src/option_implied_lab/features.py

from __future__ import annotations

import numpy as np

from .types import DensityEstimate, OptionSnapshot


def compute_features(
    snapshot: OptionSnapshot, density: DensityEstimate
) -> dict[str, float]:
    k = density.strikes.to_numpy(dtype=float)
    rho = density.density.to_numpy(dtype=float)
    spot = float(snapshot.spot)

    mean_k = float(np.trapezoid(k * rho, k))
    var_k = float(np.trapezoid((k - mean_k) ** 2 * rho, k))
    std_k = float(np.sqrt(max(var_k, 1e-12)))
    skew = float(np.trapezoid(((k - mean_k) / std_k) ** 3 * rho, k))
    tail_mass_left = (
        float(np.trapezoid(rho[k < 0.9 * spot], k[k < 0.9 * spot]))
        if np.any(k < 0.9 * spot)
        else 0.0
    )

    return {
        "spot": spot,
        "mean_terminal": mean_k,
        "std_terminal": std_k,
        "skew_proxy": skew,
        "left_tail_mass": tail_mass_left,
    }