Monte Carlo Simulation is an extremely useful tool in finance. For example, because we can simulate stock price by drawing random numbers from a lognormal distribution, the famous Black-Scholes-Merton option model can be replicated. From Chapter 9, Portfolio Theory, we have learnt that by adding more stocks into a portfolio, the firm specific risk could be reduced or eliminated. Via simulation, we can see the diversification effect much clearly since we can randomly select 50 stocks from 5,000 stocks repeatedly. For capital budgeting, we can simulate over several dozen variables with uncertain future values. For those cases, simulation can be applied to generate many possible future outcomes, events, and various types of combinations. In this chapter, the following topics will be covered:
Generating random numbers drawn from a normal, uniform, and Poisson distributions
Estimating π value by using Monte Carlo simulation
Simulate stock price movement with a...