Genetic Algorithms And Investment Strategies PDF Download
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Author | : Richard J. Bauer |
Publisher | : John Wiley & Sons |
Total Pages | : 324 |
Release | : 1994-03-31 |
Genre | : Business & Economics |
ISBN | : 9780471576792 |
Download Genetic Algorithms and Investment Strategies Book in PDF, ePub and Kindle
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 | : Fan Zhang |
Publisher | : |
Total Pages | : 0 |
Release | : 2013 |
Genre | : Genetic algorithms |
ISBN | : |
Download Use of Genetic Algorithms for Optimal Investment Strategies Book in PDF, ePub and Kindle
In this project, a genetic algorithm (GA) is used in the development of investment strategies to decide the optimum asset allocations that back up a portfolio of term insurance contracts and the re-balancing strategy to respond to the changing financial markets, such as change in interest rates and mortality experience. The objective function used as the target to be maximized in GA allows us to accommodate three objectives that should be of interest to the management in insurance companies. The three objectives under consideration are maximizing the total value of wealth at the end of the period, minimizing the variance of the total value of the wealth across the simulated interest rate scenarios and achieving consistent returns on the portfolio from year to year. One objective may be in conflict with another, and GA tries to find a solution, among the large searching space of all the solutions, that favors a particular objective as specified by the user while not worsening other objectives too much. Duration matching, a popular approach to manage risks underlying the traditional life insurance portfolios, is used as a benchmark to examine the effectiveness of the strategies obtained through the use of genetic algorithms. Experiments are conducted to compare the performance of the investment strategy proposed by the genetic algorithm to the duration matching strategy in terms of the different objectives under the testing scenarios. The results from the experiments successfully illustrate that with the help of GA, we are able to find a strategy very similar to the strategy from duration matching. We are also able to find other strategies that could outperform duration matching in terms of some of the desired objectives and are robust in the tested changing environment of interest rate and mortality.
Author | : Kapoor, Vivek |
Publisher | : IGI Global |
Total Pages | : 262 |
Release | : 2021-06-25 |
Genre | : Computers |
ISBN | : 1799841065 |
Download Genetic Algorithms and Applications for Stock Trading Optimization Book in PDF, ePub and Kindle
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.
Author | : António M.L. Canelas |
Publisher | : Springer Science & Business Media |
Total Pages | : 90 |
Release | : 2012-09-28 |
Genre | : Computers |
ISBN | : 3642331092 |
Download Investment Strategies Optimization based on a SAX-GA Methodology Book in PDF, ePub and Kindle
This book presents a new computational finance approach combining a Symbolic Aggregate approximation (SAX) technique with an optimization kernel based on genetic algorithms (GA). While the SAX representation is used to describe the financial time series, the evolutionary optimization kernel is used in order to identify the most relevant patterns and generate investment rules. The proposed approach considers several different chromosomes structures in order to achieve better results on the trading platform The methodology presented in this book has great potential on investment markets.
Author | : Coulibaly Oumar Baba |
Publisher | : |
Total Pages | : 300 |
Release | : 2007 |
Genre | : Investment analysis |
ISBN | : |
Download Using Genetic Algorithms to Develop Investment Strategies for the Malaysian Stock Market Book in PDF, ePub and Kindle
Author | : Shu-Heng Chen |
Publisher | : Springer Science & Business Media |
Total Pages | : 491 |
Release | : 2012-12-06 |
Genre | : Business & Economics |
ISBN | : 1461508355 |
Download Genetic Algorithms and Genetic Programming in Computational Finance Book in PDF, ePub and Kindle
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 | : Bonnie M. Shapbell |
Publisher | : |
Total Pages | : 134 |
Release | : 2000 |
Genre | : Genetic algorithms |
ISBN | : |
Download Selecting a Debt Repayment/investment Strategy Using a Genetic Algorithm Book in PDF, ePub and Kindle
Author | : Antonio Gorgulho |
Publisher | : Springer Science & Business Media |
Total Pages | : 85 |
Release | : 2012-09-27 |
Genre | : Business & Economics |
ISBN | : 3642329888 |
Download Intelligent Financial Portfolio Composition based on Evolutionary Computation Strategies Book in PDF, ePub and Kindle
The management of financial portfolios or funds constitutes a widely known problematic in financial markets which normally requires a rigorous analysis in order to select the most profitable assets. This subject is becoming popular among computer scientists which try to adapt known Intelligent Computation techniques to the market’s domain. This book proposes a potential system based on Genetic Algorithms, which aims to manage a financial portfolio by using technical analysis indicators. The results are promising since the approach clearly outperforms the remaining approaches during the recent market crash.
Author | : Dongjun Wu |
Publisher | : |
Total Pages | : 158 |
Release | : 1997 |
Genre | : |
ISBN | : |
Download Using Genetic Algorithms to Detemine Near-optimal Pricing, Investment and Operating Strategies in the Electric Power Indutry Book in PDF, ePub and Kindle
Author | : Management Association, Information Resources |
Publisher | : IGI Global |
Total Pages | : 1534 |
Release | : 2020-12-05 |
Genre | : Computers |
ISBN | : 1799880990 |
Download Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms Book in PDF, ePub and Kindle
Genetic programming is a new and evolutionary method that has become a novel area of research within artificial intelligence known for automatically generating high-quality solutions to optimization and search problems. This automatic aspect of the algorithms and the mimicking of natural selection and genetics makes genetic programming an intelligent component of problem solving that is highly regarded for its efficiency and vast capabilities. With the ability to be modified and adapted, easily distributed, and effective in large-scale/wide variety of problems, genetic algorithms and programming can be utilized in many diverse industries. This multi-industry uses vary from finance and economics to business and management all the way to healthcare and the sciences. The use of genetic programming and algorithms goes beyond human capabilities, enhancing the business and processes of various essential industries and improving functionality along the way. The Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms covers the implementation, tools and technologies, and impact on society that genetic programming and algorithms have had throughout multiple industries. By taking a multi-industry approach, this book covers the fundamentals of genetic programming through its technological benefits and challenges along with the latest advancements and future outlooks for computer science. This book is ideal for academicians, biological engineers, computer programmers, scientists, researchers, and upper-level students seeking the latest research on genetic programming.