Monte Carlo method: Difference between revisions
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Revision as of 14:12, 9 October 2013
In Value at Risk analysis, an alternative method for calculating the probability distribution (rather than using the Delta-normal method or the Historical simulation method).
Monte Carlo simulations consist of two steps:
- First, a stochastic process for financial variables is specified as well as process parameters.
- Both historical data and appropriate judgement can be used for such parameters as risk and correlations.
- Second, fictitious price paths are simulated for all variables of interest. At each horizon considered, the portfolio is marked-to-market using full valuation.
- A distribution of returns is eventually produced, from which a VaR figure can be measured.
Comparing the methods:
- 1. The Delta-normal method is the simplest method to implement.
- The main drawbacks are the assumption that risk factors have normal distributions, and the assumption that the assets are linear (in other words, that they do not contain options).
- 2. The Historical simulation method is also relatively simple to implement.
- The main drawback is that the historical information used may not adequately represent future probability distributions. (This is also a drawback of the delta-normal method.)
Monte Carlo techniques are designed to address these shortcomings.
Disadvantages of Monte Carlo methods include their relative complexity.