| name | visualization |
| description | Creates financial charts and visualizations. Supports candlestick charts, equity curves, indicator overlays, correlation heatmaps, and distribution plots. Trigger when the user wants to visualize financial data or trading results. |
| metadata | {"hermes":{"tags":["visualization","charts","plotting","finance","matplotlib"],"category":"analysis","requires_toolsets":["terminal"]}} |
Visualization
Creates financial charts using matplotlib/mplfinance.
Real Code Reference
tradinglearn/backtest/backtester.py — plot_results() shows price vs portfolio overlay with buy/sell markers
tradinglearn/utils/parameter_optimizer.py — plot_optimization_results() generates 4-panel heatmap figure
Chart Types
- Price charts: candlestick (mplfinance), OHLC, line, area
- Indicator overlays: MACD subplot, RSI panel, Bollinger Bands on price
- Performance: equity curve, drawdown chart, rolling returns
- Analysis: correlation heatmap, return distribution histogram, scatter matrix
- Comparison: multi-stock overlay, benchmark vs strategy
Usage
from backtest.backtester import Backtester
bt = Backtester()
bt.run_backtest(data, strategy, params)
bt.plot_results()
For custom charts:
import matplotlib.pyplot as plt
fig, axes = plt.subplots(2, 1, figsize=(12, 8))
axes[0].plot(portfolio['date'], portfolio['portfolio_value'])
axes[1].bar(trade_log['exit_date'], trade_log['pnl'])