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- ÖFAI-TR-98-15 (
42kB g-zipped PostScript file)Volatility Prediction with Mixture Density Networks
- Christian Schittenkopf, Georg Dorffner, Engelbert Dockner
- Despite the lack of a precise definition of volatility in finance,
the estimation of volatility and its prediction is an important
problem. In this paper we compare the performance of standard
volatility models and the performance of a class of neural models,
i.e. mixture density networks (MDNs). First experimental results
indicate
the importance of long-term memory of the models as well as the benefit
of using non-gaussian probability densities for practical applications.
Keywords: Mixture Density Networks, Volatility, Density Estimation, Econometrics
- Despite the lack of a precise definition of volatility in finance,
the estimation of volatility and its prediction is an important
problem. In this paper we compare the performance of standard
volatility models and the performance of a class of neural models,
i.e. mixture density networks (MDNs). First experimental results
indicate
the importance of long-term memory of the models as well as the benefit
of using non-gaussian probability densities for practical applications.