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Capital Structure <strong>in</strong> Banks 217<br />

Theoretical Concerns Schröder was one of the first 390 to po<strong>in</strong>t out that VaRbased<br />

risk measures have a serious short<strong>com</strong><strong>in</strong>g <strong>in</strong> that they lack a sound<br />

theoretical foundation. 391 We can def<strong>in</strong>e the so-called lower partial moment<br />

(LPM) of a distribution as:<br />

t<br />

n<br />

LPMn() t =<br />

∫<br />

( t −X) f ( X)<br />

dX<br />

(5.39) 392<br />

where t = Target (m<strong>in</strong>imum) return<br />

X = Realized return<br />

n = Moment of the distribution<br />

f = Probability density function of the returns X<br />

−∞<br />

The moment n of the distribution determ<strong>in</strong>es (theoretically) the type of<br />

the utility function used. 393 For <strong>in</strong>stance, for n = 0, 394 this approach 395 assumes<br />

a risk-neutral <strong>in</strong>vestor who is only <strong>in</strong>terested <strong>in</strong> the probability of<br />

fall<strong>in</strong>g short of the target m<strong>in</strong>imum return t, ignor<strong>in</strong>g the extent (or severity)<br />

of this event when it occurs. For n = 1, we consider a risk-averse <strong>in</strong>vestor<br />

who is <strong>in</strong>terested <strong>in</strong> both the probability <strong>and</strong> the extent (severity) of the<br />

actual return fall<strong>in</strong>g short of the target return t. It therefore calculates<br />

the expected value of the shortfall. 396 For n = 2, the result is similar to the<br />

semivariance <strong>and</strong> is, therefore, also often called target semivariance. 397<br />

Replac<strong>in</strong>g the target return t with VaR α<br />

, the value at risk at the (1 – α)<br />

confidence level, it is easy to show, because:<br />

– VaR<br />

∫<br />

LPM0 (– VaR ) = f ( X) dX = F(– VaR ) = %,<br />

α α<br />

α<br />

– ∞<br />

that<br />

–VaR α<br />

= F -1 (LPM 0<br />

) (5.40)<br />

where F<br />

F -1<br />

= Cumulative probability function<br />

= The <strong>in</strong>verse of the cumulative probability function<br />

390 At least <strong>in</strong> discuss<strong>in</strong>g this <strong>in</strong> the context of VaR approaches.<br />

391 See Schröder (1996), pp. 1–2. Obviously, Markowitz (1959) already po<strong>in</strong>ts <strong>in</strong>to<br />

the same direction.<br />

392 See Fishburn (1977), p. 116.<br />

393 See Wittrock (1995), p. 43.<br />

394 Obviously, this is the least restrictive shortfall risk measure possible.<br />

395 As can be easily seen, LPM 0<br />

reduces to the (cumulative) probability distribution.<br />

396 In the above methodology, we would call this expected loss.<br />

397 See Copel<strong>and</strong> <strong>and</strong> Weston (1988), p. 152. This measure is also suitable for riskaverse<br />

<strong>in</strong>vestors.

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