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.Shop Courses