Included in this volume are Louise McWhirter's theories and numerous, fully-explained and detailed examples for: Forecasting business cycles and stock market trends, forecasting trends of individual stocks, and forecasting monthly and daily trends on the New York stock exchange.

Stock Market Modeling and Forecasting translates experience in system adaptation gained in an engineering context to the modeling of financial markets with a view to improving the capture and understanding of market dynamics. The modeling process is considered as identifying a dynamic system in which a real stock market is treated as an unknown plant and the identification model proposed is tuned by feedback of the matching error. Like a physical system, a financial market exhibits fast and slow dynamics corresponding to external (such as company value and profitability) and internal forces (such as investor sentiment and commodity prices) respectively. The framework presented here, consisting of an internal model and an adaptive filter, is successful at considering both fast and slow market dynamics. A double selection method is efficacious in identifying input factors influential in market movements, revealing them to be both frequency- and market-dependent. The authors present work on both developed and developing markets in the shape of the US, Hong Kong, Chinese and Singaporean stock markets. Results from all these sources demonstrate the efficiency of the model framework in identifying significant influences and the quality of its predictive ability; promising results are also obtained by applying the model framework to the forecasting of major market-turning periods. Having shown that system-theoretic ideas can form the core of a novel and effective basis for stock market analysis, the book is completed by an indication of possible and likely future expansions of the research in this area.

In 1937 Louise McWhirter published her ground-breaking forecasting methodology in which she revealed how to forecast in advance the general state of the economy for years to come. She revealed how to use planetary angles present at the time of a New Moon to identify key dates in a lunar cycle when the New York Stock Exchange would have a high probability of exhibiting a price trend change. She further showed how to use planetary transits, angles and aspects to predict times when individual stocks and commodity futures would have a high probability of exhibiting a price trend change. Today, McWhirter's work in in danger of fading into a distant memory. This book has been crafted in part to help ensure that does not happen. This book has also been crafted to assist the trader and investor in de-mystifying the many nuances in the McWhirter methodology.

Richard W. Schabacker's great work, Technical Analysis and Stock Market Profits, is a worthy addition to any technical analyst's personal library or any market library. His "pioneering research" represents one of the finest works ever produced on technical analysis, and this book remains an example of the highest order of analytical quality and incisive trading wisdom. Originally devised as a practical course for investors, it is as alive, vital and instructional today as the day it was written. It paved the way for Robert Edwards and John Magee's best-selling Technical Analysis of Stock Trends - a debt which is acknowledged in their foreword: 'Part One is based in large part on the pioneer researches and writings of the late Richard Schabacker.'Schabacker presents technical analysis as a totally organized subject and comprehensively lays out the various important patterns, formations, trends, support and resistance areas, and associated supporting technical detail. He presents factors that can be confidently relied on, and gives equal attention to the blemishes and weaknesses that can upset the best of analytical forecasts: Factors which investors would do well to absorb and apply when undertaking the fascinating game of price, time and volume analysis.

Business Informatics is the scientific discipline targeting information processes and related phenomena in their socio economical business context, including companies, organisations, administrations and society in general As a field of study, it endeavours to take a systematic and analytic approach in adopting a multi disciplinary orientation that draws theories and practices from the fields of management science, organisational science, computer science, systems engineering, information systems, information management, social science, and economics information science The IEEE CBI 2017 is aimed at creating a forum for researchers and practitioners from the fields that contribute to the construction, use and maintenance of information systems and the organisational context in which they are embedded

This is an extensive course for the gann trader as well as the investor. W. D. Gann's Stock Trading Course can teach you a number of different trading techniques and skills, such as charting, chart interpretation, how do find natural resistance levels, forecasting trend changes, using Gann Lines (or Gann Angles), seasonal changes for stocks, how to decipher time cycles, the relationship between time and price, squaring price and time, how to use gann squares & gann calculators and more.

This book constitutes the refereed proceedings of the 8th International Conference on Advanced Data Mining and Applications, ADMA 2012, held in Nanjing, China, in December 2012. The 32 regular papers and 32 short papers presented in this volume were carefully reviewed and selected from 168 submissions. They are organized in topical sections named: social media mining; clustering; machine learning: algorithms and applications; classification; prediction, regression and recognition; optimization and approximation; mining time series and streaming data; Web mining and semantic analysis; data mining applications; search and retrieval; information recommendation and hiding; outlier detection; topic modeling; and data cube computing.

Forecasting—the art and science of predicting future outcomes—has become a crucial skill in business and economic analysis. This volume introduces the reader to the tools, methods, and techniques of forecasting, specifically as they apply to financial and investing decisions. With an emphasis on "earnings per share" (eps), the author presents a data-oriented text on financial forecasting, understanding financial data, assessing firm financial strategies (such as share buybacks and R&D spending), creating efficient portfolios, and hedging stock portfolios with financial futures. The opening chapters explain how to understand economic fluctuations and how the stock market leads the general economic trend; introduce the concept of portfolio construction and how movements in the economy influence stock price movements; and introduce the reader to the forecasting process, including exponential smoothing and time series model estimations. Subsequent chapters examine the composite index of leading economic indicators (LEI); review financial statement analysis and mean-variance efficient portfolios; and assess the effectiveness of analysts’ earnings forecasts. Using data from such firms as Intel, General Electric, and Hitachi, Guerard demonstrates how forecasting tools can be applied to understand the business cycle, evaluate market risk, and demonstrate the impact of global stock selection modeling and portfolio construction.