Forecasting Volatility:Evidence from the German Stock Market

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Show simple item record Bluhm, Hagen en Yu, Jun en 2006-11-30T20:53:46Z en 2006-11-30T20:53:46Z en 2001 en
dc.identifier.citation Department of Economics Working Paper Series 219 en
dc.identifier.uri en
dc.description.abstract In this paper we compare two basic approaches to forecast volatility in the German stock market. The first approach uses various univariate time series techniques while the second approach makes use of volatility implied in option prices. The time series models include the historical mean model, the exponentially weighted moving average (EWMA) model, four ARCH-type models and a stochastic volatility (SV) model. Based on the utilization of volatility forecasts in option pricing and Value-at-Risk (VaR), various forecast horizons and forecast error measurements are used to assess the ability of volatility forecasts. We show that the model rankings are sensitive to the error measurements as well as the forecast horizons. The result indicates that it is difficult to state which method is the clear winner. However, when option pricing is the primary interest, the SV model and implied volatility should be used. On the other hand, when VaR is the objective, the ARCH-type models are useful. Furthermore, a trading strategy suggests that the time series models are not better than the implied volatility in predicting volatility. en
dc.format.extent application/pdf en
dc.format.mimetype text en
dc.language.iso en en
dc.publisher ResearchSpace@Auckland en
dc.relation.ispartofseries Department of Economics Working Paper Series (1997-2006) en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri en
dc.subject.other Forecasting Volatility en
dc.subject.other Economics en
dc.title Forecasting Volatility:Evidence from the German Stock Market en
dc.type Working Paper en
dc.rights.holder Copyright: the author en Economics en

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