Chapter 3. Measuring and Monitoring Volatility Study Notes ontains 38 pages covering the following learning objectives:

* Explain how asset return distributions tend to deviate from the normal distribution.

* Explain reasons for fat tails in a return distribution and describe their implications.

* Distinguish between conditional and unconditional distributions.

* Describe the implications of regime switching on quantifying volatility.

* Evaluate the various approaches for estimating VaR.

* Compare and contrast different parametric and non-parametric approaches for estimating conditional volatility.

* Calculate conditional volatility using parametric and non-parametric approaches.

* Evaluate implied volatility as a predictor of future volatility and its shortcomings.

* Apply the exponentially weighted moving average (EWMA) approach and the GARCH (1,1) model to estimate volatility.

* Explain and apply approaches to estimate long horizon volatility/VaR, and describe the process of mean reversion according to a GARCH (1,1) model.

* Calculate conditional volatility with and without mean reversion.

* Describe the impact of mean reversion on long horizon conditional volatility estimation.

* Describe an example of updating correlation estimates.

After reviewing the notes, you will be able to apply what you learned with practice questions.

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