Trading days are numbered from 1 to 24, where the number 1 is 13.10.2008 and the 24 is 13.11.2008 All the index values for our calculation in the contract payoff (except ) are taken as the closing prices for specified date. - being accounted as values of i-th index the opening of the market on 13.10.2008 Theoretical background Monte Carlo simulation In finance, there is an amount of uncertainty and risk relative with estimating the future value of figures due to the wide variety of potential outcomes. Monte Carlo simulation is one technique that helps to simplify the model with uncertainty involved in estimating future outcomes. Monte Carlo simulation can be applied to complex, non-linear models or used to evaluate the accuracy and performance of other models. To apply Monte Carlo simulation to estimate a financial value, there are typically three steps: generating sample paths, evaluating the payoff along each path and calculating an average to obtain estimation. For example: For a risk-neutral environment, the value of the derivative security is the discounted value of its future date cash flow: . Monte Carlo simulation approximates the expectation of the derivative’s future cash flows with one simple arithmetic average of cash flows taken over a finite number of simulated price path:
Trading days are numbered from 1 to 24, where the number 1 is 13.10.2008 and the 24 is 13.11.2008 All the index values for our calculation in the contract payoff (except ) are taken as the closing prices for specified date. - being accounted as values of i-th index the opening of the market on 13.10.2008 Theoretical background Monte Carlo simulation In finance, there is an amount of uncertainty and risk relative with estimating the future value of figures due to the wide variety of potential outcomes. Monte Carlo simulation is one technique that helps to simplify the model with uncertainty involved in estimating future outcomes. Monte Carlo simulation can be applied to complex, non-linear models or used to evaluate the accuracy and performance of other models. To apply Monte Carlo simulation to estimate a financial value, there are typically three steps: generating sample paths, evaluating the payoff along each path and calculating an average to obtain estimation. For example: For a risk-neutral environment, the value of the derivative security is the discounted value of its future date cash flow: . Monte Carlo simulation approximates the expectation of the derivative’s future cash flows with one simple arithmetic average of cash flows taken over a finite number of simulated price path:
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