# Tag Archives: Simulating equity prices

## Computational Finance: Simulating Interest Rates using trees and Monte Carlo Simulation

Simulating Interest rates using CIR and HJM While we can club equity, commodity and currency simulators in one category, interest rate simulators are a completely different animal. First because there is more than one way of modeling interest rates Equilibrium models and Arbitrage free models.

## Computational Finance: Linking Monte Carlo Simulation, Binomial Trees and Black Scholes Equation

Linking Monte Carlo Simulation with Binomial Trees and the Black Scholes model A binomial tree uses the same process to generate a path that the Monte Carlo simulation model uses which is also the same model that the Black Scholes solution integrates over an infinitely

## Computational Finance: Monte Carlo (MC) Simulation method: Understanding drift, diffusion and volatility drag

We have introduced our friend mu (u) as drift and sigma as diffusion (or standard deviation or volatility or vol). In the previous session we have also gone out and built a simple excel based Monte Carlo simulation model for generating stock prices. While the

## Extending MC simulation for currencies and commodities.

Extending MC simulation models to Currencies & Commodities Extending the original Monte Carlo (MC) Simulator for Equities to Currencies and Commodities required a few simple changes. Rather than using just r, we now use an adjusted r for the model. In the case of currencies

## Computational Finance: Building your first Monte Carlo (MC) simulator model for simulated equity prices in Excel

Here is a slightly revised model for calculating the change in price of an equity security. We now add one more component to our generator function. While the first term works off expected return the second term will help us model uncertainty. Since in our world we drive and link uncertainly with volatility, our model also uses a factor proportional to volatility.