Computational Finance: Building Monte Carlo (MC) Simulators in Excel
Option Pricing – Building Monte Carlo Simulators in Excel for pricing vanilla & Exotic Options
My first interaction with a Monte Carlo simulation was not a very pleasant experience. It was a exam problem based on a difficult text book and an even more incomprehensible study note that I had hardly understood. But over the years great teachers like Mark Broadie, friends like Carlos Desmaras and students at SP Jain and Alchemy platforms finally helped me crack the code behind Monte Carlo Simulations.
This note starts with the basic concepts and ends with some fairly complex applications of Monte Carlo Simulations tools. The interest rate modeling piece is covered with a downloadable pdf file that Mark shared with us at Columbia as part of his course on Security pricing. Irrespective of how much I grow and write and teach it will be difficult for me to beat the simple elegance of his 10 pages on interest rate modelling.
- Computational Finance: Monte-Carlo (MC) Simulation method– Building Equities, Commodities, Currencies and Interest Rate MC Simulators in Excel
- Computational Finance: Building your first Monte Carlo (MC) simulator model for simulated equity prices in Excel
- Computational Finance: Monte Carlo (MC) Simulation method: Understanding drift, diffusion and volatility drag
- Computational Finance: Linking Monte Carlo Simulation, Binomial Trees and Black Scholes Equation
Simulation Interest Rates using Monte Carlo Simulation in Excel
- Computational Finance: Simulating Interest Rates using trees and Monte Carlo Simulation
- Computational Finance – Calibrating the Cox, Ingersoll, Ross (CIR) Interest Rate Simulator
- Computational Finance – US Treasury Curve Data – Principal Component Analysis (PCA) process, data and volatility function
- Computational Finance: Interest Rate Modeling: PCA analysis for HJM Interest Rate Simulation and calculating Eigenvectors in Excel