""" ferro_ta.analysis.derivatives_payoff — Multi-leg payoff and Greeks aggregation. """ from __future__ import annotations from collections.abc import Mapping, Sequence from dataclasses import dataclass from typing import Any import numpy as np from numpy.typing import ArrayLike, NDArray from ferro_ta._ferro_ta import aggregate_greeks_legs as _rust_aggregate_greeks_legs from ferro_ta._ferro_ta import strategy_payoff_dense as _rust_strategy_payoff_dense from ferro_ta._ferro_ta import strategy_payoff_legs as _rust_strategy_payoff_legs from ferro_ta.analysis.options import OptionGreeks from ferro_ta.analysis.options_strategy import DerivativesStrategy, StrategyLeg from ferro_ta.core.exceptions import ( FerroTAInputError, FerroTAValueError, _normalize_rust_error, ) __all__ = [ "PayoffLeg", "option_leg_payoff", "futures_leg_payoff", "strategy_payoff", "aggregate_greeks", ] @dataclass(frozen=True) class PayoffLeg: instrument: str side: str quantity: float = 1.0 option_type: str | None = None strike: float | None = None premium: float = 0.0 entry_price: float | None = None volatility: float | None = None time_to_expiry: float | None = None rate: float = 0.0 carry: float = 0.0 multiplier: float = 1.0 def __post_init__(self) -> None: if self.instrument not in {"option", "future"}: raise FerroTAValueError("instrument must be 'option' or 'future'.") if self.side not in {"long", "short"}: raise FerroTAValueError("side must be 'long' or 'short'.") if self.instrument == "option": if self.option_type not in {"call", "put"}: raise FerroTAValueError( "option legs require option_type='call' or 'put'." ) if self.strike is None: raise FerroTAValueError("option legs require strike.") if self.instrument == "future" and self.entry_price is None: raise FerroTAValueError("future legs require entry_price.") def _side_sign(side: str) -> float: return 1.0 if side == "long" else -1.0 def _coerce_spot_grid(spot_grid: ArrayLike) -> NDArray[np.float64]: grid = np.asarray(spot_grid, dtype=np.float64) if grid.ndim != 1: raise FerroTAInputError("spot_grid must be a 1-D array.") return np.ascontiguousarray(grid) def option_leg_payoff( spot_grid: ArrayLike, *, strike: float, premium: float = 0.0, option_type: str = "call", side: str = "long", quantity: float = 1.0, multiplier: float = 1.0, ) -> NDArray[np.float64]: """Expiry payoff for a single option leg.""" grid = _coerce_spot_grid(spot_grid) _side_sign(side) if option_type not in {"call", "put"}: raise FerroTAValueError("option_type must be 'call' or 'put'.") return np.asarray( _rust_strategy_payoff_dense( grid, np.array([0], dtype=np.int64), # option np.array([1 if side == "long" else -1], dtype=np.int64), np.array([1 if option_type == "call" else -1], dtype=np.int64), np.array([float(strike)], dtype=np.float64), np.array([float(premium)], dtype=np.float64), np.array([0.0], dtype=np.float64), np.array([float(quantity)], dtype=np.float64), np.array([float(multiplier)], dtype=np.float64), ), dtype=np.float64, ) def futures_leg_payoff( spot_grid: ArrayLike, *, entry_price: float, side: str = "long", quantity: float = 1.0, multiplier: float = 1.0, ) -> NDArray[np.float64]: """P/L profile for a futures leg.""" grid = _coerce_spot_grid(spot_grid) _side_sign(side) return np.asarray( _rust_strategy_payoff_dense( grid, np.array([1], dtype=np.int64), # future np.array([1 if side == "long" else -1], dtype=np.int64), np.array([-1], dtype=np.int64), np.array([0.0], dtype=np.float64), np.array([0.0], dtype=np.float64), np.array([float(entry_price)], dtype=np.float64), np.array([float(quantity)], dtype=np.float64), np.array([float(multiplier)], dtype=np.float64), ), dtype=np.float64, ) def _mapping_to_leg(mapping: Mapping[str, Any]) -> PayoffLeg: return PayoffLeg(**mapping) def _strategy_leg_to_payoff_leg(leg: StrategyLeg) -> PayoffLeg: return PayoffLeg( instrument=leg.instrument, side=leg.side, quantity=float(leg.quantity), option_type=leg.option_type, strike=leg.strike_selector.explicit_strike, ) def _normalize_legs( legs: Sequence[PayoffLeg | Mapping[str, Any]] | None = None, *, strategy: DerivativesStrategy | None = None, ) -> tuple[PayoffLeg, ...]: if strategy is not None: return tuple(_strategy_leg_to_payoff_leg(leg) for leg in strategy.legs) if legs is None: raise FerroTAInputError("Provide either legs or strategy.") normalized: list[PayoffLeg] = [] for leg in legs: normalized.append(leg if isinstance(leg, PayoffLeg) else _mapping_to_leg(leg)) return tuple(normalized) def strategy_payoff( spot_grid: ArrayLike, *, legs: Sequence[PayoffLeg | Mapping[str, Any]] | None = None, strategy: DerivativesStrategy | None = None, ) -> NDArray[np.float64]: """Aggregate expiry payoff across option and futures legs.""" grid = _coerce_spot_grid(spot_grid) normalized = _normalize_legs(legs, strategy=strategy) if len(normalized) == 0: return np.zeros_like(grid) try: return np.asarray( _rust_strategy_payoff_legs(grid, normalized), dtype=np.float64 ) except ValueError as err: _normalize_rust_error(err) def aggregate_greeks( spot: float, *, legs: Sequence[PayoffLeg | Mapping[str, Any]] | None = None, strategy: DerivativesStrategy | None = None, ) -> OptionGreeks: """Aggregate Greeks across option and futures legs.""" normalized = _normalize_legs(legs, strategy=strategy) if len(normalized) == 0: return OptionGreeks(0.0, 0.0, 0.0, 0.0, 0.0) try: delta, gamma, vega, theta, rho = _rust_aggregate_greeks_legs( float(spot), normalized ) except ValueError as err: _normalize_rust_error(err) return OptionGreeks( float(delta), float(gamma), float(vega), float(theta), float(rho), )