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Revision with unchanged content. Most banks and the recently upcoming hedge fund industry rely to a different extent on technical trading rules and technical analysis. The fact that these technical trading rules yield superior returns in practice raises several questions that will be examined in this book. First, one of the most crucial questions is in which assets technical trading rules perform extraordinarily well. This analysis is based on a risk-return approach with an assessment of the negative standard deviation of each asset as a risk indicator. Second, the statistical significance of technical trading is examined by using a simulation method known as bootstrap. Third, null models are simulated to answer the question to what extent autoregressive models and GARCH models are able to capture the dependencies in the future time series. Finally, a rule optimizer algorithm is developed to assess if any rule parameters yield superior returns over a wide range of assets.
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Philipp Jan Siegertgraduated with a MSc in International Financefrom the French „Grande Ecole“ CERAM SophiaAntipolis. He also holds a BSc in InternatioalEconomics & Business from the University ofGroningen, Netherlands.Mr. Siegert currently works in London at Keefe,Bruyette & Woods, a leadinginvestment bank in the financial sector.
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Technical Trading Rules
Verlag:
AV Akademikerverlag Mär 2012, 2012
ISBN 10: 3639393929
ISBN 13: 9783639393927
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Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Neuware -Revision with unchanged content. Most banks and the recently upcoming hedge fund industry rely to a different extent on technical trading rules and technical analysis. The fact that these technical trading rules yield superior returns in practice raises several questions that will be examined in this book. First, one of the most crucial questions is in which assets technical trading rules perform extraordinarily well. This analysis is based on a risk-return approach with an assessment of the negative standard deviation of each asset as a risk indicator. Second, the statistical significance of technical trading is examined by using a simulation method known as bootstrap. Third, null models are simulated to answer the question to what extent autoregressive models and GARCH models are able to capture the dependencies in the future time series. Finally, a rule optimizer algorithm is developed to assess if any rule parameters yield superior returns over a wide range of assets.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 92 pp. Englisch. Artikel-Nr. 9783639393927
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