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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 Mrz 2012, 2012
ISBN 10: 3639393929
ISBN 13: 9783639393927
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Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 92 pp. Englisch. Bestandsnummer des Verkäufers 9783639393927
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Technical Trading Rules
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Siegert Philipp JanPhilipp 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, Netherl. Bestandsnummer des Verkäufers 4983626
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Technical Trading Rules
Verlag:
AV Akademikerverlag Mär 2012, 2012
ISBN 10: 3639393929
ISBN 13: 9783639393927
Neu
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. Bestandsnummer des Verkäufers 9783639393927
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Technical Trading Rules : Empirical Evidence from Future Data
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Bestandsnummer des Verkäufers 9783639393927
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Technical Trading Rules | Empirical Evidence from Future Data
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Taschenbuch. Zustand: Neu. Technical Trading Rules | Empirical Evidence from Future Data | Philipp Jan Siegert | Taschenbuch | 92 S. | Englisch | 2012 | AV Akademikerverlag | EAN 9783639393927 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 106573644
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Technical Trading Rules: Empirical Evidence from Future Data
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paperback. Zustand: New. New. Ships from Multiple Locations. book. Bestandsnummer des Verkäufers ERICA82936393939296
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