Value at Risk Framework and its Utility in Risk Management - Assignment Example

? Value at Risk framework and its utility in Risk Management Introduction In the last few years, risk management truly has went through an upheaval, and a new methodology has been initiated, which is known as the value at risk ( VaR) which is being employed to measure risk associated with the financial market, and this has been developed mainly due to difficulties experienced in the financial disasters in the early 1990s. VaR is now being employed to manage and control risk well beyond derivatives. VaR methodology is now assisting us to calculate both operational and credit risk resulting to the Holy Grail of business risk management. Many famous financial companies like Barings, Orange County, Daiwa, Metallgesellschaft, etc. filed bankruptcy due to failure on their part to manage risk during the financial disaster that occurred in 1990s. If there is not proper management or poor supervision, then billions of dollars may be lost when a financial disaster occurs. VaR is a technique of evaluating risk that employs standard statistical methodologies employed on regular levels in other technical fields. VaR reviews the worst financial loss over a target perspective that will not be surpassed with a given intensity of confidence. Footed on strong scientific groundwork, VaR offers its users with an outline evaluation of risk in market. “For example, a financial institution might inform that its VaR of its trading assortment on a daily basis is $10 million at the 98% buoyancy or “confidence level”. This mean, there is only 1 opportunity in a 100, under typical market scenario, for a financial loss higher than $50 million to happen. This single number recapitulates the bank’s vulnerability not only to the prospect of an unfavourable move but also to market risk.” It evaluates the risk employing the analogues' units as the bank’s bottom-line dollars. The management and the shareholders then can make a decision, whether they feel at ease with this magnitude of risk. If the reply is in negative, then the process that has been used to the computation of VaR can be employed to settle on where to trim down the risk. (Jorion 2007: ix) As compared with the customary risk management measures, VaR offers an aggregate panorama of a portfolio’s risk that quantifies for correlations, leverage and present positions. As a result, it is truly a futuristic risk evaluation. VaR is applicable to all financial instruments though in the initial stage, it has been applied only to derivatives. (Jorion 2007: ix) 2- Background Every morning, in J.P Morgan Chase, the global head of Market risk receives a bulk report that summaries the value at risk (VaR) of the bank. JPMorgan Chase's bank’s global risk management system is generating this report during every night. Today, many brokerage firms, many banks, investment funds and even nonfinancial companies employ analogues methods to estimate their financial risk. Securities market regulators, private sector groups and banks have widely acknowledged statistical based risk management strategies like VaR. (Jorion2007:18). Till Guldimann can be said to be the father of the concept VaR while he functioned as the head of global research at J.P Morgan in the late 1980s. J P Morgan’s risk management group had to decide whether fully hedged meant making investment in long-maturity bonds, thus creating a fixed and stable revenues but oscillations in market value or investing in cash thus making the market value as fixed. The J P Morgan bank concluded that “value risks “were more significant than “earning risks” resulting from the invention of VaR. (Jorion2007:18). During that period, there were more concerns in the bank about managing the risk of derivatives. The Group of Thirty (G-30) which had a delegate from J P Morgan offered a way for deliberating best risk management techniques. Through the G-30 report which was published in July 1993, the term VaR term found its way. (Jorion2007:18). On June 26, 1974, the German authorities closed a troubled midsized bank namely the Bankhaus Herstatt. Though the bank was very active in foreign –exchange market, on the fateful day, it had exposed to huge losses as they sent large quantity of Deutsche marks but not received U.S dollars as U.S banks were exposed to losses on the full amount which the German bank had sent. This had ushered disruptions in financial markets and sent global transaction volumes in a tailspin. This risk story made the central bankers around the world to comprehend the necessity for coordination at the international level. Thus, Herstatt episode was the instrumental for the establishment of the Basel Committee on Banking Supervision., (BCBS), which after the lapse of fifteen years, introduced capital adequacy norms for the global banking system as a risk management measure.(Jorion2007:25). 3- Analysis (The Value at risk Theoretical Definition of VaR The VaR is regarded as a computation of downside risk. It is the calculation of the left tail risk of financial sequences. VaR is the maximum quantum of loss that can occur over a given perspective at some confidence level. It normally emerges in announcements like, The utmost loss over one day is about $ 5 million at the 95% confidence level. If one presumes that F is the Cumulative Distribution function of a return process, one can illustrate VaR as F (VaR) = ? (1.1) Where ? is the matching probability for the specific confidence intensity. For example, for 99% confidence level, ? = 0.01. Employing a density function f of returns, VaR can also be equivalently explained as ? = VaR f (x) d(x). - ? (Gregoriou 2009:6) Let us assume a portfolio of $100 million in value. Let us assume that the anticipated return over the next week is .2% with a standard deviation of 3%. Also let us presume that there exist normal distributions. Then, we understand that the minimum 5% possible returns are returns that happen more than “1.65 standard deviations away from the mean.” Thus 5% of the time we can anticipate returns below R -1.65 or .2 – (1.65) * (.3) .Abridging these outcomes a return of -0.295% or less. Suppose, if this investor has 100 million in assets, then, there will be a loss of $ 295,000 or more. This dollar number, 295,000 is known as Value at Risk. VaR is the best result that can happen if returns are in the worst part of the possible results. Thus, one has to project the standard deviation and the mean return over the period in question and employ the normal distribution to decide how many standard deviations from the mean are concerned with. The worst 5% is the common preference which is 1.65 standard deviations from the mean, t. This return is then calculated and multiplied times the value of the assets to arrive at the least dollar loss if the returns are in the worst probable set of results. Many financial institutions normally have assets that may not have normal distributions of returns like securities with options-like features. These financial institutions normally employ simulation to calculate the value at risk. These firms simulate probable return paths thousands of times and then decide the best outcomes among the bad results. These firms stimulate worst results. For instance, if the institution performed 1000 simulations, and they were concerned with the worst 5% of results, they would arrange the results and from the 50 bad results ( lowest 5%) take the highest returns. This, number of times the assets suffer in the dollar loss, and this dollar loss would be designated as the VaR. (Elton et al. 2009:234). The notion of VaR thus revolved around two arbitrary bounds – the horizon period, which may be a day, a fortnight, a week, etc; and a level of confidence, which may be, for illustration, be 97%, 95%. For example, if we have a 97% confidence level and a daily horizon, our VaR would be the maximum anticipated loss over a day, at the 97% level of confidence. There are many methods to project VaR. These projection methods include chronological simulation methods, in which VaR is projected from the past data of losses / profits linked with a many parametric and specific portfolio approaches, in which one can estimate that underlying risk elements adhere to some other or normal specific probability distribution. VaR can also be estimated by the use of extreme value theory or by using Monte Carlo other simulation approaches. Primarily, VaR projections are only estimates of general risk, and often not very appreciable ones. The different approaches can give quite different estimates of VaR and no one guarantee, which is the best one. Each approach to VaR has its own advantages and disadvantages, and that some kinds of portfolios (e.g., ones with lots of exotic or optionality derivatives positions) have VaRs that are mainly difficult to assess. As per Beder (1995) and Marshall and Siegel (1998)). Even if financial institutions or banks seem to use the similar fundamental type of VaR form, there is substantiation that projections can still differ extensively, even when their projection the VaRs of precisely of the same portfolios. As per Dowd (2000), VaR projections are footed on a single generally established well-specified form would still be suffering from momentous margins of error. It is essential to differentiate the difference in a majority of banks and in the majority of investment banks between the banking book and the trading book and or loan portfolio. In a nutshell, one should ever consider VaR projections with vigilance, since they can be subject to significant error. How VaR is being used to Minimise Risks “Companies managing Risk may be either have managers for cash flow risk or managers for value risk. A manager for cash flow risk employs risk control to minimise cash flow instability and thus enhances the capacity of debt.” In contrary, a manager for value risk is anxious with the company’s aggregate value at a specific phase of period. “This distress may happen from a need to circumvent insolvency, alleviate issues connected with informational imbalances or minimise anticipated tax commitments. A manager for cashflow risk controls the risks or a flow of funds whereas a value risk manager thus ideally controls the perils of an accumulation of assets. It is to be observed that a risk management that is fitting to one kind of company may not be relevant to another type of company.” (Stern & Chew 2003: 420). 4-Case studies Though VaR can offer many advantages to some companies, VaR is not a panacea for risks. Despite the fact that VaR is calculated properly, VaR in isolation will not act as a full pledged risk avoider in line with the company’s risk vulnerability. Devoid of a full-fledged risk management mechanism – procedures and policies, chiselled top management obligations and systems, VaR can contribute only modest advantages to companies. VaR may always not assist the companies to achieve its specific risk management goals. “To demonstrate a few of the disadvantages of employing VaR, we have to recall the 4 “great derivative disasters “that occurred in 1993-1995 viz. Orange County, Procter & Gamble, Metallgesellschaft and Barrings”. “Supporters of VaR frequently maintain that majority of these financial tragedies would have been prevented a bad VaR calculation system had been in place.” (Stern & Chew 2003:420). VaR offers a common, consistent measure of risk across different risk factors and positions. VaR facilitates risk managers to quantify the risk inherent with equity or speculative instruments like derivatives. VaR assumes cross-hedging and the correlations between risk factors or different asset classes’ .VaR can be considered to be an integral risk measure since all driving risk elements are wholly taken into consideration, it also spotlights on a complete portfolio. VaR offers an approximation of future happenings in a probabilistic manner meant that loss amounts are connected with probabilities. In a very understandable unit way i.e. in lost money value, VaR can be presented. It could be easily understood by everybody including top management. Further, VaR can be computed for all varieties of assets. “Thus, one can calculate VaR for “forex risk, commodity price risk, interest rate risk, and credit risk.” Some companies add all individual VaRs together to compute an overall VaR. “ It is to be noted that VaR is not free from criticism. It is to be observed that VaR is not a maximum loss quantified and actual loss in VaR can vary or exceed the loss estimation. Calculation of VaR offers a challenge even for IT systems as it involves complex calculations. As banks are using a spreadsheet to calculate VaR, there is every possibility for the presence of stale data and calculation error while arriving at VaR. As regards to option, VaR does not deal well and there is no proper evaluation of operational measurement risk involved in it. Thus, there is a possibility of incurring a loss due to frauds and poor controls. (MMag & Hofler: 21). The failure of Barrings acted as a power object lesson in risk management. According to experts, Barrings had disregarded majority of the recommendations made by G-30. However, from the Barrings fiasco, we have learnt new lessons. For the first time in UK, the Bank of England reported about reputational risk. This relates to the risk to earnings emanating from negative public opinion. Reputational risk can render a bank or a company to financial loss or to litigation from the discredit of association with clients. The G-30 report also recognised several lessons from the Barrings disaster. There is a duty on the management to comprehend about the full nature of the business they manage. The top management at Barings did not have a thorough comprehension of Leeson’s business in spite of the fact that it was obviously creating huge profits for the Barrings. For each business, responsibility should be clearly established- Barrings was employing a “matrix” reporting method (by product and region) that left confusions in the reporting features for the trader, Nick Leeson. For any effective risk control system, there should be clear segregation of duties. Indeed, the letdown has been attributed to the fact that Leeson had control over the back and front offices. Thus, the Barrings episode exhibited once and for all the necessity for independent risk management. (Jorion2007:50). LTCM When LTCM was in near failure to corroborate its risk management strategies in the industry, the Counterparty Risk Management Policy Group (CRMPG) was established. As with G-30, the efforts by private-sector were also intended at averting heavy-handed rules of financial markets. Undeniably, the brokerage industry had come under severe criticism for permitting LTCM to build up heavy leverage. LTCM main goal is to devise investment strategies intended to earn very high returns with low risk. LTCM made an investment in so-called hedged –risk investments, particularly in the fixed-income marketplace. LTCM believed in its basic investment strategy with low in risk and it employed large amounts of borrowed capital to “leverage” the returns to equity investors in the fund. LTCM had a capital of $ 7 billion, and it had also invested over $ 125 billion that was financed with the debt. Though LTCM earned profits in the year 1994 to 1997 but in the year 1998, it losses were estimated at 10% of its capital value in June 1998. LTCM made some fundamental wrong in their investment strategies. Their assumptions about the association between financial values and the values of key economic variable demonstrated to be wrong and the risk that was borne by funds’ investors was somewhat higher than the risk they anticipated. (Moyer et al 2008:25). Case Study – The Fall of Bear Stearns After passing of one decade of Russian-Asian financial crisis in 1998 that sparked off the downfall of LTCM, in 2008, the world again saw a global financial crisis that has intimidated to weaken both the financial institutions and capital markets across the world. The new financial crisis was activated by the U.S subprime mortgage disaster and has pulled down Bear Stearns, the globe’s fifth leading investment bank. Due to the subprime mortgage crisis, other leading investment banks across the world were also compelled to recapitalize their capital base by issuing a combination of equity and debt at distressed prices to sovereign wealth funds. For instance, a $7.5 billion stake in Citigroup was acquired by the Abu Dhabi Investment Authority (ADIA). The Singapore government arm namely Government Investment Arm (GIC) pumped in $9.75 billion in UBS group and made an investment of $6.88 billion into Citigroup. Along with Korean Investment Corporation (KIC), the GIC’s sister concern, Temasek, jointly invested $11 billion in Merrill Lynch. In Morgan Stanley, an investment of $5 billion was made by Chinese Investment Corporation. (Hsu & Kalesnik 2009:386) Due to the fact of ever increasing subprime mortgage losses, it seems that the application of VaR in the global finance industry is still far from necessary. As per Japan’s Financial Services Agency (FSA), the global subprime mortgage crisis losses have crossed $215 billion mark. Deutsche Bank and J.P. Morgan Chase project that the global losses due to subprime mortgage crisis could be around $300 to $ 400 billion, which is a really a whooping figure as compared to the losses of just $4.6 billion by LTCM in 1998. (Hsu & Kalesnik 2009:386) It is pertinent to ask why things have gone wrong when VaR is in force in these failed banks like Bear Stearns, Merrill Lynch, Morgan Stanley, Citigroup, etc. during the subprime mortgage crisis. Banks are needed to make VaR calculations to make sure that capital adequacy as well as to control risk associated with their balance sheets. Nonetheless, VaR had not minimised the risk as witnessed from the whooping losses incurred during the subprime mortgage crisis. However, VaR supporters argue that banks may have been employing inapt probability distributions to sculpt asset price risk. Especially, the distributions employed for calculating VaR may not enough to seize the occurrence of severe distresses to asset price (kurtosis) and the magnitude of severe shocks (negative skew).( Hsu & Kalesnik 2009:387) . Kuritzkes, a risk officer, found many incompatibilities in the usage of risk measurement tools in Bear Stearns. Kruitzkes labeled as flying blind as the Bear witnessed a variety of holes in risk management. He found that there existed cultural resistance in certain places at Bear to implement VaR and found that there existed even a single metric for financial risk in Bear and hence, there was no method to contrast and group various types of risk on an “apple-to-apple” basis. Kuritzkes suggested that Bear was in need of “well –structured VaR structure add together with stress testing. Kuritzkes was of the view that Bear’s fall was due to deficiency in their VaR. (Shari 2011:22). As per Engle and Armelliono, any application of VaR at Bear Stearns could have been only paved it to under -evaluate its vulnerability to risks associated with the subprime mortgage. Authors’ are of the opinion that VaR is a gauge of short-term risk –what could arise in the next week or the next day whereas the mortgage is having attributes of long-term risk. Risk management team at Bear Stearns was of the opinion that over reliance on VaR caused abnormal losses. It footed on stress numbers and on VaR, despite delinquency rates were mounting and there was a fall in origination standards in the U.S mortgage market. However, Bear prolonged to invest in subprime assets that were hedged partially. Hence, we can say had the Bear Stearns followed the VaR principles in letter and spirit, it would not have been a scapegoat for subprime losses. (Shari 2011:22). 5-Conclusions By assisting the reliable evaluation of risk across diverse activities and assets, VaR permits companies to supervise report, manage and manage their risks in a style that resourcefully narrates risk control to both actual and desired monetary vulnerability. At the identical juncture, complete dependence on VaR can end in grave concerns when inappropriately employed. Hence, the future users of VaR are hereby suggested to take into account the subsequent: “VaR is only beneficial to some companies and only in specific scenarios. VaR is a mechanism for companies engrossed in consolidated value risk control where the aggregate significances of vulnerability across a cluster of actions are at subject-matter. Perilous misrepresentation of the risk witnessing a company can end when VaR is erroneously used in scenarios where aggregate value risk administration is not the objective, such as companies anxious about cash flow risk instead of value risk.” VaR must be employed very methodologically to companies selectively administering their risks as a part of its core business objectives.” For such risks, VaR can act as a problem-solving supervising mechanism for such risks. While VaR is evaluated and revealed in such scenarios with no projections of identical anticipated revenues, the data expressed by the VaR projection can be gravely hoodwinking. “ Ultimately , as the all the past great derivative disasters imply , no company of risk management mechanisms – including VaR – is an alternative for good risk management. Risk management as a method includes a lot of activities than mere risk evaluation. “ Despite the thoughtful, risk evaluation can said to be very helpful to some companies, it is fairly meaningless without a well-conceived organisational infrastructure and with IT system, which is competent of backing the dynamic and complex method of risk control and risk assuming.” (Stern & Chew 2003; 420). List of References Elton E J, Martin, Gruber, Brown SJ, Goetzmann WN. (2009). Modern Portfolio Theory and Investors Analysis. New York: John Wiley & Sons. Gregoriou, G N. (2009). The VaR Implementation Handbook. New York: McGraw –Hill Professional. Hsu, J C & Kalesnik V. (2009). Risk –Managing the Uncertainty in VaR Model Parameters. [online] available from < http://www.researchaffiliates.com/ideas/pdf/Risk_Managing_the_Uncertainty_in_VaR.pdf> [accessed on 21 April 2011.] Jorion, Philippe. (2007). Value at Risk: The New Benchmark for Managing the Risk. New York: McGraw –Hill Professional. MMag & Hofler Bernhard. (2008). Risk Measures – Value at Risk and Beyond. New York: Grin. Moyer R C, McGuigan J R, Kretlow WJ. (2008). Contemporary Financial Management. New York: Cengage Learning. Shari, Michael. (February 2011). Missing Madoff. [online] available from http://www.riskprofessional-digital.com/riskprofessional/201102?pg=25#pg25> [accessed on 21 April 2011.] Stern J M & Chew, D H. (2003). The Revolution in Corporate Finance. New York: Wiley Blackwell. Read More