by Patrick Burns.
Abstract: The estimation of value at risk using univariate GARCH models is examined. A long history of the S&P 500 is used to compare these estimators with several other common approaches to value at risk estimation. The test results indicate that GARCH estimates are superior to the other methods in terms of the accuracy and consistency of the probability level. Although all of the GARCH models tested performed relatively well, the quality of the value at risk estimate does depend on which particular GARCH model is used. Weighting recent observations more heavily when fitting the GARCH model seems to be beneficial.
jun 25, 26
Online Math Degrees has a page of ”100 savvy sites on statistics and quantitative analysis”. It has some that you recognize, some that you’ve hardly ever heard of. The sites [...]
jun 25, 26
R is a piece of software, but it is also a community. Help community The most visible aspect of the R community is help. This is also the most useful [...]
jun 25, 26
Some history and a prediction. Past A discussion broke out on the R-help mailing list in January 2006 about a technical report put out by the statistical computing group at [...]