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Genetic Algorithms and Investment Strategies (Wiley Finance)

Genetic Algorithms and Investment Strategies (Wiley Finance)
Publisher
 Wiley
Published
 February 1994
ISBN
 0471576794
$75.00 List Price
$75.00 OUR PRICE
Sales Rank: 588,351
AVAILABILITY:
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When you combine nature’s efficiency and the computer’s speed, the financial possibilities are almost limitless. Today’s traders and investment analysts require faster, sleeker weaponry in today’s ruthless financial marketplace. Battles are now waged at computer speed, with skirmishes lasting not days or weeks, but mere hours. In his series of influential articles, Richard Bauer has shown why these professionals must add new computerized decision-making tools to their arsenal if they are to succeed. In Genetic Algorithms and Investment Strategies, he uniquely focuses on the most powerful weapon of all, revealing how the speed, power, and flexibility of GAs can help them consistently devise winning investment strategies. The only book to demonstrate how GAs can work effectively in the world of finance, it first describes the biological and historical bases of GAs as well as other computerized approaches such as neural networks and chaos theory. It goes on to compare their uses, advantages, and overall superiority of GAs. In subsequently presenting a basic optimization problem, Genetic Algorithms and Investment Strategies outlines the essential steps involved in using a GA and shows how it mimics nature’s evolutionary process by moving quickly toward a near-optimal solution. Introduced to advanced variations of essential GA procedures, readers soon learn how GAs can be used to:

  • Solve large, complex problems and smaller sets of problems
  • Serve the needs of traders with widely different investment philosophies
  • Develop sound market timing trading rules in the stock and bond markets
  • Select profitable individual stocks and bonds
  • Devise powerful portfolio management systems
Complete with information on relevant software programs, a glossary of GA terminology, and an extensive bibliography covering computerized approaches and market timing, Genetic Algorithms and Investment Strategies unveils in clear, nontechnical language a remarkably efficient strategic decision-making process that, when imaginatively used, enables traders and investment analysts to reap significant financial rewards.

Product Reviews

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Average rating: 3.5
A worthy introduction complete with examples Rating
December 30, 2003 Rating: 5.0 stars

After I read this book I read the review from 1998. I was quite surprised that the prior reviewer felt that way. The book provides an introduction to developing the data required for testing, a methodology for developing a study that would be useful in investment practice. This is a quality effort. This book will not provide (or promise) the reader a turnkey system for conquering the market, however there is a framework for future research.

This book was written in 1994, before many of the books dealing with Neural Networks came out, and so the terminology will seem unfamiliar. If you are willing to work through these differences (and it is not too hard) then there is a great deal to learn here.

Bauer predicted (in 1994) that Genetic Algorithms would become widely used. Bauer also predicted that much of the development would be done in secret. I have not come across them in the last few years and at very least I would have expected to see them as signals for sale from system developers. Additionally, there are a series of books like this one that should have appeared since 1994. A search of Amazon using Genetic Algorithm as the subject and sorting by publication date returns 133 titles. I reviewed these titles and did not find any further investment focused titles. I will use this book as a starting point for my research.

My next book will be Melanie Mitchell's "Introduction to GAs".

Does not provide what it promises to Rating
March 10, 1998 Rating: 2.0 stars

The author presents a general introduction into ga's , then moves over to investment strategies and presents solutions.

Unfortunately, he does NOT give background information on the really interesting things like string patterns used, crossover and fitness function and the like. Futhermore, more than one third of the book is filled with endless tables whose content the reader understands after the first table. I guess it makes for a larger book.

conclusion: very disappointing.

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