visualization

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'])