What are the pros and cons of historial and Gaussian approaches to VaR?

Question

What is the difference between historical and Gaussian method of VaR estimation?

I know how they are calculated, but what are the pros and cons of each?

Have you tried searching for this? There is a lot of info out there. — AfterWorkGuinness, Oct 27 '15 at 19:11

AfterWorkGuinness · Accepted Answer · 2015-10-28 03:00:58Z

3

Historical Simulation

Pros:

Easy to calculate
Doesn't make assumptions about distribution of returns (uses empirical distribution)
Can add some enhancements onto it such as giving a higher weighting to more recent returns (prevents ghosting mentioned below) or a weighting by volatility where more volatile returns get a higher weight.

Cons:

Assumes the past will repeat itself, doesn't consider events that it has not seen before
If you use the most basic historical simulation approach, as your historical window shifts, large losses or returns at the edge of the window will no longer be in your data-set and can cause a significant jump in the Var (this is called ghosting) which in very undesirable

Guassian/Parametric/Delta Normal/Variance-Covariance (has many names)

Pros:

Relatively easy to calculate (more work than historical, but less compared to monte carlo)

Cons:

Assumes returns are normally distributed, which is often incorrect
Assumes delta sensitivity accounts for all the risk
Very inaccurate for non-linear positions like options (because of above point re delta)
Need to compute an NxN covariance matrix for the portfolio.

answered Oct 27 '15 at 19:24

AfterWorkGuinness

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$\begingroup$ which one is used the most? monte carlo? $\endgroup$
– luka5z
Oct 27 '15 at 19:29
1

$\begingroup$ No idea sorry. If I had to make an educated guess, historical as it is the least data and process intensive. $\endgroup$
– AfterWorkGuinness
Oct 27 '15 at 19:32
$\begingroup$ Thanks anyway! Maybe some praticioner will input something $\endgroup$
– luka5z
Oct 27 '15 at 20:05
$\begingroup$ But guys: in usual Monte Carlo approaches: what do you do? Estimate a covariance from historical data and sample Gaussians. There are more sophisticated approaches but in the basic case: what is the difference? $\endgroup$
– Ric
Oct 28 '15 at 9:13
$\begingroup$ Monte Carlo simulation is quite different. Here are a couple of posts on the topic: quant.stackexchange.com/questions/17910/… and quant.stackexchange.com/questions/12592/… $\endgroup$
– AfterWorkGuinness
Oct 28 '15 at 16:37

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