Reverse Stress Testing at Quafafew
Just back from a good vacation (London Olympics followed by a sunny week in Portugal – hope your summer has gone well too) and enjoyed a great evening at a Quafafew event on Tuesday evening, entitled “Reverse Stress Testing & Roundtable on Managing Hedge Fund Risk“.
Reverse Stress Testing
The first part of the evening was a really good presentation by Daniel Satchkov of Rixtrema on reverse stress testing. Daniel started the evening by stating his opinion that risk managers should not consider their role as one of trying to predict the future, but rather one more reminiscent of “car crash testing”, where the role of the tester is one of assessing, managing and improving the response of a car to various “impacts”, without needing to understand the exact context of any specific crash such as “Who was driving?”, “Where did the accident take place?” or “Whose fault was it?”. (I guess the historic context is always interesting, but will be no guide to where, when and how the next accident takes place).
Daniel spent some of his presentation discussing the importance of paradigms (aka models) to risk management, which in many ways echos many of themes from the modeller’s manifesto. Daniel emphasised the importance of imagination in risk management, and gave a quick story about a German professor of mathematics who when asked the whereabouts of one of his new students replied that “he didn’t have enough imagination so he has gone off to become a poet”.
In terms of paradigms and how to use them, he gave the example of Brownian motion and described how the probability of all the air in the room moving to just one corner was effectively zero (as evidenced by the lack of oxygen cylinders brought along by the audience). However such extremes were not unusual in market prices, so he noted how Black-Scholes was evidently the wrong model, but when combined with volatility surfaces the model was able to give the right results i.e. “the wrong number in the wrong formula to get the right price.” His point here was that the wrong model is ok so long as you aware of how it is wrong and what its limatations are (might be worth checking out this post containing some background by Dr Yuval Millo about the evolution of the options market).
Daniel said that he disagreed with the premise by Taleb that the range of outcomes was infinite and that as a result all risk managers should just give up and buy and a lottery ticket, however he had some sympathies with Taleb over the use of stable correlations within risk management. His illustration was once again entertaining in quoting a story where a doctor asks a nurse what the temperature is of the patients at a Russian hospital, only to be told that they were all “normal, on average” which obviously is not the most useful medical information ever provided. Daniel emphasised that contrary to what you often read correlations do not always move to one in a crisis, but there are often similarities from one crisis to the next (maybe history not repeating itself but more rhyming instead). He said that accuracy was not really valid or possible in risk management, and that the focus should be on relative movements and relative importance of the different factors assessed in risk.
Coming back to the core theme of reverse stress testing, then Daniel presented a method by which from having categorised certain types of “impacts” a level of loss could be specified and the model would produce a set of scenarios that produce the loss level entered. Daniel said that he had designed his method with a view to producing sets of scenarios that were:
- not missing any key dangers
He showed some of the result sets from his work which illustrated that not all scenarios were “obvious”. He was also critical of addressing key risk factors separately, since hedges against different factors would be likely to work against each other in times of crisis and hedging is always costly. I was impressed by his presentation (both in content and in style) and if the method he described provides a reliable framework for generating a useful range of possible scenarios for a given loss level, then it sounds to me like a very useful tool to add to those available to any risk manager.
Managing Hedge Fund Risk
The second part of the evening involved Herb Blank of S-Network (and Quafew) asking a few questions to Raphael Douady, of Riskdata and Barry Schachter of Woodbine Capital. Raphael was an interesting and funny member of the audience at the Dragon Kings event, asking plenty of challenging questions and the entertainment continued yesterday evening. Herb asked how VaR should be used at hedge funds, to which Raphael said that if he calculated a VaR of 2 and we lost 2.5, he would have been doing his job. If the VaR was 2 and the loss was 10, he would say he was not doing his job. Barry said that he only uses VaR when he thinks it is useful, in particular when the assumptions underlying VaR are to some degree reflected in the stability of the market at the time it is used.
Raphael then took us off on an interesting digression based on human perceptions of probability and statistical distributions. He told the audience that yesterday was his eldest daughter’s birthday and what he wanted was for the members of the audience to write down on paper what was a lower and upper bound of her age to encompass a 99th percentile. As background, Raphael looks like this. Raphael got the results and found that out of 28 entries, the range of ages provided by 16 members of the audience did not cover his daughters age. Of the 12 successful entries (her age was 25) six entries had 25 as the upper bound. Some of the entries said that she was between 18 and 21, which Raphael took to mean that some members of the audience thought that they knew her if they assigned a 99th percentile probability to their guess (they didn’t). His point was that even for Quafafewers (or maybe Quafafewtoomuchers given the results…) then guessing probabilities and appropriate ranges of distributions was not a strong point for many of the human race.
Raphael then went on to illustrate his point above through saying that if you asked him whether he thought the Euro would collapse, then on balance he didn’t think it was very likely that this will happen since he thinks that when forced Germany would ultimately come to the rescue. However if you were assessing the range of outcomes that might fit within the 99th percentile distribution of outcomes, then Raphael said that the collapse of the Euro should be included as a possible scenario but that this possibility was not currently being included in the scenarios used by the major financial institutions. Off on another (related) digression, Raphael said that he compared LTCM with having the best team of Formula 1 drivers in the world that given a F1 track would drive the fastest and win everything, but if forced to drive an F1 car on a very bumpy road this team would be crashing much more than most, regardless of their talent or the capabilities of their vehicle.
Barry concluded the evening by saying that he would speak first, otherwise he would not get chance to given Raphael’s performance so far. Again it was a digression from hedge fund risk management, but he said that many have suggested that risk managers need to do more of what they were already doing (more scenarios, more analysis, more transparency etc). Barry suggested that maybe rather than just doing more he wondered whether the paradigm was wrong and risk managers should be thinking different rather than just more of the same. He gave one specific example of speaking to a structurer in a bank recently and asking given the higher hurdle rates for capital whether the structurer should consider investing in riskier products. The answer from the structurer was the bank was planning to meet about this later that day, so once again it would seem that what the regulators want to happen is not necessarily what they are going to get…