Prediction in ARMA Models with GARCH in Mean Effects

Menelaos G. Karanasos

36 citations0/0 files storedJournal of Time Series Analysis

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Financial Risk and Volatility Modeling Forecasting Techniques and Applications Stock Market Forecasting Methods

Abstract

This paper considers forecasting the conditional mean and variance from an ARMA model with GARCH in mean effects. Expressions for the optimal predictors and their conditional and unconditional MSEs are presented. We also derive the formula for the covariance structure of the process and its conditional variance. JEL. C22.

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References

1986Generalized autoregressive conditional heteroskedasticity 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation 1977Time Series Analysis: Forecasting and Control 1993On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks 1992ARCH modeling in finance 1987Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model 1992No news is good news 1994Autoregressive conditional heteroskedasticity and changes in regime

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2002Moments and dynamic structure of a time‐varying parameter stochastic volatility in mean model 2004Analyzing US inflation by a GARCH model with simultaneous feedback

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