Quantifying volatility in var models

[darshang3]

Hi david,

there is one chapter in valuation called Quantifying volatility in var models by Linda Allen this chapter is very lengthy can u tell me the relevant concepts which can be tested in exam from this chapter as it includes estimation of volatilies which is also included in Quants.
wat all concepts to be studied ?


thanks in advance.

 

[David Harper CFA FRM]

Darshang,

you should refer to the AIMs, here are the AIMs for Linda Allen Chapter 2:

* Discuss how asset return distributions tend to deviate from the normal distribution.
* Explain potential reasons for the existence of fat tails in a return distribution and discuss the implications fat tails have on analysis of return distributions.
* Distinguish between conditional and unconditional distributions.
* Discuss the implications regime switching has on quantifying volatility.
* Explain the various approaches for estimating VaR.
* Compare and contrast parametric approaches for estimating conditional volatility, including the historical standard deviation approach, the RiskMetrics® approach and the GARCH approach, and discuss the advantages and disadvantages of parametric methods for volatility forecasting.
* Compare and contrast the use of historic simulation, multivariate density estimation, and hybrid methods for volatility forecasting.
* Explain the process of return aggregation in the context of volatility forecasting methods.
* Explain how implied volatility can be used to predict future volatility and discuss its advantages and disadvantages.
* Explain the implications of mean reversion in returns and return volatility for forecasting VaR over long time horizons.
* Discuss the effects non‐synchronous data has on estimating correlation and describe approaches that mitigate the impact of non‐synchronous data on risk estimates.

David