Articlegreen2006

A Mixture Multiplicative Error Model for Realized Volatility

75 citations0/0 files storedJournal of Financial Econometrics

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

Abstract

A multiplicative error model with time-varying parameters and an error term following a mixture of gamma distributions is introduced. The model is fitted to the daily realized volatility series of deutschemark/dollar and yen/dollar returns and is shown to capture the conditional distribution of these variables better than the commonly used autoregressive fractionally integrated moving average model. The forecasting performance of the new model is found to be, in general, superior to that of the set of volatility models recently considered by Andersen et al. (2003, Econometrica 71, 579–625) for the same data.

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References

1986Generalized autoregressive conditional heteroskedasticity 1994Comparing Predictive Accuracy 2003Modeling and Forecasting Realized Volatility 1998Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts 2001The distribution of realized stock return volatility 2001The Distribution of Realized Exchange Rate Volatility 1998Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data 2005A forecast comparison of volatility models: does anything beat a GARCH(1,1)?

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2013Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes 2015Forecasting realized volatility with changing average levels 2012Multiplicative Error Models 2016Volatility-Related Exchange Traded Assets: An Econometric Investigation 2007Forecasting realized exchange rate volatility by decomposition 2019Choice with Limited Capacity

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