All of the following are considered to be weaknesses of the variance/covariance value at risk (VAR) methodology EXCEPT: A) market data necessary to compute VAR is often not available. B) the variance/covariance matrix may not be stable over time. C) the VAR computation becomes complex as portfolio complexity increases. Your answer: C was incorrect. The correct answer was A) market data necessary to compute VAR is often not available. One of the strengths of the variance/covariance VAR is that the required market data is readily available in most cases. ---- May I please have an explanation of why C is a weakness of the variance/covariance approach? Who cares why happens to portfolio complexity–the (very simple formula) is still just (Rp-z*stddev)Vp–why would it become more complex?
To calculate portfolio standard deviation, you use the sqrt[(w1^2)(sd1^2)+(w2^2)(sd2^2)+2(w1)(w2)(corr 1,2)(sd1)(s2)] formula. As more assets are included, the computation gets more complex.
By complexity, they mean the increasing number of inputs into the model, not necessarily the complexity of the formulas etc. And that’s a meaningless question again. One of the advantages of traditional var/covar VaR is the readily availability of historical data, which does not mean that lack of historical data could not be a problem for a particular case.
instead of nitpicking Schweser questions, learn the pros and cons of the VAR methods. Way too much time wasting.