Stock Market Prediction

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Publisher :
ISBN 13 :
Total Pages : 76 pages
Book Rating : 4.:/5 (31 download)

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Book Synopsis Stock Market Prediction by : Donald A. Bradley

Download or read book Stock Market Prediction written by Donald A. Bradley and published by . This book was released on 1948 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Predicting the Markets of Tomorrow

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Publisher : Penguin
ISBN 13 : 110121838X
Total Pages : 272 pages
Book Rating : 4.1/5 (12 download)

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Book Synopsis Predicting the Markets of Tomorrow by : James P. O'Shaughnessy

Download or read book Predicting the Markets of Tomorrow written by James P. O'Shaughnessy and published by Penguin. This book was released on 2006-03-02 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique and timely new wealth-building strategy from a legendary investment guru In his national bestsellers How to Retire Rich and What Works on Wall Street, portfolio manager extraordinaire James P. O’Shaughnessy offered investors practical advice based on rigorous quantitative analysis—advice that has consistently beaten the market. But in a recent analysis of market data, O’Shaughnessy uncovered some astonishing trends not discussed in his previous books. The Markets of Tomorrow explains O’Shaughnessy’s new research and tells ordinary investors what they must do now to revamp their portfolios. According to O’Shaughnessy, the year 2000 marked the end of a twenty-year cycle that was dominated by the stocks of larger, fastergrowing companies like those in the S&P 500. In the new cycle, the stocks of small and midsize companies are the ones that will outperform the market, along with large company value stocks and intermediate term bonds. O’Shaughnessy describes the number crunching behind his analysis and then shows individual investors exactly how to select the right mix of investments and pick top-performing small and midcap stocks. The Markets of Tomorrow is a loud and clear call to action for every investor who doesn’t want to be left behind.

Stock price Prediction a referential approach on how to predict the stock price using simple time series...

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Author :
Publisher : Clever Fox Publishing
ISBN 13 :
Total Pages : 56 pages
Book Rating : 4./5 ( download)

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Book Synopsis Stock price Prediction a referential approach on how to predict the stock price using simple time series... by : Dr.N.Srinivasan

Download or read book Stock price Prediction a referential approach on how to predict the stock price using simple time series... written by Dr.N.Srinivasan and published by Clever Fox Publishing. This book was released on with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about the various techniques involved in the stock price prediction. Even the people who are new to this book, after completion they can do stock trading individually with more profit.

Head First Python

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491919493
Total Pages : 624 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Head First Python by : Paul Barry

Download or read book Head First Python written by Paul Barry and published by "O'Reilly Media, Inc.". This book was released on 2016-11-21 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Want to learn the Python language without slogging your way through how-to manuals? With Head First Python, you’ll quickly grasp Python’s fundamentals, working with the built-in data structures and functions. Then you’ll move on to building your very own webapp, exploring database management, exception handling, and data wrangling. If you’re intrigued by what you can do with context managers, decorators, comprehensions, and generators, it’s all here. This second edition is a complete learning experience that will help you become a bonafide Python programmer in no time. Why does this book look so different? Based on the latest research in cognitive science and learning theory, Head First Pythonuses a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multi-sensory learning experience is designed for the way your brain really works.

Stock Market Prediction Through Sentiment Analysis of Social-Media and Financial Stock Data Using Machine Learning

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (129 download)

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Book Synopsis Stock Market Prediction Through Sentiment Analysis of Social-Media and Financial Stock Data Using Machine Learning by : Mohammad Al Ridhawi

Download or read book Stock Market Prediction Through Sentiment Analysis of Social-Media and Financial Stock Data Using Machine Learning written by Mohammad Al Ridhawi and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Given the volatility of the stock market and the multitude of financial variables at play, forecasting the value of stocks can be a challenging task. Nonetheless, such prediction task presents a fascinating problem to solve using machine learning. The stock market can be affected by news events, social media posts, political changes, investor emotions, and the general economy among other factors. Predicting the stock value of a company by simply using financial stock data of its price may be insufficient to give an accurate prediction. Investors often openly express their attitudes towards various stocks on social medial platforms. Hence, combining sentiment analysis from social media and the financial stock value of a company may yield more accurate predictions. This thesis proposes a method to predict the stock market using sentiment analysis and financial stock data. To estimate the sentiment in social media posts, we use an ensemble-based model that leverages Multi-Layer Perceptron (MLP), Long Short-Term Memory (LSTM), and Convolutional Neural Network (CNN) models. We use an LSTM model for the financial stock prediction. The models are trained on the AAPL, CSCO, IBM, and MSFT stocks, utilizing a combination of the financial stock data and sentiment extracted from social media posts on Twitter between the years 2015-2019. Our experimental results show that the combination of the financial and sentiment information can improve the stock market prediction performance. The proposed solution has achieved a prediction performance of 74.3%.

Stock Market Prediction and Efficiency Analysis using Recurrent Neural Network

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Publisher : GRIN Verlag
ISBN 13 : 3668800456
Total Pages : 82 pages
Book Rating : 4.6/5 (688 download)

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Book Synopsis Stock Market Prediction and Efficiency Analysis using Recurrent Neural Network by : Joish Bosco

Download or read book Stock Market Prediction and Efficiency Analysis using Recurrent Neural Network written by Joish Bosco and published by GRIN Verlag. This book was released on 2018-09-18 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: Project Report from the year 2018 in the subject Computer Science - Technical Computer Science, , course: Computer Science, language: English, abstract: Modeling and Forecasting of the financial market have been an attractive topic to scholars and researchers from various academic fields. The financial market is an abstract concept where financial commodities such as stocks, bonds, and precious metals transactions happen between buyers and sellers. In the present scenario of the financial market world, especially in the stock market, forecasting the trend or the price of stocks using machine learning techniques and artificial neural networks are the most attractive issue to be investigated. As Giles explained, financial forecasting is an instance of signal processing problem which is difficult because of high noise, small sample size, non-stationary, and non-linearity. The noisy characteristics mean the incomplete information gap between past stock trading price and volume with a future price. The stock market is sensitive with the political and macroeconomic environment. However, these two kinds of information are too complex and unstable to gather. The above information that cannot be included in features are considered as noise. The sample size of financial data is determined by real-world transaction records. On one hand, a larger sample size refers a longer period of transaction records; on the other hand, large sample size increases the uncertainty of financial environment during the 2 sample period. In this project, we use stock data instead of daily data in order to reduce the probability of uncertain noise, and relatively increase the sample size within a certain period of time. By non-stationarity, one means that the distribution of stock data is various during time changing. Non-linearity implies that feature correlation of different individual stocks is various. Efficient Market Hypothesis was developed by Burton G. Malkiel in 1991.

Stock Market Crashes: Predictable And Unpredictable And What To Do About Them

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Publisher : World Scientific
ISBN 13 : 9813223863
Total Pages : 309 pages
Book Rating : 4.8/5 (132 download)

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Book Synopsis Stock Market Crashes: Predictable And Unpredictable And What To Do About Them by : William T Ziemba

Download or read book Stock Market Crashes: Predictable And Unpredictable And What To Do About Them written by William T Ziemba and published by World Scientific. This book was released on 2017-08-30 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Overall, the book provides an interesting and useful synthesis of the authors’ research on the predictions of stock market crashes. The book can be recommended to anyone interested in the Bond Stock Earnings Yield Differential model, and similar methods to predict crashes.'Quantitative FinanceThis book presents studies of stock market crashes big and small that occur from bubbles bursting or other reasons. By a bubble we mean that prices are rising just because they are rising and that prices exceed fundamental values. A bubble can be a large rise in prices followed by a steep fall. The focus is on determining if a bubble actually exists, on models to predict stock market declines in bubble-like markets and exit strategies from these bubble-like markets. We list historical great bubbles of various markets over hundreds of years.We present four models that have been successful in predicting large stock market declines of ten percent plus that average about minus twenty-five percent. The bond stock earnings yield difference model was based on the 1987 US crash where the S&P 500 futures fell 29% in one day. The model is based on earnings yields relative to interest rates. When interest rates become too high relative to earnings, there almost always is a decline in four to twelve months. The initial out of sample test was on the Japanese stock market from 1948-88. There all twelve danger signals produced correct decline signals. But there were eight other ten percent plus declines that occurred for other reasons. Then the model called the 1990 Japan huge -56% decline. We show various later applications of the model to US stock declines such as in 2000 and 2007 and to the Chinese stock market. We also compare the model with high price earnings decline predictions over a sixty year period in the US. We show that over twenty year periods that have high returns they all start with low price earnings ratios and end with high ratios. High price earnings models have predictive value and the BSEYD models predict even better. Other large decline prediction models are call option prices exceeding put prices, Warren Buffett's value of the stock market to the value of the economy adjusted using BSEYD ideas and the value of Sotheby's stock. Investors expect more declines than actually occur. We present research on the positive effects of FOMC meetings and small cap dominance with Democratic Presidents. Marty Zweig was a wall street legend while he was alive. We discuss his methods for stock market predictability using momentum and FED actions. These helped him become the leading analyst and we show that his ideas still give useful predictions in 2016-2017. We study small declines in the five to fifteen percent range that are either not expected or are expected but when is not clear. For these we present methods to deal with these situations.The last four January-February 2016, Brexit, Trump and French elections are analzyed using simple volatility-S&P 500 graphs. Another very important issue is can you exit bubble-like markets at favorable prices. We use a stopping rule model that gives very good exit results. This is applied successfully to Apple computer stock in 2012, the Nasdaq 100 in 2000, the Japanese stock and golf course membership prices, the US stock market in 1929 and 1987 and other markets. We also show how to incorporate predictive models into stochastic investment models.

Deep Learning Tools for Predicting Stock Market Movements

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Publisher : John Wiley & Sons
ISBN 13 : 1394214308
Total Pages : 500 pages
Book Rating : 4.3/5 (942 download)

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Book Synopsis Deep Learning Tools for Predicting Stock Market Movements by : Renuka Sharma

Download or read book Deep Learning Tools for Predicting Stock Market Movements written by Renuka Sharma and published by John Wiley & Sons. This book was released on 2024-05-14 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: DEEP LEARNING TOOLS for PREDICTING STOCK MARKET MOVEMENTS The book provides a comprehensive overview of current research and developments in the field of deep learning models for stock market forecasting in the developed and developing worlds. The book delves into the realm of deep learning and embraces the challenges, opportunities, and transformation of stock market analysis. Deep learning helps foresee market trends with increased accuracy. With advancements in deep learning, new opportunities in styles, tools, and techniques evolve and embrace data-driven insights with theories and practical applications. Learn about designing, training, and applying predictive models with rigorous attention to detail. This book offers critical thinking skills and the cultivation of discerning approaches to market analysis. The book: details the development of an ensemble model for stock market prediction, combining long short-term memory and autoregressive integrated moving average; explains the rapid expansion of quantum computing technologies in financial systems; provides an overview of deep learning techniques for forecasting stock market trends and examines their effectiveness across different time frames and market conditions; explores applications and implications of various models for causality, volatility, and co-integration in stock markets, offering insights to investors and policymakers. Audience The book has a wide audience of researchers in financial technology, financial software engineering, artificial intelligence, professional market investors, investment institutions, and asset management companies.

Valuation Challenges and Solutions in Contemporary Businesses

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Publisher : IGI Global
ISBN 13 : 1799810887
Total Pages : 324 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Valuation Challenges and Solutions in Contemporary Businesses by : Köseo?lu, Sinem Derindere

Download or read book Valuation Challenges and Solutions in Contemporary Businesses written by Köseo?lu, Sinem Derindere and published by IGI Global. This book was released on 2019-11-29 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Defining the value of an entire company can be challenging, especially for large, highly competitive business markets. While the main goal for many companies is to increase their market value, understanding the advanced techniques and determining the best course of action to maximize profits can puzzle both academic and business professionals alike. Valuation Challenges and Solutions in Contemporary Businesses provides emerging research exploring theoretical and practical aspects of income-based, market-based, and asset-based valuation approaches and applications within the financial sciences. Featuring coverage on a broad range of topics such as growth rate, diverse business, and market value, this book is ideally designed for financial officers, business professionals, company managers, CEOs, corporate professionals, academicians, researchers, and students seeking current research on the challenging aspects of firm valuation and an assortment of possible solution-driven concepts.

The Stock Market Barometer; a Study of Its Forecast Value Based on Charles H. Dow's Theory of the Price Movement

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Publisher :
ISBN 13 :
Total Pages : 392 pages
Book Rating : 4.:/5 (2 download)

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Book Synopsis The Stock Market Barometer; a Study of Its Forecast Value Based on Charles H. Dow's Theory of the Price Movement by : William Peter Hamilton

Download or read book The Stock Market Barometer; a Study of Its Forecast Value Based on Charles H. Dow's Theory of the Price Movement written by William Peter Hamilton and published by . This book was released on 1922 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Divining the Dow

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Publisher : Irwin Professional Publishing
ISBN 13 : 9781557384751
Total Pages : 186 pages
Book Rating : 4.3/5 (847 download)

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Book Synopsis Divining the Dow by : Richard J. Maturi

Download or read book Divining the Dow written by Richard J. Maturi and published by Irwin Professional Publishing. This book was released on 1993 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: "With myriad investment books on the market that specialize in discussing one, two or a half-dozen investment predictors, indicators, theories and/or strategies, what more can be said?" "Divining the Dow, by Richard J. Maturi, is a one-of-a-kind guide to stock market prediction systems that provides concise descriptions of 100 of the most important stock prediction systems in use, and lets you evaluate them yourself - you can then choose the one that best fits your investing needs and strategies." "Divining the Dow illustrates how the system works, who uses it, where to get more information, and, where appropriate, includes graphs and charts that clearly demonstrate how the system works."--BOOK JACKET.Title Summary field provided by Blackwell North America, Inc. All Rights Reserved

The Stock Market Barometer

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Publisher :
ISBN 13 :
Total Pages : 360 pages
Book Rating : 4.:/5 (2 download)

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Book Synopsis The Stock Market Barometer by : William Peter Hamilton

Download or read book The Stock Market Barometer written by William Peter Hamilton and published by . This book was released on 1922 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Stock Market Prediction Using Machine Learning and Deep Learning

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Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.2/5 (98 download)

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Book Synopsis Stock Market Prediction Using Machine Learning and Deep Learning by : Amir Ebrahimi

Download or read book Stock Market Prediction Using Machine Learning and Deep Learning written by Amir Ebrahimi and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last century, the stock market has had several notable growths and declines. Prediction and analysis of financial markets, such as Stock Market prediction, have always been challenging for investors worldwide due to the non-linear nature of financial markets. With the help of Data Science, Machine Learning, and Deep Learning, prediction in Stock Market has become feasible and more reliable. This research aims to find the most accurate models for Stock Market prediction by utilizing machine learning and deep learning algorithms, such as Support Vector Regression (SVR), Long Short-term Memory (LSTM), and Random Forest Regression. Several technical analysis indicators are utilized in the models as features to improve the accuracy of the models. In addition, several transactional signals are generated and used as input features into each prediction model. Our models' training and testing performance are evaluated using Root-Mean-Square Error (RMSE) to find the average error for each model. The evaluations indicate how the models are efficient for predicting the stock price.

Prediction of Stock Market Index Movements with Machine Learning

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Publisher : Özgür Publications
ISBN 13 : 975447821X
Total Pages : 121 pages
Book Rating : 4.7/5 (544 download)

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Book Synopsis Prediction of Stock Market Index Movements with Machine Learning by : Nazif AYYILDIZ

Download or read book Prediction of Stock Market Index Movements with Machine Learning written by Nazif AYYILDIZ and published by Özgür Publications. This book was released on 2023-12-16 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book titled "Prediction of Stock Market Index Movements with Machine Learning" focuses on the performance of machine learning methods in forecasting the future movements of stock market indexes and identifying the most advantageous methods that can be used across different stock exchanges. In this context, applications have been conducted on both developed and emerging market stock exchanges. The stock market indexes of developed countries such as NYSE 100, NIKKEI 225, FTSE 100, CAC 40, DAX 30, FTSE MIB, TSX; and the stock market indexes of emerging countries such as SSE, BOVESPA, RTS, NIFTY 50, IDX, IPC, and BIST 100 were selected. The movement directions of these stock market indexes were predicted using decision trees, random forests, k-nearest neighbors, naive Bayes, logistic regression, support vector machines, and artificial neural networks methods. Daily dataset from 01.01.2012 to 31.12.2021, along with technical indicators, were used as input data for analysis. According to the results obtained, it was determined that artificial neural networks were the most effective method during the examined period. Alongside artificial neural networks, logistic regression and support vector machines methods were found to predict the movement direction of all indexes with an accuracy of over 70%. Additionally, it was noted that while artificial neural networks were identified as the best method, they did not necessarily achieve the highest accuracy for all indexes. In this context, it was established that the performance of the examined methods varied among countries and indexes but did not differ based on the development levels of the countries. As a conclusion, artificial neural networks, logistic regression, and support vector machines methods are recommended as the most advantageous approaches for predicting stock market index movements.

Predicting Forex and Stock Market with Fractal Pattern

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Publisher : www.algotrading-investment.com
ISBN 13 :
Total Pages : 330 pages
Book Rating : 4./5 ( download)

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Book Synopsis Predicting Forex and Stock Market with Fractal Pattern by : Young Ho Seo

Download or read book Predicting Forex and Stock Market with Fractal Pattern written by Young Ho Seo and published by www.algotrading-investment.com. This book was released on 2020-04-09 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: About this book This book provides you the powerful and brand new knowledge on predicting financial market that we have discovered in several years of our own research and development work. This book will help you to turn your intuition into the scientific prediction method. In the course of recognizing the price patterns in the chart of Forex and Stock market, you should be realized that it was your intuition working at the background for you. The geometric prediction devised in this book will show you the scientific way to predict the financial market using your intuition. Many of us made a mistake of viewing the financial market with deterministic cycle. Even though we knew that market would not show us such a simple prediction pattern, we never stop using the concept of deterministic cycle to predict the financial market, for example, using Fourier transform, and other similar techniques. Why is that so? The reason is simple. It is because no one presented an effective way of predicting stochastic cycle. Stochastic cycle is the true face of the financial market because many variables in the market are suppressing the predictable cycle with fixed time interval. So how we predict the stochastic cycle present in the financial market? The key to answer is the Fractal Pattern and Fractal Wave. The geometric prediction on Fractal Wave solves the puzzles of the stochastic cycle modelling problem together. In another words, your intuition, more precisely your capability to recognize geometric shape, is more powerful than any other technical indicators available in the market. Hence, the geometric prediction, which comes from your intuition, would maximize your ability to trade in the financial market. In this book, Geometric prediction is described as the combined ability to recognize the geometric regularity and statistical regularity from the chart. We provide the examples of geometric regularity and statistical regularity. In addition, we will show you how these regularities are related to your intuition. The chart patterns covered in this book include support, resistance, Fibonacci Price pattern, Harmonic Pattern, Falling Wedge pattern, Rising Wedge pattern, and Gann Angles with probability. We use these chart patterns to detect geometric regularity. Then, we use the turning point probability as the mean of detecting statistical regularity. In our trading, we combine both to improve the trading performance.

Stock Market Modeling and Forecasting

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Publisher : Springer
ISBN 13 : 1447151550
Total Pages : 166 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Stock Market Modeling and Forecasting by : Xiaolian Zheng

Download or read book Stock Market Modeling and Forecasting written by Xiaolian Zheng and published by Springer. This book was released on 2013-04-05 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Technical Analysis and Stock Market Profits

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Publisher : Harriman House Limited
ISBN 13 : 1897597568
Total Pages : 472 pages
Book Rating : 4.8/5 (975 download)

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Book Synopsis Technical Analysis and Stock Market Profits by : R. Schabacker

Download or read book Technical Analysis and Stock Market Profits written by R. Schabacker and published by Harriman House Limited. This book was released on 2021-02-15 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.