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Produktbild: Market Timing with Moving Averages | Valeriy Zakamulin
Produktbild: Market Timing with Moving Averages | Valeriy Zakamulin

Market Timing with Moving Averages

The Anatomy and Performance of Trading Rules

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This book provides a comprehensive guide to market timing using moving averages. Part I explores the foundations of market timing rules, presenting a methodology for examining how the value of a trading indicator is computed. Using this methodology the author then applies the computation of trading indicators to a variety of market timing rules to analyse the commonalities and differences between the rules. Part II goes on to present a comprehensive analysis of the empirical performance of trading rules based on moving averages.

Inhaltsverzeichnis

Chapter1 Introduction. - Chapter2 Moving Averages. - Chapter3 Trading Rules. - Chapter4 Anatomy of Trading Rules. - Chapter5 Case Study: Historical Performance of Trading Rules on Other. - Chapter6 Summary and Conclusions.

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Produktdetails

Erscheinungsdatum
30. August 2018
Sprache
englisch
Auflage
Softcover reprint of the original 1st edition 2017
Seitenanzahl
312
Reihe
Economics and Finance (R0)
Autor/Autorin
Valeriy Zakamulin
Illustrationen
XXXII, 278 p. 64 illus.
Verlag/Hersteller
Produktart
kartoniert
Abbildungen
XXXII, 278 p. 64 illus.
Gewicht
476 g
Größe (L/B/H)
235/155/17 mm
Sonstiges
Previously published in hardcover
ISBN
9783319869728

Portrait

Valeriy Zakamulin

Valeriy Zakamulin is Professor of Finance at the School of Business and Law, University of Agder, Norway. He has an M. S. in Business Administration and a PhD in Finance from the Norwegian School of Economics, Norway. He has published articles for various refereed academic and practitioner journals and is a frequent speaker at international conferences. He has also served on the Editorial Board of the Open Economics Journal, Journal of Banking and Finance, and International Journal of Emerging Markets. His current research interests cover behavioral finance, portfolio optimization, time-series analysis of financial data, and stock return and risk predictability.

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