
|
|
|
# Plot Buy/Sell signals on Price chart
|
|
if not buy_signals.empty:
|
|
ax1.scatter(buy_signals.index, buy_signals['close'], color='green', marker='o', s=10, label='Buy Signal', zorder=5)
|
|
if not sell_signals.empty:
|
|
ax1.scatter(sell_signals.index, sell_signals['close'], color='red', marker='o', s=10, label='Sell Signal', zorder=5)
|
|
ax1.set_title(f'Price and Signals ({strategy_name})')
|
|
ax1.set_ylabel('Price')
|
|
ax1.legend()
|
|
ax1.grid(True)
|
|
|
|
# Plot 2: RSI and Strategy-Specific Thresholds
|
|
rsi_col_name = 'RSI' if strategy_name == "MarketRegimeStrategy" else 'RSI_15m'
|
|
if rsi_col_name in processed_data.columns:
|
|
sns.lineplot(x=processed_data.index, y=rsi_col_name, data=processed_data, label=f'{rsi_col_name} (' + str(config_strategy.get("rsi_period", 14)) + ')', ax=ax2, color='purple')
|
|
if strategy_name == "MarketRegimeStrategy":
|
|
# Assuming trending thresholds are what we want to show generally
|
|
ax2.axhline(config_strategy.get("trending", {}).get("rsi_threshold", [30,70])[1], color='red', linestyle='--', linewidth=0.8, label=f'Overbought (' + str(config_strategy.get("trending", {}).get("rsi_threshold", [30,70])[1]) + ')')
|
|
ax2.axhline(config_strategy.get("trending", {}).get("rsi_threshold", [30,70])[0], color='green', linestyle='--', linewidth=0.8, label=f'Oversold (' + str(config_strategy.get("trending", {}).get("rsi_threshold", [30,70])[0]) + ')')
|
|
elif strategy_name == "CryptoTradingStrategy":
|
|
ax2.axhline(65, color='red', linestyle='--', linewidth=0.8, label='Overbought (65)') # As per Crypto strategy logic
|
|
ax2.axhline(35, color='green', linestyle='--', linewidth=0.8, label='Oversold (35)') # As per Crypto strategy logic
|
|
|
|
# Plot Buy/Sell signals on RSI chart
|
|
if not buy_signals.empty and rsi_col_name in buy_signals.columns:
|
|
ax2.scatter(buy_signals.index, buy_signals[rsi_col_name], color='green', marker='o', s=20, label=f'Buy Signal ({rsi_col_name})', zorder=5)
|
|
if not sell_signals.empty and rsi_col_name in sell_signals.columns:
|
|
ax2.scatter(sell_signals.index, sell_signals[rsi_col_name], color='red', marker='o', s=20, label=f'Sell Signal ({rsi_col_name})', zorder=5)
|
|
ax2.set_title(f'Relative Strength Index ({rsi_col_name}) with Signals')
|
|
ax2.set_ylabel(f'{rsi_col_name} Value')
|
|
ax2.set_ylim(0, 100)
|
|
ax2.legend()
|
|
ax2.grid(True)
|
|
else:
|
|
logging.info(f"{rsi_col_name} data not available for plotting.")
|
|
|
|
# Plot 3: Strategy-Specific Indicators
|
|
ax3.clear() # Clear previous plot content if any
|
|
if strategy_name == "MarketRegimeStrategy":
|
|
if 'BBWidth' in processed_data.columns:
|
|
sns.lineplot(x=processed_data.index, y='BBWidth', data=processed_data, label='BB Width', ax=ax3)
|
|
if 'MarketRegime' in processed_data.columns:
|
|
sns.lineplot(x=processed_data.index, y='MarketRegime', data=processed_data, label='Market Regime (Sideways: 1, Trending: 0)', ax=ax3)
|
|
ax3.set_title('Bollinger Bands Width & Market Regime')
|
|
ax3.set_ylabel('Value')
|
|
elif strategy_name == "CryptoTradingStrategy":
|
|
if 'VolumeMA_15m' in processed_data.columns:
|
|
sns.lineplot(x=processed_data.index, y='VolumeMA_15m', data=processed_data, label='Volume MA (15m)', ax=ax3)
|
|
if 'volume' in processed_data.columns: # Plot original volume for comparison
|
|
sns.lineplot(x=processed_data.index, y='volume', data=processed_data, label='Volume (15m)', ax=ax3, alpha=0.5)
|
|
ax3.set_title('Volume Analysis (15m)')
|
|
ax3.set_ylabel('Volume')
|
|
|
|
ax3.legend()
|
|
ax3.grid(True)
|
|
|
|
plt.xlabel('Date')
|
|
fig.tight_layout()
|
|
plt.show()
|
|
else:
|
|
logging.info("No data to plot.")
|
|
|