I am looking for a bit of advice. I have recently used to a new firm, which uses Value at Risk in a manner that is unfamiliar from previous places I have worked that I find less than ideal.
Previous, I have seen it used as a simple desk level tool as a basic measue of risk to translate across strategies/assets/instruments, as often as not used as the denominator in a reward/risk ratio for trade sizing or two allocate scarce risk capital. For this purpose it needs to (a) have a universal definition (holding period,confidence) across assets and (b) to have confidence limits high enough to be simply and robusts back tested (c) be of parametric form to cut out any historical idiosyncracies. Regulatory calcs were often done by a more refined method.
At the new place, they use purely historcal calculations, exactly the same methodology as used for regulatory submissions andares completely unfiltered with a database that is configurable in terms of confidence limits, historical periods etc.
There is a tendency to use really tailish confidence limits (e.g. 99.5%) and long holding periods (10 day etc.).
As you can imagine this leads some noisy, less meaningful calculations when used to time series which are short, or particularly trending or have huge shock events.
For instance, for linear positions, long and short positions can have drastically different VaR consumptions, at odds to how much margin the exchanges would demand for the two positions. To address some of the postions some risk managers use idiosyncratic defintions by asset/instrument etc. This to me undermines the usefulness of the numbers severely.
So my question is, is there a frequently referenced method to convert historical methods to treat forward price dynamics as risk neutral/martingale (e.g. to moderate the differences between long and short linear positions). There is such a deep literature on VaR that I would have thought a quick google would find that quickly. I may be missing something obvious but couldn't see this.