Technical analysis and financial asset forecasting : from simple tools to advanced technique
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Bibliographic Information
Technical analysis and financial asset forecasting : from simple tools to advanced technique
World Scientific, c2014
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Note
Includes bibliographical references (p. 173-179) and index
Description and Table of Contents
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.
Table of Contents
- Introduction to Technical Analysis
- The Primary Tools for Technical Analysis
- Chart Pattern Reading - Trend, Trend Line and Trend Channel
- Chart Pattern Reading - Identifying Important Chart Patterns
- Linear Filters
- Momentum Indicators
- Moving Averages
- Wavelets in Financial Market Trading
- Bollinger Bands and Relative Strength Index
- Unraveling Mysticism in Gann's Theory: Prophecy of Stock Market Trends
- Standardized Yield Differential Indicator
- Empirical Mode Decomposition in Financial Time Series
- Other Trading Methods in Technical Analysis.
by "Nielsen BookData"