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Real-Time GARCH

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  • Ekaterina Smetanina

Abstract

Most GARCH-type models follow Engle’s (1982) original idea of modeling the volatility of asset returns as a function of only past information. We propose a new model, which retains the simple GARCH structure, but describes the volatility process as a mixture of past and current information. We show how the new model can be interpreted as the special case of a stochastic volatility (SV) model, which provides therefore a link between GARCH and SV models. We show that we are able to obtain better volatility forecasts than the standard GARCH-type models; improve the empirical fit to the data, especially in the tails of the distribution; and make the model faster in its adjustment to the new unconditional level of volatility. Further, we offer a much needed framework for specification testing as the new model nests the standard GARCH models.

Suggested Citation

  • Ekaterina Smetanina, 2017. "Real-Time GARCH," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 561-601.
    • Handle: RePEc:oup:jfinec:v:15:y:2017:i:4:p:561-601.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbx008
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    References listed on IDEAS

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