Technical Analysis for Algorithmic Pattern Recognition

Technical Analysis for Algorithmic Pattern Recognition

Author: Prodromos E. Tsinaslanidis

Publisher: Springer

Published: 2015-10-31

Total Pages: 213

ISBN-13: 3319236369

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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. ​


Evidence-Based Technical Analysis

Evidence-Based Technical Analysis

Author: David Aronson

Publisher: John Wiley & Sons

Published: 2011-07-11

Total Pages: 572

ISBN-13: 1118160584

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Evidence-Based Technical Analysis examines how you can apply the scientific method, and recently developed statistical tests, to determine the true effectiveness of technical trading signals. Throughout the book, expert David Aronson provides you with comprehensive coverage of this new methodology, which is specifically designed for evaluating the performance of rules/signals that are discovered by data mining.


Pattern Recognition and Classification in Time Series Data

Pattern Recognition and Classification in Time Series Data

Author: Volna, Eva

Publisher: IGI Global

Published: 2016-07-22

Total Pages: 295

ISBN-13: 1522505660

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Patterns can be any number of items that occur repeatedly, whether in the behaviour of animals, humans, traffic, or even in the appearance of a design. As technologies continue to advance, recognizing, mimicking, and responding to all types of patterns becomes more precise. Pattern Recognition and Classification in Time Series Data focuses on intelligent methods and techniques for recognizing and storing dynamic patterns. Emphasizing topics related to artificial intelligence, pattern management, and algorithm development, in addition to practical examples and applications, this publication is an essential reference source for graduate students, researchers, and professionals in a variety of computer-related disciplines.


Technical Analysis Applications

Technical Analysis Applications

Author: Florin Cornel Dumiter

Publisher: Springer Nature

Published: 2023-03-11

Total Pages: 178

ISBN-13: 3031274164

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This book integrates technical analysis in the capital markets: stock market theories, valuation approaches, portfolio theories, company analysis. In addition to deepening the overall inspection of technical analysis, the book will challenge the corporate norm and offer alternative theories, sometimes even contrary theories, and explore related areas in the context of increasing investment efficiency. Unlike other research in this area, this approach does not consider technical analysis as an ultimate and absolute truth and recognizes that by studying all aspects of an interdisciplinary problem, the chances of success increase substantially. The book will be of specific interest to academics, students and practitioners of financial markets.


Technical Analysis

Technical Analysis

Author: Charles D. Kirkpatrick II

Publisher: FT Press

Published: 2010-11-08

Total Pages: 700

ISBN-13: 0132599627

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Already the field's most comprehensive, reliable, and objective guidebook, Technical Analysis: The Complete Resource for Financial Market Technicians, Second Edition has been thoroughly updated to reflect the field's latest advances. Selected by the Market Technicians Association as the official companion to its prestigious Chartered Market Technician (CMT) program, this book systematically explains the theory of technical analysis, presenting academic evidence both for and against it. Using hundreds of fully updated illustrations, the authors explain the analysis of both markets and individual issues, and present complete investment systems and portfolio management plans. They present authoritative, up-to-date coverage of tested sentiment, momentum indicators, seasonal affects, flow of funds, testing systems, risk mitigation strategies, and many other topics. This edition thoroughly covers the latest advances in pattern recognition, market analysis, and systems management. The authors introduce new confidence tests; cover increasingly popular methods such as Kagi, Renko, Kase, Ichimoku, Clouds, and DeMark indicators; present innovations in exit stops, portfolio selection, and testing; and discuss the implications of behavioral bias for technical analysis. They also reassess old formulas and methods, such as intermarket relationships, identifying pitfalls that emerged during the recent market decline. For traders, researchers, and serious investors alike, this is the definitive book on technical analysis.


Handbook of Artificial Intelligence for Music

Handbook of Artificial Intelligence for Music

Author: Eduardo Reck Miranda

Publisher: Springer Nature

Published: 2021-07-02

Total Pages: 994

ISBN-13: 3030721167

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This book presents comprehensive coverage of the latest advances in research into enabling machines to listen to and compose new music. It includes chapters introducing what we know about human musical intelligence and on how this knowledge can be simulated with AI. The development of interactive musical robots and emerging new approaches to AI-based musical creativity are also introduced, including brain–computer music interfaces, bio-processors and quantum computing. Artificial Intelligence (AI) technology permeates the music industry, from management systems for recording studios to recommendation systems for online commercialization of music through the Internet. Yet whereas AI for online music distribution is well advanced, this book focuses on a largely unexplored application: AI for creating the actual musical content.


Mathematical and Statistical Methods for Actuarial Sciences and Finance

Mathematical and Statistical Methods for Actuarial Sciences and Finance

Author: Marco Corazza

Publisher: Springer Science & Business Media

Published: 2011-06-07

Total Pages: 315

ISBN-13: 8847014816

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This book features selected papers from the international conference MAF 2008 that cover a wide variety of subjects in actuarial, insurance and financial fields, all treated in light of the successful cooperation between mathematics and statistics.


Algorithmic Trading: Technical Indicators

Algorithmic Trading: Technical Indicators

Author: SQ2 SYSTEMS AB

Publisher: SQ2 SYSTEMS AB

Published: 2023-09-20

Total Pages: 43

ISBN-13:

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"Algorithmic Trading: Technical Indicators" is your go-to guide for unraveling the power of technical indicators in algorithmic trading. If you're intrigued by data-driven signals that inform trading decisions, this book is your key to mastering the art of technical analysis. Designed for traders and investors seeking a practical introduction to technical indicators, this book simplifies the complex world of charts, patterns, and signals. It provides clear insights into how historical price and volume data can drive trading strategies. Explore the fundamental principles of technical analysis, where historical data becomes your ally in making informed trading decisions. Delve into the secrets of candlestick patterns, moving averages, Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), and Bollinger Bands. These indicators will become your trusted tools for identifying trends, overbought or oversold conditions, and potential reversals. "Algorithmic Trading: Technical Indicators" offers practical guidance on incorporating these indicators into your trading strategy. Discover how to recognize entry and exit points, effectively manage risk with stop-loss and take-profit levels, and enhance your decision-making. This book provides accessible insights without delving into complex technical examples or deep understanding. It's perfect for beginners curious about the power of technical analysis or experienced traders looking to refine their algorithmic strategies. Whether you're new to technical indicators or seeking to enhance your trading skills, "Algorithmic Trading: Technical Indicators" equips you with the knowledge and tools to confidently navigate the world of algorithmic trading through the lens of technical analysis. Join us in harnessing the potential of data-driven trading signals in today's dynamic financial markets.


Statistical Pattern Recognition

Statistical Pattern Recognition

Author: Andrew R. Webb

Publisher: John Wiley & Sons

Published: 2003-07-25

Total Pages: 516

ISBN-13: 0470854782

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Statistical pattern recognition is a very active area of study andresearch, which has seen many advances in recent years. New andemerging applications - such as data mining, web searching,multimedia data retrieval, face recognition, and cursivehandwriting recognition - require robust and efficient patternrecognition techniques. Statistical decision making and estimationare regarded as fundamental to the study of pattern recognition. Statistical Pattern Recognition, Second Edition has been fullyupdated with new methods, applications and references. It providesa comprehensive introduction to this vibrant area - with materialdrawn from engineering, statistics, computer science and the socialsciences - and covers many application areas, such as databasedesign, artificial neural networks, and decision supportsystems. * Provides a self-contained introduction to statistical patternrecognition. * Each technique described is illustrated by real examples. * Covers Bayesian methods, neural networks, support vectormachines, and unsupervised classification. * Each section concludes with a description of the applicationsthat have been addressed and with further developments of thetheory. * Includes background material on dissimilarity, parameterestimation, data, linear algebra and probability. * Features a variety of exercises, from 'open-book' questions tomore lengthy projects. The book is aimed primarily at senior undergraduate and graduatestudents studying statistical pattern recognition, patternprocessing, neural networks, and data mining, in both statisticsand engineering departments. It is also an excellent source ofreference for technical professionals working in advancedinformation development environments. For further information on the techniques and applicationsdiscussed in this book please visit ahref="http://www.statistical-pattern-recognition.net/"www.statistical-pattern-recognition.net/a


Encyclopedia of Chart Patterns

Encyclopedia of Chart Patterns

Author: Thomas N. Bulkowski

Publisher: John Wiley & Sons

Published: 2011-03-10

Total Pages: 1145

ISBN-13: 1118045858

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In this revised and expanded second edition of the bestselling Encyclopedia of Chart Patterns, Thomas Bulkowski updates the classic with new performance statistics for both bull and bear markets and 23 new patterns, including a second section devoted to ten event patterns. Bulkowski tells you how to trade the significant events -- such as quarterly earnings announcements, retail sales, stock upgrades and downgrades -- that shape today?s trading and uses statistics to back up his approach. This comprehensive new edition is a must-have reference if you're a technical investor or trader. Place your order today. "The most complete reference to chart patterns available. It goes where no one has gone before. Bulkowski gives hard data on how good and bad the patterns are. A must-read for anyone that's ever looked at a chart and wondered what was happening." -- Larry Williams, trader and author of Long-Term Secrets to Short-Term Trading