Overview
- Proposes unbiased, novel rule-based techniques for recognizing technical patterns
- Implements a statistical framework for assessing realizing returns
- Presents a unified methodological framework ?
- Includes supplementary material: sn.pub/extras
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Table of contents(9 chapters)
About this book
Authors and Affiliations
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The Business School, Canterbury Christ Church University, Canterbury, United Kingdom
Prodromos E. Tsinaslanidis
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Department of Accounting and Finance, University of Macedonia, Thessaloniki, Greece
Achilleas D. Zapranis
About the authors
Prodromos E. Tsinaslanidis, Ph.D., is Lecturer of Finance in the Business School at the Canterbury Christ Church University. Dr. Tsinaslanidis’ research interests include technical analysis, pattern recognition, efficient market hypothesis and design and assessment of investment and trading strategies.
Achilleas D. Zapranis, Ph.D., is Professor of Finance in the Department of Accounting and Finance at the University of Macedonia, where he is also Rector. In addition, Dr. Zapranis is a member of the Board of Directors of Thessaloniki’s Innovation Zone.
Bibliographic Information
Book Title: Technical Analysis for Algorithmic Pattern Recognition
Authors: Prodromos E. Tsinaslanidis, Achilleas D. Zapranis
DOI: https://doi.org/10.1007/978-3-319-23636-0
Publisher: Springer Cham
eBook Packages: Economics and Finance, Economics and Finance (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Hardcover ISBN: 978-3-319-23635-3Published: 06 November 2015
Softcover ISBN: 978-3-319-35395-1Published: 23 August 2016
eBook ISBN: 978-3-319-23636-0Published: 31 October 2015
Edition Number: 1
Number of Pages: XIV, 204
Topics: Finance, general, Econometrics, Statistics for Business, Management, Economics, Finance, Insurance, Pattern Recognition, Quantitative Finance, Macroeconomics/Monetary Economics//Financial Economics