Technical Analysis And Financial Asset Forecasting: From Simple Tools To Advanced Techniques


Book Description

Technical analysis is defined as the tracking and prediction of asset price movements using charts and graphs in combination with various mathematical and statistical methods. More precisely, it is the quantitative criteria used in predicting the relative strength of buying and selling forces within a market to determine what to buy, what to sell, and when to execute trades. This book introduces simple technical analysis tools like moving averages and Bollinger bands, and also advanced techniques such as wavelets and empirical mode decomposition. It first discusses some traditional tools in technical analysis, such as trend, trend Line, trend channel, Gann's Theory, moving averages, and Bollinger bands. It then introduces a recent indicator developed for stock market and two recent techniques used in the technical analysis field: wavelets and the empirical mode decomposition in financial time series. The book also discusses the theory to test the performance of the indicators and introduces the MATLAB Financial Toolbox, some of the functions/codes of which are used in our numerical experiments.




Essentials of Technical Analysis


Book Description

This book presents a roundup of tools in technical analysis. The major targeted readers are university undergraduates and investors who want to have a basic understanding of the nuts and bolts related to technical analysis. The book first discusses some basic and traditional tools and then moves on to study the more advanced mathematical techniques, like neural network and program trading.




Technical Analysis of the Financial Markets


Book Description

John J. Murphy has updated his landmark bestseller Technical Analysis of the Futures Markets, to include all of the financial markets. This outstanding reference has already taught thousands of traders the concepts of technical analysis and their application in the futures and stock markets. Covering the latest developments in computer technology, technical tools, and indicators, the second edition features new material on candlestick charting, intermarket relationships, stocks and stock rotation, plus state-of-the-art examples and figures. From how to read charts to understanding indicators and the crucial role technical analysis plays in investing, readers gain a thorough and accessible overview of the field of technical analysis, with a special emphasis on futures markets. Revised and expanded for the demands of today's financial world, this book is essential reading for anyone interested in tracking and analyzing market behavior.




Analysis of Financial Time Series


Book Description

This book provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: Analysis and application of univariate financial time series The return series of multiple assets Bayesian inference in finance methods Key features of the new edition include additional coverage of modern day topics such as arbitrage, pair trading, realized volatility, and credit risk modeling; a smooth transition from S-Plus to R; and expanded empirical financial data sets. The overall objective of the book is to provide some knowledge of financial time series, introduce some statistical tools useful for analyzing these series and gain experience in financial applications of various econometric methods.




Essentials of Time Series for Financial Applications


Book Description

Essentials of Time Series for Financial Applications serves as an agile reference for upper level students and practitioners who desire a formal, easy-to-follow introduction to the most important time series methods applied in financial applications (pricing, asset management, quant strategies, and risk management). Real-life data and examples developed with EViews illustrate the links between the formal apparatus and the applications. The examples either directly exploit the tools that EViews makes available or use programs that by employing EViews implement specific topics or techniques. The book balances a formal framework with as few proofs as possible against many examples that support its central ideas. Boxes are used throughout to remind readers of technical aspects and definitions and to present examples in a compact fashion, with full details (workout files) available in an on-line appendix. The more advanced chapters provide discussion sections that refer to more advanced textbooks or detailed proofs. - Provides practical, hands-on examples in time-series econometrics - Presents a more application-oriented, less technical book on financial econometrics - Offers rigorous coverage, including technical aspects and references for the proofs, despite being an introduction - Features examples worked out in EViews (9 or higher)




Empirical Asset Pricing


Book Description

An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.




Cybernetic Analysis for Stocks and Futures


Book Description

Cutting-edge insight from the leader in trading technology In Cybernetic Analysis for Stocks and Futures, noted technical analyst John Ehlers continues to enlighten readers on the art of predicting the market based on tested systems. With application of his engineering expertise, Ehlers explains the latest, most advanced techniques that help traders predict stock and futures markets with surgical precision. Unique new indicators and automatic trading systems are described in text as well as Easy Language and EFS code. The approaches are universal and robust enough to be applied to a full range of market conditions. John F. Ehlers (Santa Barbara, CA) is President of MESA Software (www.mesasoftware.com) and has also written Rocket Science for Traders (0-471-40567-1) as well as numerous articles for Futures and Technical Analysis of Stocks & Commodities magazines.




New Frontiers in Technical Analysis


Book Description

An essential guide to the most innovative technical trading tools and strategies available In today's investment arena, there is a growing demand to diversify investment strategies through numerous styles of contemporary market analysis, as well as a continuous search for increasing alpha. Paul Ciana, Bloomberg L.P.'s top liason to Technical Analysts worldwide, understands these challenges very well and that is why he has created New Frontiers in Technical Analysis. Paul, along with in-depth contributions from some of the worlds most accomplished market participants developed this reliable guide that contains some of the newest tools and strategies for analyzing today's markets. The methods discussed are based on the existing body of knowledge of technical analysis and have evolved to support, and appeal to technical, fundamental, and quantitative analysts alike. • It answers the question "What are other people using?" by quantifying the popularity of the universally accepted studies, and then explains how to use them • Includes thought provoking material on seasonality, sector rotation, and market distributions that can bolster portfolio performance • Presents ground-breaking tools and data visualizations that paint a vivid picture of the direction of trend by capitalizing on traditional indicators and eliminating many of their faults • And much more Engaging and informative, New Frontiers in Technical Analysis contains innovative insights that will sharpen your investments strategies and the way you view today's market.




Statistics and Data Analysis for Financial Engineering


Book Description

The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.




Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance


Book Description

This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.