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.

Download or read book Genetic Algorithms in Applications written by Rustem Popa and published by BoD – Books on Demand. This book was released on 2012-03-21 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic Algorithms (GAs) are one of several techniques in the family of Evolutionary Algorithms - algorithms that search for solutions to optimization problems by "evolving" better and better solutions. Genetic Algorithms have been applied in science, engineering, business and social sciences. This book consists of 16 chapters organized into five sections. The first section deals with some applications in automatic control, the second section contains several applications in scheduling of resources, and the third section introduces some applications in electrical and electronics engineering. The next section illustrates some examples of character recognition and multi-criteria classification, and the last one deals with trading systems. These evolutionary techniques may be useful to engineers and scientists in various fields of specialization, who need some optimization techniques in their work and who may be using Genetic Algorithms in their applications for the first time. These applications may be useful to many other people who are getting familiar with the subject of Genetic Algorithms.

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.

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.

Download or read book Stock Exchange Trading Using Grid Pattern Optimized by A Genetic Algorithm with Speciation written by Tiago Martins and published by Springer Nature. This book was released on 2021-07-08 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a genetic algorithm that optimizes a grid template pattern detector to find the best point to trade in the SP 500. The pattern detector is based on a template using a grid of weights with a fixed size. The template takes in consideration not only the closing price but also the open, high, and low values of the price during the period under testing in contrast to the traditional methods of analysing only the closing price. Each cell of the grid encompasses a score, and these are optimized by an evolutionary genetic algorithm that takes genetic diversity into consideration through a speciation routine, giving time for each individual of the population to be optimized within its own niche. With this method, the system is able to present better results and improves the results compared with other template approaches. The tests considered real data from the stock market and against state-of-the-art solutions, namely the ones using a grid of weights which does not have a fixed size and non-speciated approaches. During the testing period, the presented solution had a return of 21.3% compared to 10.9% of the existing approaches. The use of speciation was able to increase the returns of some results as genetic diversity was taken into consideration.

Download or read book Genetic Algorithms in Applications written by Rustem Popa and published by IntechOpen. This book was released on 2012-03-21 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic Algorithms (GAs) are one of several techniques in the family of Evolutionary Algorithms - algorithms that search for solutions to optimization problems by "evolving" better and better solutions. Genetic Algorithms have been applied in science, engineering, business and social sciences. This book consists of 16 chapters organized into five sections. The first section deals with some applications in automatic control, the second section contains several applications in scheduling of resources, and the third section introduces some applications in electrical and electronics engineering. The next section illustrates some examples of character recognition and multi-criteria classification, and the last one deals with trading systems. These evolutionary techniques may be useful to engineers and scientists in various fields of specialization, who need some optimization techniques in their work and who may be using Genetic Algorithms in their applications for the first time. These applications may be useful to many other people who are getting familiar with the subject of Genetic Algorithms.

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

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

Download or read book Advances in Computation and Intelligence written by Zhihua Cai and published by Springer Science & Business Media. This book was released on 2010-10-06 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volumes CCIS 107 and LNCS 6382 constitute the proceedings of the 5th International Symposium, ISICA 2010, held in Wuhan, China, in October 2010. ISICA 2010 attracted 267 submissions and through rigorous reviews 53 papers were included in LNCS 6382. The papers are presented in sections on ANT colony and particle swarm optimization, differential evolution, distributed computing, genetic algorithms, multi-agent systems, multi-objective and dynamic optimization, robot intelligence, statistic learning and system design.

Download or read book An Introduction to High Frequency Finance written by Ramazan Gençay and published by Elsevier. This book was released on 2001-05-29 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book The Evolutionary Foundations of Economics written by Kurt Dopfer and published by Cambridge University Press. This book was released on 2005-05-23 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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.

Download or read book Artificial Intelligence in Asset Management written by Söhnke M. Bartram and published by CFA Institute Research Foundation. This book was released on 2020-08-28 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and return forecasts and more complex constraints. Trading algorithms use AI to devise novel trading signals and execute trades with lower transaction costs. AI also improves risk modeling and forecasting by generating insights from new data sources. Finally, robo-advisors owe a large part of their success to AI techniques. Yet the use of AI can also create new risks and challenges, such as those resulting from model opacity, complexity, and reliance on data integrity.

Download or read book New Frontier In Evolutionary Algorithms Theory And Applications written by Iba Hitoshi and published by Imperial College Press. This book was released on 2011-08-26 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book delivers theoretical and practical knowledge of Genetic Algorithms (GA) for the purpose of practical applications. It provides a methodology for a GA-based search strategy with the integration of several Artificial Life and Artificial Intelligence techniques, such as memetic concepts, swarm intelligence, and foraging strategies. The development of such tools contributes to better optimizing methodologies when addressing tasks from areas such as robotics, financial forecasting, and data mining in bioinformatics.The emphasis of this book is on applicability to the real world. Tasks from application areas - optimization of the trading rule in foreign exchange (FX) and stock prices, economic load dispatch in power system, exit/door placement for evacuation planning, and gene regulatory network inference in bioinformatics - are studied, and the resultant empirical investigations demonstrate how successful the proposed approaches are when solving real-world tasks of great importance.

Download or read book Computational Science ICCS 2004 written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Using Genetic Algorithms for Robust Optimization in Financial Applications written by Olivier V. Pictet and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this study, optimal indicators and strategies for foreign exchange trading models are investigated in the framework of genetic algorithms. We first explain how the relevant quantities of our application can be encoded in quot;genesquot; so as to fit the requirements of the genetic evolutionary optimization technique. In financial problems, sharp peaks of high fitness are usually not representative of a general solution but, rather, indicative of some accidental fluctuations. Such fluctuations may arise out of inherent noise in the time series or due to threshold effects in the trading model performance. Peaks in such a discontinuous, noisy and multimodal fitness space generally correspond to trading models which will not perform well in out-of-sample tests. In this paper we show that standard genetic algorithms will be quickly attracted to one of the accidental peaks of the fitness space whereas genetic algorithms for multimodal functions employing clustering and a specially designed fitness sharing scheme will find optimal parameters which correspond to broad regions where the fitness function is higher on average. The optimization and the quality tests have been performed over eight years of high frequency data of the main foreign exchange rates. The authors acknowledge a careful review of the manuscript by Rakhal D. Dave and useful discussions with Ulrich M. Muller. The Swiss National Science Foundation is gratefully acknowledged for its financial support.

Download or read book Recent Advances in Simulated Evolution and Learning written by K. C. Tan and published by World Scientific. This book was released on 2004 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the latest advances in the theories, algorithms, and applications of simulated evolution and learning techniques. It provides insights into different evolutionary computation techniques and their applications in domains such as scheduling, control and power, robotics, signal processing, and bioinformatics. The book will be of significant value to all postgraduates, research scientists and practitioners dealing with evolutionary computation or complex real-world problems.