10 Bootstrapping v Simulation.pdf - Excel Modeling VBA Simulations and Monte Carlo Methods Dr Ronald K CHUNG FINA0404/3351 – Spreadsheet Modelling in

# 10 Bootstrapping v Simulation.pdf - Excel Modeling VBA...

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Excel Modeling: VBA Simulations and Monte Carlo Methods Dr. Ronald K. CHUNG FINA0404/3351 Spreadsheet Modelling in Finance

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Simulating Stock Prices, (Ch 11, S) Simulation Random number generation Understanding/Testing a relationship Testing the result Project… Simulation v. Bootstrapping Monte Carlo Runs
Simulation Simulating the price of an asset = generating price paths that it may follow in the future … guessing , but based on parameters (inputs), and see what potential results look like Best when: there exists a degree of uncertainty around point estimates, e.g., stock price (draw values from the distribution multiple times, e.g., 10,000)

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Simulation Consider a stock, P0 = \$20 and trades only once a day => A simple rule: every day, its price can either go up or down by \$1 with equal probability .
Simulation: probability If the price of a stock were predictable, = only one possible future price path, no need to simulate. If a stock’s price is not constrained by any rule, = unlimited price path meaningless to simulate Simulate stock prices only because future stock prices are uncertain (i.e., stochastic), but we believe they follow a set of rules (probabilities) that can be derive from historical data / other knowledge (e.g., distribution) of stock prices. This set of rules is called the model for stock prices.

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