Using Genetic Algorithms to Find Technical Trading Rules in Financial Markets

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ISBN 13 :
Total Pages : 640 pages
Book Rating : 4.:/5 (187 download)

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Book Synopsis Using Genetic Algorithms to Find Technical Trading Rules in Financial Markets by : Risto Karjalainen

Download or read book Using Genetic Algorithms to Find Technical Trading Rules in Financial Markets written by Risto Karjalainen and published by . This book was released on 1994 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Using Genetic Algorithms to Find Technical Trading Rules

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ISBN 13 :
Total Pages : 58 pages
Book Rating : 4.:/5 (351 download)

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Book Synopsis Using Genetic Algorithms to Find Technical Trading Rules by : Franklin Allen

Download or read book Using Genetic Algorithms to Find Technical Trading Rules written by Franklin Allen and published by . This book was released on 1995 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Using Genetic Algorithms to Find Technical Trading Rules

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ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (247 download)

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Book Synopsis Using Genetic Algorithms to Find Technical Trading Rules by : Christopher J. Neely

Download or read book Using Genetic Algorithms to Find Technical Trading Rules written by Christopher J. Neely and published by . This book was released on 1999 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Mining Optimal Technical Trading Rules with Genetic Algorithms

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ISBN 13 : 9781361276105
Total Pages : pages
Book Rating : 4.2/5 (761 download)

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Book Synopsis Mining Optimal Technical Trading Rules with Genetic Algorithms by : Rujun Shen

Download or read book Mining Optimal Technical Trading Rules with Genetic Algorithms written by Rujun Shen and published by . This book was released on 2017-01-26 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "Mining Optimal Technical Trading Rules With Genetic Algorithms" by Rujun, Shen, 沈汝君, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: In recent years technical trading rules are widely known by more and more people, not only the academics many investors also learn to apply them in financial markets. One approach of constructing technical trading rules is to use technical indicators, such as moving average(MA) and filter rules. These trading rules are widely used possibly because the technical indicators are simple to compute and can be programmed easily. An alternative approach of constructing technical trading rules is to rely on some chart patterns. However, the patterns and signals detected by these rules are often made by the visual inspection through human eyes. As for as I know, there are no universally acceptable methods of constructing the chart patterns. In 2000, Prof. Andrew Lo and his colleagues are the first ones who define five pairs of chart patterns mathematically. They are Head-and-Shoulders(HS) & Inverted Headand- Shoulders(IHS), Broadening tops(BTOP) & bottoms(BBOT), Triangle tops(TTOP) & bottoms(TBOT), Rectangle tops(RTOP) & bottoms( RBOT) and Double tops(DTOP) & bottoms(DBOT). The basic formulation of a chart pattern consists of two steps: detection of (i) extreme points of a price series; and (ii) shape of the pattern. In Lo et al.(2000), the method of kernel smoothing was used to identify the extreme points. It was admitted by Lo et al. (2000) that the optimal bandwidth used in kernel method is not the best choice and the expert judgement is needed in detecting the bandwidth. In addition, their work considered chart pattern detection only but no buy/sell signal detection. It should be noted that it is possible to have a chart pattern formed without a signal detected, but in this case no transaction will be made. In this thesis, I propose a new class of technical trading rules which aims to resolve the above problems. More specifically, each chart pattern is parameterized by a set of parameters which governs the shape of the pattern, the entry and exit signals of trades. Then the optimal set of parameters can be determined by using genetic algorithms (GAs). The advantage of GA is that they can deal with a high-dimensional optimization problems no matter the parameters to be optimized are continuous or discrete. In addition, GA can also be convenient to use in the situation that the fitness function is not differentiable or has a multi-modal surface. DOI: 10.5353/th_b4787001 Subjects: Stocks - Prices - Statistical methods Investments - Statistical methods Genetic algorithms

Genetic Algorithms and Investment Strategies

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Publisher : John Wiley & Sons
ISBN 13 : 9780471576792
Total Pages : 324 pages
Book Rating : 4.5/5 (767 download)

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Book Synopsis Genetic Algorithms and Investment Strategies by : Richard J. Bauer

Download or read book Genetic Algorithms and Investment Strategies written by Richard J. Bauer and published by John Wiley & Sons. This book was released on 1994-03-31 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: When you combine nature's efficiency and the computer's speed, thefinancial possibilities are almost limitless. Today's traders andinvestment analysts require faster, sleeker weaponry in today'sruthless financial marketplace. Battles are now waged at computerspeed, with skirmishes lasting not days or weeks, but mere hours.In his series of influential articles, Richard Bauer has shown whythese professionals must add new computerized decision-making toolsto their arsenal if they are to succeed. In Genetic Algorithms andInvestment Strategies, he uniquely focuses on the most powerfulweapon of all, revealing how the speed, power, and flexibility ofGAs can help them consistently devise winning investmentstrategies. The only book to demonstrate how GAs can workeffectively in the world of finance, it first describes thebiological and historical bases of GAs as well as othercomputerized approaches such as neural networks and chaos theory.It goes on to compare their uses, advantages, and overallsuperiority of GAs. In subsequently presenting a basic optimizationproblem, Genetic Algorithms and Investment Strategies outlines theessential steps involved in using a GA and shows how it mimicsnature's evolutionary process by moving quickly toward anear-optimal solution. Introduced to advanced variations ofessential GA procedures, readers soon learn how GAs can be usedto: * Solve large, complex problems and smaller sets of problems * Serve the needs of traders with widely different investmentphilosophies * Develop sound market timing trading rules in the stock and bondmarkets * Select profitable individual stocks and bonds * Devise powerful portfolio management systems Complete with information on relevant software programs, a glossaryof GA terminology, and an extensive bibliography coveringcomputerized approaches and market timing, Genetic Algorithms andInvestment Strategies unveils in clear, nontechnical language aremarkably efficient strategic decision-making process that, whenimaginatively used, enables traders and investment analysts to reapsignificant financial rewards.

Mining Optimal Technical Trading Rules with Genetic Algorithms

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Publisher :
ISBN 13 :
Total Pages : 138 pages
Book Rating : 4.:/5 (81 download)

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Book Synopsis Mining Optimal Technical Trading Rules with Genetic Algorithms by : Rujun Shen (M. Phil.)

Download or read book Mining Optimal Technical Trading Rules with Genetic Algorithms written by Rujun Shen (M. Phil.) and published by . This book was released on 2011 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Genetic Algorithms and Genetic Programming in Computational Finance

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Publisher : Springer Science & Business Media
ISBN 13 : 1461508355
Total Pages : 491 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Genetic Algorithms and Genetic Programming in Computational Finance by : Shu-Heng Chen

Download or read book Genetic Algorithms and Genetic Programming in Computational Finance written by Shu-Heng Chen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: After a decade of development, genetic algorithms and genetic programming have become a widely accepted toolkit for computational finance. Genetic Algorithms and Genetic Programming in Computational Finance is a pioneering volume devoted entirely to a systematic and comprehensive review of this subject. Chapters cover various areas of computational finance, including financial forecasting, trading strategies development, cash flow management, option pricing, portfolio management, volatility modeling, arbitraging, and agent-based simulations of artificial stock markets. Two tutorial chapters are also included to help readers quickly grasp the essence of these tools. Finally, a menu-driven software program, Simple GP, accompanies the volume, which will enable readers without a strong programming background to gain hands-on experience in dealing with much of the technical material introduced in this work.

Mining Optimal Technical Trading Rules with Genetic Algorithms

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Publisher :
ISBN 13 :
Total Pages : 138 pages
Book Rating : 4.:/5 (81 download)

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Book Synopsis Mining Optimal Technical Trading Rules with Genetic Algorithms by : Rujun Shen (M. Phil.)

Download or read book Mining Optimal Technical Trading Rules with Genetic Algorithms written by Rujun Shen (M. Phil.) and published by . This book was released on 2011 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Advanced Trading Rules

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Publisher : Elsevier
ISBN 13 : 0080493432
Total Pages : 468 pages
Book Rating : 4.0/5 (84 download)

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Book Synopsis Advanced Trading Rules by : Emmanual Acar

Download or read book Advanced Trading Rules written by Emmanual Acar and published by Elsevier. This book was released on 2002-05-23 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Trading Rules is the essential guide to state of the art techniques currently used by the very best financial traders, analysts and fund managers. The editors have brought together the world's leading professional and academic experts to explain how to understand, develop and apply cutting edge trading rules and systems. It is indispensable reading if you are involved in the derivatives, fixed income, foreign exchange and equities markets. Advanced Trading Rules demonstrates how to apply econometrics, computer modelling, technical and quantitative analysis to generate superior returns, showing how you can stay ahead of the curve by finding out why certain methods succeed or fail. Profit from this book by understanding how to use: stochastic properties of trading strategies; technical indicators; neural networks; genetic algorithms; quantitative techniques; charts. Financial markets professionals will discover a wealth of applicable ideas and methods to help them to improve their performance and profits. Students and academics working in this area will also benefit from the rigorous and theoretically sound analysis of this dynamic and exciting area of finance. - The essential guide to state of the art techniques currently used by the very best financial traders, analysts and fund managers - Provides a complete overview of cutting edge financial markets trading rules, including new material on technical analysis and evaluation - Demonstrates how to apply econometrics, computer modeling, technical and quantitative analysis to generate superior returns

Neural Networks in Finance and Investing

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Publisher : Irwin Professional Publishing
ISBN 13 :
Total Pages : 872 pages
Book Rating : 4.:/5 (318 download)

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Book Synopsis Neural Networks in Finance and Investing by : Robert R. Trippi

Download or read book Neural Networks in Finance and Investing written by Robert R. Trippi and published by Irwin Professional Publishing. This book was released on 1996 with total page 872 pages. Available in PDF, EPUB and Kindle. Book excerpt: This completely updated version of the classic first edition offers a wealth of new material reflecting the latest developments in teh field. For investment professionals seeking to maximize this exciting new technology, this handbook is the definitive information source.

Advanced Trading Rules

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Publisher : Butterworth-Heinemann
ISBN 13 : 9780750655163
Total Pages : 474 pages
Book Rating : 4.6/5 (551 download)

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Book Synopsis Advanced Trading Rules by : Emmanual Acar

Download or read book Advanced Trading Rules written by Emmanual Acar and published by Butterworth-Heinemann. This book was released on 2002-06-05 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Trading Rules is the essential guide to state of the art techniques currently used by the very best financial traders, analysts and fund managers. The editors have brought together the world's leading professional and academic experts to explain how to understand, develop and apply cutting edge trading rules and systems. It is indispensable reading if you are involved in the derivatives, fixed income, foreign exchange and equities markets. Advanced Trading Rules demonstrates how to apply econometrics, computer modelling, technical and quantitative analysis to generate superior returns, showing how you can stay ahead of the curve by finding out why certain methods succeed or fail. Profit from this book by understanding how to use: stochastic properties of trading strategies; technical indicators; neural networks; genetic algorithms; quantitative techniques; charts. Financial markets professionals will discover a wealth of applicable ideas and methods to help them to improve their performance and profits. Students and academics working in this area will also benefit from the rigorous and theoretically sound analysis of this dynamic and exciting area of finance. The essential guide to state of the art techniques currently used by the very best financial traders, analysts and fund managers Provides a complete overview of cutting edge financial markets trading rules, including new material on technical analysis and evaluation Demonstrates how to apply econometrics, computer modeling, technical and quantitative analysis to generate superior returns

Genetic Algorithms and Applications for Stock Trading Optimization

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Publisher : IGI Global
ISBN 13 : 1799841065
Total Pages : 262 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Genetic Algorithms and Applications for Stock Trading Optimization by : Kapoor, Vivek

Download or read book Genetic Algorithms and Applications for Stock Trading Optimization written by Kapoor, Vivek and published by IGI Global. This book was released on 2021-06-25 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic algorithms (GAs) are based on Darwin’s theory of natural selection and survival of the fittest. They are designed to competently look for solutions to big and multifaceted problems. Genetic algorithms are wide groups of interrelated events with divided steps. Each step has dissimilarities, which leads to a broad range of connected actions. Genetic algorithms are used to improve trading systems, such as to optimize a trading rule or parameters of a predefined multiple indicator market trading system. Genetic Algorithms and Applications for Stock Trading Optimization is a complete reference source to genetic algorithms that explains how they might be used to find trading strategies, as well as their use in search and optimization. It covers the functions of genetic algorithms internally, computer implementation of pseudo-code of genetic algorithms in C++, technical analysis for stock market forecasting, and research outcomes that apply in the stock trading system. This book is ideal for computer scientists, IT specialists, data scientists, managers, executives, professionals, academicians, researchers, graduate-level programs, research programs, and post-graduate students of engineering and science.

Development of Trading Systems using Genetic Programming with a Case Study

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Publisher : GRIN Verlag
ISBN 13 : 3869436921
Total Pages : 99 pages
Book Rating : 4.8/5 (694 download)

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Book Synopsis Development of Trading Systems using Genetic Programming with a Case Study by : Holger Hartmann

Download or read book Development of Trading Systems using Genetic Programming with a Case Study written by Holger Hartmann and published by GRIN Verlag. This book was released on 2012-03-02 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diploma Thesis from the year 2007 in the subject Computer Science - Programming, grade: 1.7, University of Hamburg, language: English, abstract: In this thesis Genetic Progrmming is used to create trading systems for the EUR/USD foreign exchange market using intraday data. In addition to the exchange rates several moving averages are used as inputs. The developed evolutionary algorithm extends the framework ECJ. The created trading systems are being evaluated by a fitness function that consists of a trading simulation. Genetic operators have been adapted to support "node weights". By using these on the one hand macromutaion is tried to be reduced on the other hand the interpretability of the created trading systems is tried to be improved. Results of experiments show that created trading systems are apparently successfull in profitably using informations contained within the exchange rates. Profits of the created trading systems are maximized by using the optimal position size. It is shown that if the minimum investment period is met the achieved results are optimal even when taking into account the used risk adjusted performance figure.

Evolutionary Algorithms in Optimization of Technical Rules for Automated Stock Trading

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Publisher :
ISBN 13 :
Total Pages : 152 pages
Book Rating : 4.:/5 (129 download)

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Book Synopsis Evolutionary Algorithms in Optimization of Technical Rules for Automated Stock Trading by : Harish K. Subramanian

Download or read book Evolutionary Algorithms in Optimization of Technical Rules for Automated Stock Trading written by Harish K. Subramanian and published by . This book was released on 2004 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: The effectiveness of technical analysis indicators as a means of predicting future price levels and enhancing trading profitability in stock markets is an issue constantly under review. It is an area that has been researched and its profitability examined in foreign exchange trade [1], portfolio management [2] and day trading [3]. Their use has been advocated by many traders [4], [5] and the uses of these charting and analysis techniques are being scrutinized [6], [7]. However, despite their popularity among human traders, a number of popular technical trading rules can be loss-making when applied individually, typically because human technical traders use combinations [8], [9] of a broad range of these technical indicators. Moreover, successful traders tend to adapt to market conditions by varying the weight they give to certain trading rules and dropping some of them as they are deemed to be loss-making. In this thesis, we try to emulate such a strategy by developing trading systems consisting of rules based on combinations of different indicators, and evaluating their profitability in a simulated economy. We propose and empirically examine two schemes, using evolutionary algorithms (genetic algorithm and genetic programming), of optimizing the combination of technical rules. A multiple model approach [10a] is used to control agent behavior and encourage unwinding of share position to ensure a zero final share position (as is essential within the framework that our experiments are run in). Evaluation of the evolutionary composite technical trading strategies leads us to believe that there is substantial merit in such evolutionary designs (particularly the weighted majority model), provided the right learning parameters are used. To explore this possibility, we evaluated a fitness function measure limiting only downside volatility, and compared its behavior and benefits with the classical Sharpe ratio, which uses a measure of standard deviation. The improved performance of the new fitness function strengthens our claim that a weighted majority approach could indeed be useful, albeit with a more sophisticated fitness function

Optimisation of Trading Rules Using Genetic Algorithms

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (643 download)

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Book Synopsis Optimisation of Trading Rules Using Genetic Algorithms by : S. C. Tsai

Download or read book Optimisation of Trading Rules Using Genetic Algorithms written by S. C. Tsai and published by . This book was released on 1997 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Trend Following

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Publisher : FT Press
ISBN 13 : 013702018X
Total Pages : 467 pages
Book Rating : 4.1/5 (37 download)

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Book Synopsis Trend Following by : Michael W. Covel

Download or read book Trend Following written by Michael W. Covel and published by FT Press. This book was released on 2009 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the investment strategy that works in any market. The one strategy that works in up and down markets, good times and bad.

Biologically Inspired Algorithms for Financial Modelling

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Publisher : Springer Science & Business Media
ISBN 13 : 3540313079
Total Pages : 276 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Biologically Inspired Algorithms for Financial Modelling by : Anthony Brabazon

Download or read book Biologically Inspired Algorithms for Financial Modelling written by Anthony Brabazon and published by Springer Science & Business Media. This book was released on 2006-03-28 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predicting the future for financial gain is a difficult, sometimes profitable activity. The focus of this book is the application of biologically inspired algorithms (BIAs) to financial modelling. In a detailed introduction, the authors explain computer trading on financial markets and the difficulties faced in financial market modelling. Then Part I provides a thorough guide to the various bioinspired methodologies – neural networks, evolutionary computing (particularly genetic algorithms and grammatical evolution), particle swarm and ant colony optimization, and immune systems. Part II brings the reader through the development of market trading systems. Finally, Part III examines real-world case studies where BIA methodologies are employed to construct trading systems in equity and foreign exchange markets, and for the prediction of corporate bond ratings and corporate failures. The book was written for those in the finance community who want to apply BIAs in financial modelling, and for computer scientists who want an introduction to this growing application domain.