Risk Management and Value Creation in ... - Arabictrader.com

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Capital Structure in Banks 201 ■ ■ expected losses, 323 the bank should either calculate an internal insurance premium (similar to expected losses for credit risk) or should buy insurance at a premium. For the remaining (small) probability that event risks outside the three sigma range lead to larger losses, the bank should hold economic capital (see below). 324 Banks should insure as much of the risk of experiencing major event losses as they can. Even though buying insurance externally is frequently perceived as expensive because of the direct and observable costs that are associated with it, buying catastrophe insurance might be the most appropriate way to hedge against event risk. 325 Despite the fact that such catastrophe insurance for banks is more or less in the early stage of development, 326 insurance companies now offer mitigation options at competitive prices. 327 Therefore, the other available option, to try and exploit the internal potential for selfinsurance, seems to be less attractive but should be used where appropriate, that is, where the market price is higher. Assuming that a bank has insured itself up to its intended level and has executed controls to the extent desired, the bank should hold economic capital for the remaining part of its event risks; the derivation of the amount of this economic capital will be discussed in detail below. The Derivation of Economic Capital for Remaining Event Risks As already mentioned, event risk has no upside potential. Therefore, the methodology to determine economic capital for event risk should be similar to the one for determining economic capital for credit risk, especially with respect to the fact that an event can occur with probability PE H or not with probability (1 – PE H ) at any time over the predetermined time horizon up to H. 328 In a manner similar to that used in the credit risk framework, we can also estimate the expected size of the loss at any time up to H and can, hence, determine an expected loss (in dollar terms) for event risks (EL ER ). As for 323 One could also rate/score the underlying processes and calibrate them to probabilities of occurrence (despite the fact that there is very little historical data to do so), see Buhr (2000), pp. 203–205, and then determine expected losses and in a VaRlike approach the required economic capital amount. 324 See Lam and Cameron (1999), p. 83. 325 See Damodaran (1997), p. 777, and Lam and Cameron (1999), p. 88. 326 Banks have only just realized the potential for large losses since they have been trying to measure event risks. 327 See Wills et al. (1999), pp. 79–81 and 111. 328 Since we will use a consistent time horizon of one year, again we will drop time index H from our discussion.
202 RISK MANAGEMENT AND VALUE CREATION IN FINANCIAL INSTITUTIONS EL for credit risk, a bank should build (loss) reserves for what it can expect to lose on average due to event risks 329 and should also include that in its pricing. However, as we have also seen previously in the credit risk framework, if losses are “lumpy” or are experienced only rarely, 330 then the expected losses amount will not be sufficient to cover the (unexpected) losses up to a certain level of confidence. Therefore, we also need to hold economic capital for event risks. 331 In general, this amount of economic capital can be derived in the same way as for credit risk. The problem, however, is that the number of observable event risk losses for estimating the event risk loss distribution is even scarcer than the data points for credit risk. Because of the lack of sufficient data for a historical analysis, a variety of assumptions need to be made for the calculation of event risk capital, making the approach subject to challenge and criticism. In almost all of the cases, banks will have no or insufficient (historical) internal experience with major event risk losses, because—by definition— those events are very infrequent. To increase the number of observations, data points (mostly in the form of case studies) from as many banks and events as possible are being collected in so-called event loss databases, which are currently being built around the world. 332 Since there are many different types of event risk to which a bank can be exposed, it is useful to create different categories 333 of such events and adjust them for the bank’s risk profile before conducting the quantitative analysis. 334 These adjustments need to be made in two dimensions: ■ Adjustment of the potential size of the loss due to event risk: The event database is a good starting point for the estimation of the potential size of the loss due to an event in a certain category. However, a bank should use the input from its risk experts to allow for a customization of the potential size of the loss for the bank, adjusting for both the size and the risk characteristics of the bank. 335 329 See Lam and Cameron (1999), pp. 87–88. 330 Indicating that the normal assumption might not be appropriate and the distribution is skewed. 331 Recall that the total amount of capital available to “burn” before a bank goes into default is EL ER plus the economic capital held for event risks. 332 See Wills et al. (1999), pp. 11 and 66–70. 333 For a possible list of categories, see the event risk definition above. 334 This data collection and interpretation can be very costly. The expected costs for conducting the analysis should, therefore, be evaluated against the expected value of losses from event risks in a cost-benefit analysis. 335 Obviously, this is very subjective, but also the only way to derive meaningful results.
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isk management and value creation i
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Copyright © 2002 by John Wiley & S
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preface From an empirical as well a
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acknowledgments No book is solely t
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x CONTENTS Goals of Risk Management
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xii CONTENTS Definition of RAROC 24
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xiv FIGURES Figure 5.5 Figure 5.6 F
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symbols ↑ ↓ α β i xvi Increas
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xviii SYMBOLS ln Natural logarithm
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abbreviations APT BIS bn bps CAPM C
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2 RISK MANAGEMENT AND VALUE CREATIO
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CHAPTER 2 Foundations for Determini
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Foundations for Determining the Lin
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eferences Aguais, Scott D., and Ant
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References 295 Blanden, Michael (19
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References 297 and Abuses,” Journ
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References 299 Froot, Kenneth A., a
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References 301 risiken aus Handelsg
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References 303 Investments in Stock
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References 305 Institute of Technol
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References 307 Sharpe, William F. (
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References 309 Wall, L.D., and John
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312 INDEX Approach (continued) top-
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314 INDEX Capital: Tier-1, 139, 146
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316 INDEX Credit: derivatives, 178,
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318 INDEX Expectations: homogeneous
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320 INDEX Incentive(s), 22, 33, 45,
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322 INDEX Managers, poorly diversif
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324 INDEX Overinvestment, 75, 79, 8
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326 INDEX Reserve(s) (continued) lo
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328 INDEX Risk, liquidity, 3, 165 R
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330 INDEX Sharpe ratio, 244, 252 Sh
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332 INDEX Value at risk (VaR) (cont
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