There are different ways of computing the expected shortfall of a portfolio. A common approach is to use historical asset returns to simulate the portfolio return distribution. In the study presented in this chapter, why did the authors use a factor model and the associated factor return history to simulate a portfolio's historical return distribution?
Discuss the difference between beta and shortfall beta.
By constraining shortfall beta, one tends to lower the standard beta of the portfolio, since the two are strongly correlated. Is the outperformance of shortfall constrained optimization for the findings reported in this chapter simply due to its lower beta, especially during the turbulent periods?
Does constraining shortfall help protect against sharp daily losses?
Can you provide any insight into why shortfall constrained optimization performed better than mean-variance optimization in the empirical study?
1 Dimitris Bertsimas, Geoffrey J. Lauprete, and Alexander Samarov, “Shortfall as a Risk Measure: Properties, Optimization and Applications,” Journal of Economic Dynamics and Control 28, no. 7 (2004): 1353–1381.
2 Lisa Goldberg, and Michael Hayes, “The Long View of Financial Risk,” report, MSCI Barra Research Insight (2009).
3 VaR can be computed at other likelihoods of loss as well. For example, The portfolio suffers a return worse than VaRP at 1% or less no more than 1% of the time.
4 Lisa Goldberg, and Michael Hayes, “Barra Extreme Risk,” report, MSCI Barra ...
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