AC211 Module 4 Class 4

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Garima Singh AC211. Module 4 – Class 4 Risk and Performance Measurement Question 1 One 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 int
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  Garima Singh  AC211. Module 4 – Class 4Risk and Performance Measurement Question 1 One of the primary reasons VaR became so popular is that it was developed as acommon measure that could be applied to just about any asset class.Additionally, VaR could be regarded a performance measure of how good theorganisation was at minimising risk whilst making profits and it was increasinglybeing perceived as a sign of good governance due to its growing popularity andthus seen to possibly translate into good performance.The article draws to attention the many flaws of VaR, which will beconsi dered 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”. It  s simplicity made it an accessible and easily understandable measure toa much wider variety of peop le 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 lesssound in their understanding of VaR than risk managers/risk experts) tended totake comfort in a single number rather than scrutinizing signs of changes orobserving the measure on a regular basis. Which eventually would lead to a “bubble” because of limiting focus only on a single number. Second ly, VaR benchmarked itself against ‘past’ events, which could be extremely unreliable and misleading because new factors and new environments were extremelyimportant to take into consideration as well –   this is known as “futureblindness” , where people tend not to be able to anticipate a future they havenever personally experienced. Thirdly, the VaR measure ignored the possibility of “fat tails” or “black swans” as N.N.Tale b describes them. For example, VaR onlyfocused on the number that fell within a 99% probability and ignored what couldhappened 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 lik  ely tohave a significant impact may arise from external sources, such as changes in economic conditions…Thus many organisations discover that relevant KRIs areoften 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 themeasure 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 2 The statement more or less supports the fact that VaR numbers could be veryuseful as diagnostic control tools because they provided a top-level view and alsobecause they were a standardized measure they provided better comparabilityfor senior management.  Garima SinghDespite having previous knowledge as a trader himself, Dennis Weatherstone supported the VaR measure because “he understood both thelimits and the value of VaR” and “It told him things he hadn’t known before. Hecould 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 managersa 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 theincreasing dependence on VaR and the clouded judgement that resulted fromthis. Question 3 The statement describes the institutionalisation of VaR as an industry-wide risk measure. VaR may have increasingly become a more important part of thefinancial scene because as more and more companies regarded it as “good managerial pract  ice”   since other companies were using it too (like a “dominoeffect”   –   “I’ll do this because you’re doing it too” ).This widespread acceptance of VaR signalled to more and more peoplethat it was a useful tool in risk measurement. However, it was important torecognise that VaR needed to be complemented along with accurate judgment of the significance of the measure by top management otherwise the informationwas worthless or even potentially dangerous (misleading). Through the exampleof Dennis Weatherstone of JPMorgan and Goldman Sachs, we saw in the articlethat the VaR measure was used to facilitate and reinforce decision-making andnot a tool to simply acquire data. This may have been a common mistake amongless experienced or less knowledgeabl e managers that may have led to “bubbles” being created like 2008 housing bubble. Managers may have come to accept VaRas a common standard for risk measurement in the industry but failed tounderstand that VaR was after all based on a 2-year data history, an aggregatedmeasure and to top it all ignored the fact that VaR only captured 99% probabilityand ignored the remaining 1% probability.Nevertheless, as Greg Berman puts it: “If you say that all risk isunknowable, you don’t have the basis of any sort    of a bet or a trade…if you spendall your time thinking about black swans, you’ll be so risk averse you’ll never doa trade…to not use VaR is to say that I won’t care about the 99%, in which caseyou won’t have a business…When you think about disasters, a ll you can rely on isthe 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 VaRsituation, and as mentioned before, “it was the best number anyone had come up with”. This sufficiently provides us with some foundation to understand howVaR 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. Mikesarticle: Risk Management and Calculative Cultures. For example, tailored credit risk models that gauge the probability of default and the expected credit loss in  Garima Singhvarious 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 4 The statement tries to point out that VaR served the purpose to reducetransparency in risks to make better judgment. However, if people lack a properunderstanding 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 theseindividuals 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 orprocesses 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 (seniormanagement) 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 risksbefore 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 tothose who were delivering the numbers.
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