pyoptmc 0.14.4

A package for pricing OTC options using a vectorized Monte Carlo method.

Monte Carlo Method for Option Pricing

UPDATE: 19th November 2025

    pip install pyoptmc --upgrade

This is a package for pricing path-dependent options using Monte Carlo Simulation under Black-Scholes market dynamics.

This package relies heavily on NumPy for the implementation of vectorization, which significantly boosts algorithm speed. It also uses joblib to implement parallel computation.

Example

import datetime
import pyoptmc as opt
calendar = opt.Calendar()

start_date = datetime.date(2025, 11, 5)
ko_ob_dates = calendar.periodic(start_date, '1M', 13, "next")[1:]

mc = opt.MonteCarlo(100, 1000000)
bs = opt.BlackScholes(0.03, 0, 0.265, 244)
end_date = ko_ob_dates[-1]

dcn = opt.PhoenixProd(
    start_date= start_date,
    end_date = end_date,
    initial_price = 100.0,
    settlement_barrier = 80.0,
    settlement_dates = ko_ob_dates,
    settlement_coupon_rate = 0.15,
    ko_barrier = 100.0,
    ko_ob_dates = ko_ob_dates,
    ki_barrier = 80.0,
    ki_ob_dates = "daily",
    calendar = calendar)

print(dcn.value(start_date, 100.0, True, mc, bs, request_greeks=True))

# {'PV': np.float64(-0.16274331381605528), 'Delta': np.float64(0.2390255106366182), 'Gamma': np.float64(-0.031593825237697534), 'Rho': np.float64(0.020117531945007528), 'Vega': np.float64(-0.23208919587396326), 'Theta': np.float64(0.04311655912199197)}

fcn = opt.PhoenixProd(
    start_date=start_date,
    end_date=end_date,
    initial_price=100.0,
    settlement_barrier=0.0,
    settlement_dates=ko_ob_dates,
    settlement_coupon_rate=0.15,
    ko_barrier=100.0,
    ko_ob_dates=ko_ob_dates,
    ki_barrier=80.0,
    ki_ob_dates=[end_date],
    calendar=calendar)

print(fcn.value(start_date, 100.0, False, mc, bs, request_greeks=True))
# {'PV': np.float64(1.6827002150401873), 'Delta': np.float64(-0.007450531928672407), 'Gamma': np.float64(-0.011540440160383967), 'Rho': np.float64(0.011854131363408455), 'Vega': np.float64(-0.1869648625597277), 'Theta': np.float64(0.017297330302293138)}