Advertisement

Technical Analysis for Algorithmic Pattern Recognition

  • Prodromos E. Tsinaslanidis
  • Achilleas D. Zapranis

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Prodromos E. Tsinaslanidis, Achilleas D. Zapranis
    Pages 1-28
  3. Prodromos E. Tsinaslanidis, Achilleas D. Zapranis
    Pages 29-43
  4. Prodromos E. Tsinaslanidis, Achilleas D. Zapranis
    Pages 45-55
  5. Prodromos E. Tsinaslanidis, Achilleas D. Zapranis
    Pages 57-83
  6. Prodromos E. Tsinaslanidis, Achilleas D. Zapranis
    Pages 85-126
  7. Prodromos E. Tsinaslanidis, Achilleas D. Zapranis
    Pages 127-145
  8. Prodromos E. Tsinaslanidis, Achilleas D. Zapranis
    Pages 147-159
  9. Prodromos E. Tsinaslanidis, Achilleas D. Zapranis
    Pages 161-192
  10. Prodromos E. Tsinaslanidis, Achilleas D. Zapranis
    Pages 193-204

About this book

Introduction

The main purpose of this book is to resolve deficiencies and limitations that currently exist when using Technical Analysis (TA). Particularly, TA is being used either by academics as an “economic test” of the weak-form Efficient Market Hypothesis (EMH) or by practitioners as a main or supplementary tool for deriving trading signals. This book approaches TA in a systematic way utilizing all the available estimation theory and tests. This is achieved through the developing of novel rule-based pattern recognizers, and the implementation of statistical tests for assessing the importance of realized returns. More emphasis is given to technical patterns where subjectivity in their identification process is apparent. Our proposed methodology is based on the algorithmic and thus unbiased pattern recognition. The unified methodological framework presented in this book can serve as a benchmark for both future academic studies that test the null hypothesis of the weak-form EMH and for practitioners that want to embed TA within their trading/investment decision making processes.      ​

Keywords

Algorithmic Pattern Recognition Efficient Market Hypothesis Financial Markets Technical Analysis Trading Strategies

Authors and affiliations

  • Prodromos E. Tsinaslanidis
    • 1
  • Achilleas D. Zapranis
    • 2
  1. 1.The Business SchoolCanterbury Christ Church UniversityCanterburyUnited Kingdom
  2. 2.Department of Accounting and FinanceUniversity of MacedoniaThessalonikiGreece

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-23636-0
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Economics and Finance
  • Print ISBN 978-3-319-23635-3
  • Online ISBN 978-3-319-23636-0
  • Buy this book on publisher's site
Industry Sectors
Pharma
Automotive
Chemical Manufacturing
Biotechnology
Finance, Business & Banking
Oil, Gas & Geosciences
Engineering