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Volatility Forecasting and DeltaNeutral Volatility Trading for ...

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we evaluate profits from options trading for rival volatility ... tions on the DTB DAX option trading were carried out by the second named author ...

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Volatility Forecasting and DeltaNeutral Volatility Trading for DTB Options on the DAX H.J. Bartels Department Page 1Volatility Forecasting and DeltaNeutral Volatility Trading for DTB Options on the DAX H.J. Bartels Department of Mathematics and Computer Science University of Mannheim Seminargebaude 45 D68131 Mannheim. Germany Tel.: 496211812450 Fax: 496211812506 Email: bartels@math.unimannheim.de Jian Lu Department of Political Economy University of Mannheim Seminargebaude A5 D68131 Mannheim Germany Tel.: 496211811936 Fax: 496211811931 Email: lu@pool.unimannheim.de Abstract One of the most interesting topics in financial time series analysis is the forecasting of the volatility of asset returns. Market practice has found different ways around this problem. One approach derives implied volatilities from actual option prices. Another possibility would be to predict the volatility on the basis of historical asset returns. In recent years the ARCH type models appear to be promising in the mentioned time series context. The optimal choice of an appropriate model for predicting volatility outofsample is closely related to the question of how to measure the prediction performance of a model. In our study below we use four volatility approaches: implied volatility historical volatility GARCH( 1 l) and EGAR.CH(ll) volatility forecasts and compare their performance with two option trading strategies. The backtesting includes a time period from July 1995 to July 1997. The methodology we have used in our study offers an opportunity to evaluate the outofsample volatility forecast with a convenient metric: the profitability in cumulative profits. 4s a result it turns out that the performances of the different models are dependent of the used trading strategies and are also depending on filters adopted fo ...

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