Plots

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Backtide provides many plotting methods to analyze the data or compare the model performances. Descriptions and examples can be found in the API section. Backtide uses the plotly library for plotting. Plotly makes interactive, publication-quality graphs that are rendered using HTML.

Available plots

The plotting functions are split into two groups by what they consume: data plots operate on raw market bars (and indicators / dividends) and are typically used before an experiment to explore the universe; result plots operate on the RunResult / ExperimentResult objects produced by run_experiment and are used to evaluate strategy performance after a run.

Data analysis

Use these to understand the symbols you plan to trade. They take a DataFrame of OHLCV bars (typically returned by query_bars) plus a small set of plot-specific options.

Plot	Description
plot_candlestick	OHLC candlestick chart with optional volume sub-plot.
plot_correlation	Correlation heatmap across symbols.
plot_dividends	Dividend cash-flow timeline.
plot_drawdown	Percentage drawdown from running peak.
plot_price	Price line chart, with optional indicator overlays.
plot_returns	Distribution of period-over-period returns.
plot_seasonality	Average return per calendar bucket (month / weekday / hour).
plot_volatility	Rolling annualised volatility.
plot_volume	Trading volume bar chart.
plot_vwap	Volume-weighted average price line.

In addition, compute_statistics returns a tabular summary (mean / volatility / Sharpe / drawdown / ...) over the same DataFrame inputs — handy as a non-graphical complement to the plots above.

Experiment results

Use these to inspect a finished experiment. They take one or more RunResult objects (returned by run_experiment in result.strategies or by query_strategy_runs).

Plot	Multi-run?	Description
plot_cash_holdings	multi	Per-currency cash balance over time.
plot_mae_mfe	single	Maximum adverse / favourable excursion per trade.
plot_pnl	multi	Cumulative PnL (or relative return) per strategy.
plot_pnl_histogram	multi	Distribution of per-trade PnL.
plot_position_size	single	Per-symbol position size over time.
plot_rolling_returns	multi	Compounded return over a trailing window.
plot_rolling_sharpe	multi	Rolling annualised Sharpe ratio per run.
plot_trade_duration	multi	Distribution of trade holding times.
plot_trade_pnl	multi	Per-trade PnL scatter / bar chart.

Parameters

Apart from the plot-specific parameters, all plots have five parameters in common:

• The title parameter adds a title to the plot. The default value doesn't show any title. Provide a configuration (as dictionary) to customize its appearance, e.g., title=dict(text="Awesome plot", color="red"). Read more in plotly's documentation.

• The legend parameter is used to show/hide, position or customize the plot's legend. Provide a configuration (as dictionary) to customize its appearance (e.g., legend=dict(title="Title for legend", title_font_color="red")) or choose one of the following locations:

  • upper left
  • upper right
  • lower left
  • lower right
  • upper center
  • lower center
  • center left
  • center right
  • center
  • out: Position the legend outside the axis, on the right hand side. This is plotly's default position. Note that this shrinks the size of the axis to fit both legend and axes in the specified figsize.

• The figsize parameter adjust the plot's size.

• The filename parameter is used to save the plot.
• The display parameter determines whether to show or return the plot.

Aesthetics

The plot's aesthetics are controlled through the plots section of the configuration. The default values are:

• template: "plotly" — Plotly template for figure styling.
• palette: Blue-to-teal gradient. Colors cycle when there are more traces than entries. ["rgb(13, 71, 161)", "rgb(2, 136, 209)", "rgb(0, 172, 193)", "rgb(0, 137, 123)", "rgb(56, 142, 60)", "rgb(129, 199, 132)"]
• title_fontsize: 22 — Font size (px) for plot titles.
• label_fontsize: 20 — Font size (px) for axis labels and legends.
• tick_fontsize: 14 — Font size (px) for axis tick labels.

To change these values, set them in your configuration file or programmatically:

from backtide.config import get_config, set_config

cfg = get_config()
cfg.plots.template = "plotly_dark"
cfg.plots.title_fontsize = 28
set_config(cfg)