Raising the bar Solution to Question 1 from UoL exam 2016, Zone A

Apr 18

Solution to Question 1 from UoL exam 2016, Zone A

Solution to Question 1 from UoL exam 2016, Zone A (FN3142)

Frankly, this is a crazy exercise. I deserve full 100 marks for this solution but I wouldn't be able to solve this during an exam. In the problem statement, I took the liberty to change some terminology and notation. In particular, I use the definitions of the Value at Risk and expected shortfall that give negative values. You can go ahead and redo everything with definitions that give positive values.

Problem statement

Assume daily returns that are normally distributed with constant mean (equal to zero) and variance, i.e., they are given by

$R_{t+1}=\sigma_{t+1} z_{t+1},$ where $z_{t+1}\vert\mathcal{F}_t\overset{i.i.d.}{\sim}N(0,1),$

where the time increment $t+1$ is 1-day.

(a) [25 marks] Derive the following formula for the Value-at-Risk at the $\alpha$ % critical level and 1-day horizon

(1) $VaR^\alpha_{t+1}=\sigma_{t+1}\Phi^{-1}(\alpha)$

where $\Phi$ is the standard normal cumulative density function.

(b) [25 marks] The expected shortfall $ES^\alpha_{t+1}$ at the critical level $\alpha$ % and 1-day horizon can be defined as

$ES^\alpha_{t+1}=E_t(R_{t+1}|R_{t+1}\le VaR^\alpha_{t+1})$ .

Using the VaR formula from part (a) derive the following formula for the 1-day expected shortfall

(2) $ES^\alpha_{t+1}=-\frac{\sigma_{t+1}}{\alpha}p_z(\Phi^{-1}(\alpha))$

where $p_z$ is the standard normal probability density function.

(c) [50 marks] Prove that the relative difference between the 1-day expected shortfall and 1-day Value-at-Risk, as a proportion of the 1-day Value-at-Risk, converges to zero when $\alpha$ goes to zero, i.e., show that

(3) $\lim_{\alpha\rightarrow 0}\frac{ES^\alpha_{t+1}-VaR^\alpha_{t+1}}{VaR^\alpha_{t+1}}=0.$

Solution

(a) The answer is contained in this post.

(b) This part has been solved here.

$\lambda\equiv\frac{ES^\alpha_{t+1}-VaR^\alpha_{t+1}}{VaR^\alpha_{t+1}}=\frac{-\frac{\sigma_{t+1}}{\alpha}p_z(\Phi^{-1}(\alpha))-\sigma_{t+1}\Phi^{-1}(\alpha)}{\sigma_{t+1}\Phi^{-1}(\alpha)}$