Article2001

GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics

1,224 citations0/0 files storedThe Journal of Economic Perspectives

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Financial Risk and Volatility Modeling Stochastic processes and financial applications Complex Systems and Time Series Analysis

Abstract

ARCH and GARCH models have become important tools in the analysis of time series data, particularly in financial applications. These models are especially useful when the goal of the study is to analyze and forecast volatility. This paper gives the motivation behind the simplest GARCH model and illustrates its usefulness in examining portfolio risk. Extensions are briefly discussed.

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References

1986Generalized autoregressive conditional heteroskedasticity 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation 1991Conditional Heteroskedasticity in Asset Returns: A New Approach 1993On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks 1993Measuring and Testing the Impact of News on Volatility 1992Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances 2004CAViaR

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