Garima Singh

AC211. Module 4 – Class 4 Risk and Performance Measurement

Question 1One of the primary reasons VaR became so popular is that it was developed as a common measure that could be applied to just about any asset class. Additionally, VaR could be regarded a performance measure of how good the organisation was at minimising risk whilst making profits and it was increasingly being perceived as a sign of good governance due to its growing popularity and thus seen to possibly translate into good performance.

The article draws to attention the many flaws of VaR, which will be considered later on, but it did pinpoint on one major benefit of VaR: “VaR may have been a flawed number, but it was the best number anyone had come up with”. Its simplicity made it an accessible and easily understandable measure to a much wider variety of people in the organisation, which only added to it’s widespread acceptance.

However, there were three main apparent flaws of the VaR measure. Firstly by putting a dollar number to it, senior management (who were less sound in their understanding of VaR than risk managers/risk experts) tended to take comfort in a single number rather than scrutinizing signs of changes or observing the measure on a regular basis. Which eventually would lead to a “bubble” because of limiting focus only on a single number. Secondly, VaR benchmarked itself against ‘past’ events, which could be extremely unreliable and misleading because new factors and new environments were extremely important to take into consideration as well – this is known as “future blindness”, where people tend not to be able to anticipate a future they have never personally experienced. Thirdly, the VaR measure ignored the possibility of “fat tails” or “black swans” as N.N.Taleb describes them. For example, VaR only focused on the number that fell within a 99% probability and ignored what could happened the other 1% of the time. The severity of losses/risk that could occur within 1% of the time, which wasn’t accounted for, could be very high.

The COSO paper on developing KRI’s, mentions that “often risks likely to have a significant impact may arise from external sources, such as changes in economic conditions…Thus many organisations discover that relevant KRIs are often based on external data” which supports the previous argument of VaR not using accurate benchmarks.

Therefore, despite VaR drawbacks, many people were in favour for the measure perhaps because of lack of expert knowledge in certain members pf senior management or over-optimistic future expectations along with VaR’s simplistic appearance as a standardized single number.

Question 2The statement more or less supports the fact that VaR numbers could be very useful as diagnostic control tools because they provided a top-level view and also because they were a standardized measure they provided better comparability for senior management.

Garima Singh

Despite having previous knowledge as a trader himself, Dennis Weatherstone supported the VaR measure because “he understood both the limits and the value of VaR” and “It told him things he hadn’t known before. He could use it to help him make judgements about whether the firm should take on additional risk or pull back”.

This indicates that VaR’s conception was initially to give senior managers a more comprehensive, easy-to-understand risk measure and help in decision-making as it did for JPMorgan’s chairman Dennis Weatherstone. And it proved to be quite successful.

Nevertheless, in the following questions, we look further into the increasing dependence on VaR and the clouded judgement that resulted from this.

Question 3The statement describes the institutionalisation of VaR as an industry-wide risk measure. VaR may have increasingly become a more important part of the financial scene because as more and more companies regarded it as “good managerial practice” since other companies were using it too (like a “domino effect” – “I’ll do this because you’re doing it too”).

This widespread acceptance of VaR signalled to more and more people that it was a useful tool in risk measurement. However, it was important to recognise that VaR needed to be complemented along with accurate judgment of the significance of the measure by top management otherwise the information was worthless or even potentially dangerous (misleading). Through the example of Dennis Weatherstone of JPMorgan and Goldman Sachs, we saw in the article that the VaR measure was used to facilitate and reinforce decision-making and not a tool to simply acquire data. This may have been a common mistake among less experienced or less knowledgeable managers that may have led to “bubbles” being created like 2008 housing bubble. Managers may have come to accept VaR as a common standard for risk measurement in the industry but failed to understand that VaR was after all based on a 2-year data history, an aggregated measure and to top it all ignored the fact that VaR only captured 99% probability and ignored the remaining 1% probability.

Nevertheless, as Greg Berman puts it: “If you say that all risk is unknowable, you don’t have the basis of any sort of a bet or a trade…if you spend all your time thinking about black swans, you’ll be so risk averse you’ll never do a trade…to not use VaR is to say that I won’t care about the 99%, in which case you won’t have a business…When you think about disasters, all you can rely on is the disasters of the past. And yet you know that it will be different in the future. How do you plan for that?” Berman’s argument describes the flipside of our VaR situation, and as mentioned before, “it was the best number anyone had come up with”.

This sufficiently provides us with some foundation to understand how VaR came about to become such an institutionalised practice in the industry.

Additionally, there are other risk measures that manager’s may choose to add to their risk measurement process such as the ones mentioned in A. Mikes article: Risk Management and Calculative Cultures. For example, tailored credit risk models that gauge the probability of default and the expected credit loss in

Garima Singh

various loan portfolios. Other ones include is Operational Risk and Basel rules (require banks to set aside regulatory capital that must reflect the amount of risk they take).

Question 4The statement tries to point out that VaR served the purpose to reduce transparency in risks to make better judgment. However, if people lack a proper understanding of risk then even VaR cannot serve its purpose effectively since it essentially acts as a holistic aid in risk measurement.

The COSO paper on KRIs supplements this theory: “The KRI identification process may benefit from subject matter experts within the organisation as these individuals may be in the best position to know where stress points (i.e. root cause events and intermediate events) exist in the units they manage or processes they oversee. Their input helps ensure that key risks are not overlooked” and therefore “the person charged with oversight of the enterprise risk management process can work in concert with the risk owners (senior management) to identify appropriate trigger points and action or treatment plans to be initiated in the event those points are reached”.

Many of the organisational actors (i.e. top management) ignored that VaR does not capture all relevant risks (measuring the “right” things). The statement also further tries to emphasise that some risk managers may have seen risks before the crisis but were not heard. Therefore risk management was not just about getting the numbers right but also a problem of paying serious attention to those who were delivering the numbers.