abaquant.visualization.options

Import path: abaquant.visualization.options

Domain: Matplotlib and Plotly visualization helpers with shared themes.

Purpose

Configurable visualizations for scalar option-pricing model objects.

When to use it

Use these functions to inspect model behavior, portfolio allocations, market surfaces, credit assessments, calibrations, and dashboard outputs.

Public objects

  • function: visualize_option_model — Visualize one scalar option-pricing model using the active theme.

  • function: visualize_derivative_scenario_grid — Visualize a derivative spot–volatility scenario grid.

  • function: visualize_option_chain_analytics — Visualize listed-option-chain analytics with the active theme.

  • function: visualize_option_strategy — Visualize a composable option strategy payoff profile.

  • function: visualize_calibration_result — Visualize an option-model calibration result.

Detailed reference

Configurable visualizations for scalar option-pricing model objects.

abaquant.visualization.options.visualize_option_model(model, *, option_type='call', chart='payoff', backend=None, theme=None, save_path=None, filename=None, lower_spot_multiple=0.5, upper_spot_multiple=1.5, grid_size=101, lower_volatility_multiple=0.5, upper_volatility_multiple=1.5, volatility_grid_size=31, greek_scale='raw')

Visualize one scalar option-pricing model using the active theme.

Parameters:

  • model (object) – Scalar model exposing spot_price and strike_price. Value charts require call_price() and put_price(). Greek charts additionally require greeks().

  • option_type ({"call", "put"}, default="call") – Vanilla payoff, value, decomposition, and Greek family to display.

  • chart (str, default="payoff") – Requested visual diagnostic. Supported values are "payoff", "price_profile", "extrinsic_value", "greeks", "volatility_smile", "tree", "price_surface", "extrinsic_surface", "delta_surface", "gamma_surface", "theta_surface", and "vega_surface".

  • backend ({"matplotlib", "plotly"}, optional) – Per-call backend override. When omitted, theme.backend is used.

  • theme (VisualizationTheme, optional) – Per-call style and export override. When omitted, the global theme is used.

  • save_path (str or pathlib.Path, optional) – Explicit export path. A filename extension selects the export format.

  • filename (str, optional) – Filename relative to theme.save_directory.

  • lower_spot_multiple (float, default=0.5, 1.5) – Spot-grid bounds expressed as multiples of the strike price.

  • upper_spot_multiple (float, default=0.5, 1.5) – Spot-grid bounds expressed as multiples of the strike price.

  • grid_size (int, default=101) – Number of spot points for curves and the surface x-axis.

  • lower_volatility_multiple (float, default=0.5, 1.5) – Volatility-grid bounds expressed as multiples of the model’s base volatility-like attribute.

  • upper_volatility_multiple (float, default=0.5, 1.5) – Volatility-grid bounds expressed as multiples of the model’s base volatility-like attribute.

  • volatility_grid_size (int, default=31) – Number of volatility points for surface charts.

  • greek_scale ({"raw", "standardized"}, default="raw") – Scaling mode for the multi-Greek curve chart. "standardized" divides each Greek by its maximum absolute value over the spot grid.

Returns:

Styled backend-native figure object. The figure is optionally saved but is never shown automatically.

Return type:

matplotlib.figure.Figure or plotly.graph_objects.Figure

abaquant.visualization.options.visualize_derivative_scenario_grid(scenario_grid, *, metric='price', chart='surface', backend=None, theme=None, save_path=None, filename=None)

Visualize a derivative spot–volatility scenario grid.

Parameters:

  • scenario_grid (object) – Object exposing a long-form data DataFrame with spot_price, volatility, and the selected metric column.

  • metric (str, default="price") – Scenario metric to display.

  • chart ({"surface", "heatmap", "curves"}, default="surface") – Visual form for the scenario table.

  • backend ({"matplotlib", "plotly"}, optional) – Per-call backend override.

  • theme (VisualizationTheme, optional) – Per-call style override.

  • save_path (str or pathlib.Path, optional) – Explicit export path.

  • filename (str, optional) – Filename relative to the active theme’s save directory.

Returns:

Backend-native figure object.

Return type:

matplotlib.figure.Figure or plotly.graph_objects.Figure

abaquant.visualization.options.visualize_option_chain_analytics(analytics, *, chart='iv_smile', option_type='call', metric='implied_volatility', backend=None, theme=None, save_path=None, filename=None, **kwargs)

Visualize listed-option-chain analytics with the active theme.

Parameters:

  • analytics (object) – Option-chain analytics object exposing iv_smile, iv_surface, term_structure, rich_cheap_table, and open_interest_grid.

  • chart ({"iv_smile", "iv_surface", "term_structure", "rich_cheap", "open_interest_heatmap"}, default="iv_smile") – Chain diagnostic to render.

  • option_type ({"call", "put"}, default="call") – Option family used by diagnostics that accept an option-family filter.

  • metric (str, default="implied_volatility") – Metric displayed by surface charts.

  • backend ({"matplotlib", "plotly"}, optional) – Per-call backend override.

  • theme (VisualizationTheme, optional) – Per-call style override.

  • save_path (str or pathlib.Path, optional) – Explicit output path.

  • filename (str, optional) – Filename relative to the active theme save directory.

  • **kwargs (object) – Additional keyword arguments forwarded to the requested analytic table.

Returns:

Backend-native figure object.

Return type:

matplotlib.figure.Figure or plotly.graph_objects.Figure

abaquant.visualization.options.visualize_option_strategy(strategy, *, chart='payoff', backend=None, theme=None, save_path=None, filename=None, spot_min=None, spot_max=None, points=501)

Visualize a composable option strategy payoff profile.

Parameters:

  • strategy (object) – Strategy object exposing profile(...) and break_even_points().

  • chart ({"payoff", "components"}, default="payoff") – "payoff" plots aggregate net profit. "components" also plots each leg’s net profit contribution.

  • backend ({"matplotlib", "plotly"}, optional) – Backend override.

  • theme (VisualizationTheme, optional) – Per-call style override.

  • save_path (str or pathlib.Path, optional) – Explicit export path.

  • filename (str, optional) – Filename relative to the active theme’s save directory.

  • spot_min (float, optional) – Terminal-price grid bounds.

  • spot_max (float, optional) – Terminal-price grid bounds.

  • points (int, default=501) – Number of grid points for the payoff table.

Returns:

Backend-native figure object.

Return type:

matplotlib.figure.Figure or plotly.graph_objects.Figure

abaquant.visualization.options.visualize_calibration_result(calibration_result, *, chart='model_vs_market', backend=None, theme=None, save_path=None, filename=None)

Visualize an option-model calibration result.

Parameters:

  • calibration_result (object) – Calibration result exposing model_data and parameter_table().

  • chart ({"model_vs_market", "residuals", "parameters"}, default="model_vs_market") – Diagnostic to render. "model_vs_market" compares the fitted model with observed market values, "residuals" shows fit errors by strike, and "parameters" displays calibrated parameter values.

  • backend ({"matplotlib", "plotly"}, optional) – Per-call backend override.

  • theme (VisualizationTheme, optional) – Per-call style override.

  • save_path (str or pathlib.Path, optional) – Explicit export path.

  • filename (str, optional) – Filename relative to the active theme save directory.

Returns:

Backend-native figure object.

Return type:

matplotlib.figure.Figure or plotly.graph_objects.Figure