Volatility (FRM Part 1 2023 – Book 2 – Chapter 14)

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After completing this reading you should be able to:
- Define and distinguish between volatility, variance rate, and implied volatility.
- Describe the power law.
- Explain how various weighting schemes can be used in estimating volatility.
- Apply the exponentially weighted moving average (EWMA) model to estimate volatility.
- Describe the generalized autoregressive conditional heteroskedasticity (GARCH(p,q)) model for estimating volatility and its properties.
- Calculate volatility using the GARCH(1,1) model.
- Explain mean reversion and how it is captured in the GARCH(1,1) model.
- Explain the weights in the EWMA and GARCH(1,1) models.
- Explain how GARCH models perform in volatility forecasting.
- Describe the volatility term structure and the impact of volatility changes.

0:00 Introduction
0:46 Learning Objectives
1:16 What is Volatility?
4:35 The Power Law
7:46 Weighting Schemes
8:40 The Exponentially Weighted Moving Average (EWMA) Model
10:16 GARCH (1, 1) Model
12:43 Mean Reversion
13:21 Forecasting Performance