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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()  # Price chart + portfolio value + buy/sell signals

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'])