Using Genetic Algorithms To Find Technical Trading Rules In Financial Markets
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| Author | : Emmanual Acar |
| Publisher | : Elsevier |
| Total Pages | : 468 |
| Release | : 2002-05-23 |
| Genre | : Political Science |
| ISBN | : 0080493432 |
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
| Author | : Shu-Heng Chen |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 491 |
| Release | : 2012-12-06 |
| Genre | : Business & Economics |
| ISBN | : 1461508355 |
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.
| Author | : Richard J. Bauer |
| Publisher | : John Wiley & Sons |
| Total Pages | : 324 |
| Release | : 1994-03-31 |
| Genre | : Business & Economics |
| ISBN | : 9780471576792 |
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.
| Author | : Emmanual Acar |
| Publisher | : Butterworth-Heinemann |
| Total Pages | : 474 |
| Release | : 2002-06-05 |
| Genre | : Business & Economics |
| ISBN | : 9780750655163 |
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
| Author | : Michael W. Covel |
| Publisher | : FT Press |
| Total Pages | : 467 |
| Release | : 2009 |
| Genre | : Business & Economics |
| ISBN | : 013702018X |
Discover the investment strategy that works in any market. The one strategy that works in up and down markets, good times and bad.
| Author | : Anthony Brabazon |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 276 |
| Release | : 2006-03-28 |
| Genre | : Computers |
| ISBN | : 3540313079 |
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.
| Author | : Kurt Dopfer |
| Publisher | : Cambridge University Press |
| Total Pages | : 604 |
| Release | : 2005-05-23 |
| Genre | : Business & Economics |
| ISBN | : 9781139443234 |
It is widely recognised that mainstream economics has failed to translate micro consistently into macro economics and to provide endogenous explanations for the continual changes in the economic system. Since the early 1980s, a growing number of economists have been trying to provide answers to these two key questions by applying an evolutionary approach. This new departure has yielded a rich literature with enormous variety, but the unifying principles connecting the various ideas and views presented are, as yet, not apparent. This 2005 volume brings together fifteen original articles from scholars - each of whom has made a significant contribution to the field - in their common effort to reconstruct economics as an evolutionary science. Using meso economics as an analytical entity to bridge micro and macro economics as well as static and dynamic realms, a unified economic theory emerges.
| Author | : Hans-Paul Schwefel |
| Publisher | : John Wiley & Sons |
| Total Pages | : 408 |
| Release | : 1981 |
| Genre | : Computers |
| ISBN | : |
| Author | : Ramazan Gençay |
| Publisher | : Elsevier |
| Total Pages | : 411 |
| Release | : 2001-05-29 |
| Genre | : Business & Economics |
| ISBN | : 008049904X |
Liquid markets generate hundreds or thousands of ticks (the minimum change in price a security can have, either up or down) every business day. Data vendors such as Reuters transmit more than 275,000 prices per day for foreign exchange spot rates alone. Thus, high-frequency data can be a fundamental object of study, as traders make decisions by observing high-frequency or tick-by-tick data. Yet most studies published in financial literature deal with low frequency, regularly spaced data. For a variety of reasons, high-frequency data are becoming a way for understanding market microstructure. This book discusses the best mathematical models and tools for dealing with such vast amounts of data.This book provides a framework for the analysis, modeling, and inference of high frequency financial time series. With particular emphasis on foreign exchange markets, as well as currency, interest rate, and bond futures markets, this unified view of high frequency time series methods investigates the price formation process and concludes by reviewing techniques for constructing systematic trading models for financial assets.
| Author | : John R. Koza |
| Publisher | : MIT Press |
| Total Pages | : 856 |
| Release | : 1992 |
| Genre | : Computers |
| ISBN | : 9780262111706 |
In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic programming may be more powerful than neural networks and other machine learning techniques, able to solve problems in a wider range of disciplines. In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic Programming contains a great many worked examples and includes a sample computer code that will allow readers to run their own programs.In getting computers to solve problems without being explicitly programmed, Koza stresses two points: that seemingly different problems from a variety of fields can be reformulated as problems of program induction, and that the recently developed genetic programming paradigm provides a way to search the space of possible computer programs for a highly fit individual computer program to solve the problems of program induction. Good programs are found by evolving them in a computer against a fitness measure instead of by sitting down and writing them.
