Repository to store homework for FE 621 (Computational Methods in Finance) taught by Professor Ionut Florescu at the Steven Institute of Technology in Spring Semester 2019.

• Asian (i.e. average value) Equity Options: https://github.com/rukmal/FE-621-Homework/tree/master/fe621/black_scholes/asian
• Barrier Equity Options: https://github.com/rukmal/FE-621-Homework/tree/master/fe621/black_scholes/barrier
• Vanilla Equity Options: https://github.com/rukmal/FE-621-Homework/tree/master/fe621/black_scholes
• Vanilla Greeks: https://github.com/rukmal/FE-621-Homework/blob/master/fe621/black_scholes/greeks.py
• Vanilla Parity: https://github.com/rukmal/FE-621-Homework/blob/master/fe621/black_scholes/parity.py

Note: All option pricing functions are under the Black Scholes model heuristic.

• General Simulation Driver: https://github.com/rukmal/FE-621-Homework/blob/master/fe621/monte_carlo/monte_carlo.py
• Simple Geometric Brownian Motion Equity Option Pricing: https://github.com/rukmal/FE-621-Homework/blob/master/fe621/monte_carlo/option_pricing/simple_gbm.py
• Delta-Based Control Variates Method Variance-Reduced Equity Option Pricing: https://github.com/rukmal/FE-621-Homework/blob/master/fe621/monte_carlo/option_pricing/control_variates.py
• Antithetic Variates Method Variance-Reduced Equity Option Pricing: https://github.com/rukmal/FE-621-Homework/blob/master/fe621/monte_carlo/option_pricing/antithetic_variates.py
• Antithetic Variates Delta-Based Control Variates Method Variance-Reduced Equity Option Pricing: https://github.com/rukmal/FE-621-Homework/blob/master/fe621/monte_carlo/option_pricing/antithetic_control_variates.py

• Numerical Differentiation: https://github.com/rukmal/FE-621-Homework/tree/master/fe621/numerical_differentiation
• Simpson's Quadrature Rule (Numerical Integration): https://github.com/rukmal/FE-621-Homework/blob/master/fe621/numerical_integration/simpsons.py
• Trapezoidal Quadrature Rule (Numerical Integration): https://github.com/rukmal/FE-621-Homework/blob/master/fe621/numerical_integration/trapezoidal.py

• Bisection Method: https://github.com/rukmal/FE-621-Homework/blob/master/fe621/optimization/bisection.py
• Newton's Method: https://github.com/rukmal/FE-621-Homework/blob/master/fe621/optimization/newton.py

Note: All option pricing functions are under the Black Scholes model heuristic.

• General Tree Driver: https://github.com/rukmal/FE-621-Homework/blob/master/fe621/tree_pricing/general_tree.py
• Binomial Trigeorgis Additive Vanilla Option Pricing: https://github.com/rukmal/FE-621-Homework/blob/master/fe621/tree_pricing/binomial/trigeorgis.py
• Binomial Trigeorgis Additive Barrier Option Pricing: https://github.com/rukmal/FE-621-Homework/blob/master/fe621/tree_pricing/binomial/barrier.py
• Trinomial Additive Vanilla Option Pricing: https://github.com/rukmal/FE-621-Homework/blob/master/fe621/tree_pricing/trinomial/trinomial_price.py