Monte Carlo Simulation – Topic Guide

Pricing a financial instrument is not an exact science. There may be formulae, mathematics, derivation, proofs and exact models but in essence pricing financial securities in real-world markets is more along the lines of a science of approximation.

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One approach to pricing these instruments is to use a Monte Carlo Simulator. A simulation is an experiment, and a MC simulator may be considered a machine that can churn out a series of experiments. The simulator will behave in a certain fashion (i.e. produce symmetric, asymmetric, normal and skewed, with thin tails or long fat tails) depending on the tool used to build the machine (i.e. the choice of distribution).


EXCEL files

The Monte Carlo Simulation course pre-packaged deal includes 3 EXCEL files.The files contain:

    1. Simulated prices generated using Black Schole’s Terminal Price formula St=S0*exp[(r-q-0.5σ2)t+σ√tzt]
    2. Random numbers, zts, obtained by normally scaling Excel’s RAND() function NORMINV(RAND())
    3. A path of prices, St, for 10 time steps, up to and including the Terminal price, ST
    4. Terminal Prices for 25 different scenarios using Excel’s DATA Table functionality
    5. Average Terminal Price across the 25 scenarios

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