Risk Management: In the Eye of the Storm
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After VaR: Q&A with Ron Papanek
December 15, 2010
STM: Then, there’s liquidity risk.
RP: There’s asset liquidity and there’s funding liquidity.
Asset liquidity means or refers specifically to your ability to liquidate your assets. In other words, what I need to sell to convert your assets into cash.
Funding liquidity is a separate category and what that has to do with is whether you have access to capital to fund your liabilities or your ongoing operations. And if you have a line of credit and that gets drawn upon, your liquidity is decreasing.
STM: Which matters most?
RP: The liquidity that is probably most relevant for what we’re talking about here is asset liquidity.
STM: How do you assess that?
RP: You can look at trade-level data to identify for example, what’s the trade volume, open interest, bid-offer spread; all that gives you some idea of your ability to liquidate an asset.
I would say that asset managers generally have a good subjective view or opinion on liquidity. Unfortunately, there are not a lot of good systems.
STM: Why is that?
RP: For two reasons: one, it’s a complicated mathematical problem. The other reason is that the instrument types that have the biggest liquidity problems are those which there’s very little data for. If I have some type of exotic derivative or some type of debt that I want to sell, there’s no market for it and essentially there’s no market data to be used to calculate the liquidity.
STM: All right, so let’s come back to VaR itself. What do you think has been learned about VaR over the last couple of years? Do you think it still should be the primary way for valuing risk in a portfolio of assets?
RP: First of all, VaR is one component of risk analysis. Whether it’s the primary, secondary or whatever it is, I’m not going to argue that point. That’s not the issue. What I would change is the user base. VaR is not the problem; the problem is the incorrect usage of VaR.
STM: What do you mean?
RP: Here’s a report that I got from a company that I won’t name, but it says “Our data shows there have already been nine exceedances of 99 percent normal Value-at-Risk on the Dow.” Okay, by definition if you have nine exceedances of 99 percent VaR (in a three-month period) it means you’re not calculating your VaR right.
If you’re using the data you need to know when your model is not working properly. And by the way, it doesn’t mean the model is not working; maybe it just means the data is not incorporated correctly or the model is not being flexible enough or you’re not changing parameters.
I mean, if I flipped a coin 50 times and I got heads 50 times in a row, I’m gonna look at the other side of the coin.
STM: [ LAUGHS]
RP: I’m willing to bet there’s two heads.
RP: And so the problem with VAR has to do with the usage, not with the framework.
STM: So in effect, I guess your answer to the question, “What comes after VaR?” is other tools. Life goes on with VaR, just with a broader set of tools.
RP: Value at Risk is a useful analytical framework. But let’s not try to get too much out of it; let’s get out of it what we can get out of it. We should also incorporate other risk measures.