Monte Carlo method: Difference between revisions
From ACT Wiki
Jump to navigationJump to search
imported>Doug Williamson (Broaden definition to non-Value at Risk applications.) |
imported>Doug Williamson (Simplify.) |
||
Line 1: | Line 1: | ||
== Monte Carlo methods in VaR analysis == | == Monte Carlo methods in VaR analysis == | ||
Line 15: | Line 14: | ||
:A distribution of returns is eventually produced, from which a VaR figure can be measured. | :A distribution of returns is eventually produced, from which a VaR figure can be measured. | ||
Line 41: | Line 24: | ||
== See also == | == See also == | ||
* [[Stochastic]] | * [[Stochastic]] | ||
* [[Value at risk]] | * [[Value at risk]] | ||
[[Category:Risk_frameworks]] | [[Category:Risk_frameworks]] |
Revision as of 10:35, 19 April 2015
Monte Carlo methods in VaR analysis
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 (random) 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, multiple 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.
Monte Carlo methods in other applications
More generally, Monte Carlo methods are the simulation of multiple fictitious outcomes, using a combination of historical and judgemental parameters and a randomised process.
The name originated from the famous Monte Carlo casino.