Download or read book Technical Analysis for Algorithmic Pattern Recognition written by Prodromos E. Tsinaslanidis and published by Springer. This book was released on 2015-10-31 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Technical Analysis written by Jasmina Hasanhodzic and published by . This book was released on 2004 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: We revisit the kernel regression based pattern recognition algorithm designed by Lo, Mamaysky, and Wang (2000) to extract nonlinear patterns from the noisy price data, and develop an analogous neural network based one. We argue that, given the natural flexibility of neural network models and the extent of parallel processing that they allow, our algorithm is a step forward in the automation of technical analysis. More importantly, following the approach proposed by Lo, Mamaysky, and Wang, we apply our neural network based model to examine empirically the ability of the patterns under consideration to add value to the investment process. We discover overwhelming support for the validity of these indicators, just like Lo, Mamaysky, and Wang do. Moreover, this basic conclusion appears to remain valid across different levels of smoothing and insensitive to the nuances of pattern definitions present in the technical analysis literature. This confirms that Lo, Mamaysky, and Wang's results are not an artifact of their kernel regression model, and suggests that the kinds of nonlinearities that technical indicators are designed to capture constitute some underlying properties of the financial time series itself. Finally, we complement our empirical analysis with a historical one, focusing on the origins of trading and speculation in general, and technical analysis in particular.
Download or read book Pattern Recognition and Trading Decisions written by Chris Satchwell and published by McGraw Hill Professional. This book was released on 2004-10-22 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Success in technical analysis is all about recognizing, and quickly acting on, patterns of market behavior. Pattern Recognition and Trading Decisions shows active traders how to realize when a pattern is developing, distinguish between a genuine pattern and a misleading series of events, and apply this recognition for success in specific trading situations. A how-to guide that steers clear of difficult calculations and formulas, this dynamic book--from an author tabbed "far ahead of anyone else" by technical analysis guru Martin Pring--is destined to be on the desktop of every serious technical trader.
Download or read book Mastering Financial Pattern Recognition written by Sofien Kaabar and published by "O'Reilly Media, Inc.". This book was released on 2022-10-18 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: Candlesticks have become a key component of platforms and charting programs for financial trading. With these charts, traders can learn underlying patterns for interpreting price action history and forecasts. This A-Z guide shows portfolio managers, quants, strategists, and analysts how to use Python to recognize, scan, trade, and back-test the profitability of candlestick patterns. Financial author, trading consultant, and institutional market strategist Sofien Kaabar shows you how to create a candlestick scanner and indicator so you can compare the profitability of these patterns. With this hands-on book, you'll also explore a new type of charting system similar to candlesticks, as well as new patterns that have never been presented before. With this book, you will: Create and understand the conditions required for classic and modern candlestick patterns Learn the market psychology behind them Use a framework to learn how back-testing trading strategies are conducted Explore different charting systems and understand their limitations Import OHLC historical FX data in Python in different time frames Use algorithms to scan for and reproduce patterns Learn a pattern's potential by evaluating its profitability and predictability
Download or read book Foundations of Technical Analysis written by Andrew Wen-Chuan Lo and published by . This book was released on 2000 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technical analysis, also known as charting, ' has been part of financial practice for many decades, but this discipline has not received the same level of academic scrutiny and acceptance as more traditional approaches such as fundamental analysis. One of the main obstacles is the highly subjective nature of technical analysis the presence of geometric shapes in historical price charts is often in the eyes of the beholder. In this paper, we propose a systematic and automatic approach to technical pattern recognition using nonparametric kernel regression, and apply this method to a large number of U.S. stocks from 1962 to 1996 to evaluate the effectiveness to technical analysis. By comparing the unconditional empirical distribution of daily stock returns to the conditional distribution conditioned on specific technical indicators such as head-and-shoulders or double-bottoms we find that over the 31-year sample period, several technical indicators do provide incremental information and may have some practical value
Download or read book Evidence Based Technical Analysis written by David Aronson and published by John Wiley & Sons. This book was released on 2011-07-11 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Foundations of Technical Analysis written by Andrew W. Lo and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Technical analysis, also known as quot;charting,quot; has been a part of financial practice for many decades, but this discipline has not received the same level of academic scrutiny and acceptance as more traditional approaches such as fundamental analysis. One of the main obstacles is the highly subjective nature of technical analysis - the presence of geometric shapes in historical price charts is often in the eyes of the beholder. In this paper, we propose a systematic and automatic approach to technical pattern recognition using nonparametric kernel regression, and apply this method to a large number of U.S. stocks from 1962 to 1996 to evaluate the effectiveness of technical analysis. By comparing the unconditional empirical distribution of daily stock returns to the conditional distribution - conditioned on specific technical indicators such as head-and-shoulders or double-bottoms - we find that over the 31-year sample period, several technical indicators do provide incremental information and may have some practical value.
Download or read book Pattern Recognition written by Brett Anderson and published by Scientific e-Resources. This book was released on 2019-09-14 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Watching the environment and recognising patterns with the end goal of basic leadership is central to human instinct. This book manages the logical train that empowers comparable observation in machines through pattern recognition, which has application in differing innovation regions-character recognition, picture handling, modern computerization, web looks, discourse recognition, therapeutic diagnostics, target recognition, space science, remote detecting, information mining, biometric recognizable proof-to give some examples. This book is a composition of central subjects in pattern recognition utilizing an algorithmic approach. It gives a careful prologue to the ideas of pattern recognition and an efficient record of the real points in pattern recognition other than assessing the huge advance made in the field as of late. It incorporates fundamental strategies of pattern recognition, neural systems, bolster vector machines and choice trees. While hypothetical angles have been given due scope, the accentuation is more on the pragmatic. Pattern recognition has application in practically every field of human undertaking including topography, geology, space science and brain research. All the more particularly, it is helpful in bioinformatics, mental investigation, biometrics and a large group of different applications.
Download or read book Pattern Recognition written by Sergios Theodoridis and published by Elsevier. This book was released on 2006-04-07 with total page 854 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern recognition is a fast growing area with applications in a widely diverse number of fields such as communications engineering, bioinformatics, data mining, content-based database retrieval, to name but a few. This new edition addresses and keeps pace with the most recent advancements in these and related areas. This new edition: a) covers Data Mining, which was not treated in the previous edition, and is integrated with existing material in the book, b) includes new results on Learning Theory and Support Vector Machines, that are at the forefront of today's research, with a lot of interest both in academia and in applications-oriented communities, c) for the first time treats audio along with image applications since in today's world the most advanced applications are treated in a unified way and d) the subject of classifier combinations is treated, since this is a hot topic currently of interest in the pattern recognition community. - The latest results on support vector machines including v-SVM's and their geometric interpretation - Classifier combinations including the Boosting approach - State-of-the-art material for clustering algorithms tailored for large data sets and/or high dimensional data, as required by applications such as web-mining and bioinformatics - Coverage of diverse applications such as image analysis, optical character recognition, channel equalization, speech recognition and audio classification
Download or read book Pattern Recognition written by Wladyslaw Homenda and published by John Wiley & Sons. This book was released on 2018-03-07 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new approach to the issue of data quality in pattern recognition Detailing foundational concepts before introducing more complex methodologies and algorithms, this book is a self-contained manual for advanced data analysis and data mining. Top-down organization presents detailed applications only after methodological issues have been mastered, and step-by-step instructions help ensure successful implementation of new processes. By positioning data quality as a factor to be dealt with rather than overcome, the framework provided serves as a valuable, versatile tool in the analysis arsenal. For decades, practical need has inspired intense theoretical and applied research into pattern recognition for numerous and diverse applications. Throughout, the limiting factor and perpetual problem has been data—its sheer diversity, abundance, and variable quality presents the central challenge to pattern recognition innovation. Pattern Recognition: A Quality of Data Perspective repositions that challenge from a hurdle to a given, and presents a new framework for comprehensive data analysis that is designed specifically to accommodate problem data. Designed as both a practical manual and a discussion about the most useful elements of pattern recognition innovation, this book: Details fundamental pattern recognition concepts, including feature space construction, classifiers, rejection, and evaluation Provides a systematic examination of the concepts, design methodology, and algorithms involved in pattern recognition Includes numerous experiments, detailed schemes, and more advanced problems that reinforce complex concepts Acts as a self-contained primer toward advanced solutions, with detailed background and step-by-step processes Introduces the concept of granules and provides a framework for granular computing Pattern recognition plays a pivotal role in data analysis and data mining, fields which are themselves being applied in an expanding sphere of utility. By facing the data quality issue head-on, this book provides students, practitioners, and researchers with a clear way forward amidst the ever-expanding data supply.
Download or read book Statistical Pattern Recognition written by Andrew R. Webb and published by John Wiley & Sons. This book was released on 2011-10-13 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions. It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields, including the areas of engineering, statistics, computer science and the social sciences. The book has been updated to cover new methods and applications, and includes a wide range of techniques such as Bayesian methods, neural networks, support vector machines, feature selection and feature reduction techniques.Technical descriptions and motivations are provided, and the techniques are illustrated using real examples. Statistical Pattern Recognition, 3rd Edition: Provides a self-contained introduction to statistical pattern recognition. Includes new material presenting the analysis of complex networks. Introduces readers to methods for Bayesian density estimation. Presents descriptions of new applications in biometrics, security, finance and condition monitoring. Provides descriptions and guidance for implementing techniques, which will be invaluable to software engineers and developers seeking to develop real applications Describes mathematically the range of statistical pattern recognition techniques. Presents a variety of exercises including more extensive computer projects. The in-depth technical descriptions make the book suitable for senior undergraduate and graduate students in statistics, computer science and engineering. Statistical Pattern Recognition is also an excellent reference source for technical professionals. Chapters have been arranged to facilitate implementation of the techniques by software engineers and developers in non-statistical engineering fields. www.wiley.com/go/statistical_pattern_recognition
Download or read book Pattern Recognition Algorithms for Data Mining written by Sankar K. Pal and published by CRC Press. This book was released on 2004-05-27 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. This volume presents various theories, me
Download or read book Computational Intelligence for Pattern Recognition written by Witold Pedrycz and published by Springer. This book was released on 2018-04-30 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a comprehensive and up-to-date review of fuzzy pattern recognition. It carefully discusses a range of methodological and algorithmic issues, as well as implementations and case studies, and identifies the best design practices, assesses business models and practices of pattern recognition in real-world applications in industry, health care, administration, and business. Since the inception of fuzzy sets, fuzzy pattern recognition with its methodology, algorithms, and applications, has offered new insights into the principles and practice of pattern classification. Computational intelligence (CI) establishes a comprehensive framework aimed at fostering the paradigm of pattern recognition. The collection of contributions included in this book offers a representative overview of the advances in the area, with timely, in-depth and comprehensive material on the conceptually appealing and practically sound methodology and practices of CI-based pattern recognition.
Download or read book Methodologies of Pattern Recognition written by Satosi Watanabe and published by Academic Press. This book was released on 2014-05-12 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methodologies of Pattern Recognition is a collection of papers that deals with the two approaches to pattern recognition (geometrical and structural), the Robbins-Monro procedures, and the implications of interactive graphic computers for pattern recognition methodology. Some papers describe non-supervised learning in statistical pattern recognition, parallel computation in pattern recognition, and statistical analysis as a tool to make patterns emerge from data. One paper points out the importance of cluster processing in visual perception in which proximate points of similar brightness values form clusters. At higher levels of mental activity humans are efficient in clumping complex items into clusters. Another paper suggests a recognition method which combines versatility and an efficient noise-proofness in dealing with the two main problems in the field of recognition. These difficulties are the presence of a large variety of observed signals and the presence of interference. One paper reports on a possible feature selection for pattern recognition systems employing the minimization of population entropy. Electronic engineers, physicists, physiologists, psychologists, logicians, mathematicians, and philosophers will find great rewards in reading the above collection.
Download or read book Technical Analysis for Portofolio Trading by Syntactic Pattern Recognition written by L. F. Pau and published by . This book was released on 1989 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Pattern Recognition written by S. Ramakrishnan and published by BoD – Books on Demand. This book was released on 2016-12-14 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern recognition continued to be one of the important research fields in computer science and electrical engineering. Lots of new applications are emerging, and hence pattern analysis and synthesis become significant subfields in pattern recognition. This book is an edited volume and has six chapters arranged into two sections, namely, pattern recognition analysis and pattern recognition applications. This book will be useful for graduate students, researchers, and practicing engineers working in the field of machine vision and computer science and engineering.
Download or read book Pattern Recognition written by M. Narasimha Murty and published by Springer Science & Business Media. This book was released on 2011-05-25 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Observing the environment and recognising patterns for the purpose of decision making is fundamental to human nature. This book deals with the scientific discipline that enables similar perception in machines through pattern recognition (PR), which has application in diverse technology areas. This book is an exposition of principal topics in PR using an algorithmic approach. It provides a thorough introduction to the concepts of PR and a systematic account of the major topics in PR besides reviewing the vast progress made in the field in recent times. It includes basic techniques of PR, neural networks, support vector machines and decision trees. While theoretical aspects have been given due coverage, the emphasis is more on the practical. The book is replete with examples and illustrations and includes chapter-end exercises. It is designed to meet the needs of senior undergraduate and postgraduate students of computer science and allied disciplines.
