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 | | Investment Science by David G. Luenberger ISBN-10: 0195108094 ISBN-10: 0-19-510809-4 ISBN-13: 9780195108095 ISBN-13: 978-0-19-510809-5 Hardcover 1997-07-03 Oxford University Press, USA Find Lowest Price |
Editorials | ||
Product Description Fueled in part by some extraordinary theoretical developments in finance, an explosive growth of information and computing technology, and the global expansion of investment activity, investment theory currently commands a high level of intellectual attention. Recent developments in the field are being infused into university classrooms, financial service organizations, business ventures, and into the awareness of many individual investors. Modern investment theory using the language of mathematics is now an essential aspect of academic and practitioner training. Representing a breakthrough in the organization of finance topics, Investment Science will be an indispensable tool in teaching modern investment theory. It presents sound fundamentals and shows how real problems can be solved with modern, yet simple, methods. David Luenberger gives thorough yet highly accessible mathematical coverage of standard and recent topics of introductory investments: fixed-income securities, modern portfolio theory and capital asset pricing theory, derivatives (futures, options, and swaps), and innovations in optimal portfolio growth and valuation of multiperiod risky investments. Throughout the book, he uses mathematics to present essential ideas of investments and their applications in business practice. The creative use of binomial lattices to formulate and solve a wide variety of important finance problems is a special feature of the book. In moving from fixed-income securities to derivatives, Luenberger increases naturally the level of mathematical sophistication, but never goes beyond algebra, elementary statistics/probability, and calculus. He includes appendices on probability and calculus at the end of the book for student reference. Creative examples and end-of-chapter exercises are also included to provide additional applications of principles given in the text. Ideal for investment or investment management courses in finance, engineering economics, operations research, and management science departments, Investment Science has been successfully class-tested at Boston University, Stanford University, and the University of Strathclyde, Scotland, and used in several firms where knowledge of investment principles is essential. Executives, managers, financial analysts, and project engineers responsible for evaluation and structuring of investments will also find the book beneficial. The methods described are useful in almost every field, including high-technology, utilities, financial service organizations, and manufacturing companies. | ||
Reviews | ||
The book's a book The book was fine, but the shipping was absolutely horrible. This is the first and last time I ever try to buy a textbook online - I hate UPS! | ||
It might be a good finance book, but it's a terrible math book. Too often, explanations, examples, and problems do not clearly explain the meanings of variables and applicable assumptions. This poor presentation of material makes the book barely usable to someone trying to learn the material for the first time. | ||
superb coverage of subject matter Prof. Luenberger currently teaches at Stanford and this book is used as the textbook for a 2-quarter series in investment science there. The coverage is concise and the math is manageable and yet extremely practical. I agree that this an excellent self-study book in the subject of investment science. | ||
good but not excellent This book serves very good introduction to mathematical finance. Particularly, I enjoyed the discussion of bonds immunization, mean-variance theory, CAPM, APT. It's most suitable for senior undergraduates or any junior graduate students. But it doesn't deserve 5 star for the following reasons: 1) Most of the theories discussed so far in the book are TOO idealized and over simplified. Financial data is dynamic and massive. In model quantitative/computational finance, the most important thing is to understand what the data says rather than what one thinks the data structure might be. With the book, one probably can only do some macroeconomic/very coarse analysis. Author should incorporate more data analysis evidence together with proposed theories. 2) The proof of ito's lemma is wrong(i.e. "Deltaz^2 --> deterministic as Deltat --> 0"). It's surprising since most books make the same mistake. It is the law of the large number contributes to the equality!(i.e. integration sense). The misunderstanding of the proof might lead to the misunderstanding of the hedging process. 3) In the commodity option pricing session, author demonstrated the use of futher market to price the option. This should be discussed further (i.e. black's model). 4) The volatility pumping session should be further researched. The explanation is not satisfactory. | ||
Good book to understand quantitative finance Luenberger was a professor of optimization and his books on that subject are also very good. Clear and Precise. But sometimes he is extremely concise, so that you need to work a bit to completely understand a point. In this book, we have again the same style (after all, it is the author style): Clear and precise book, GOOD choice of notation (I cant say the same thing about HULL's books) but sometimes extremely concise. Overall, a good book to start learning and on a solid foundation. | ||