Investment Science

by David G. Luenberger

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.

Genres: Finance, Economics, Reference, Mathematics, Textbooks, Business, Nonfiction

512 pages, Hardcover

First published February 15, 2013

Reviews

[Jim Brown]

to get the solutions manual email: footofpride@adelphia.net

[T · Rating 5 out of 5]

I've read Ch 5-9, 11, and 15. That was enough to take me from knowing nothing about portfolio analysis, to writing Python scripts that will solve for -- and simulate -- portfolios that are on the log-optimal frontier. This book is generally very clear and explains the concepts with enough rigor that you will believe them, but without being so rigorous that you are distracted from the actual application and implementation of the concepts. The reader would benefit from having a background in probability, linear algebra, and optimization. Even if you're not comfortable with optimization, Luenberger gives the sufficient conditions for optimality whenever possible; these are often linear. Thus you can skip solving a quadratic program and simply plug the linear conditions into your preferred linear equation solver and boom: optimized portfolios.

Of course I will be reading more books to gain deeper knowledge and better computational strategies, but this book has set me on an excellent course to make multi-period investment decisions that are smarter and more quantitative than just spending money on hunches or letting my money sit in index funds. Highly recommended if you have a strong background in math and want to learn about finance and investing.

[Ayushman Bahuguna · Rating 4 out of 5]

nice

[Huston · Rating 4 out of 5]

Read first half of book for upperclassman-level finance course (Ch. 1-9)

Highly theoretical treatment of mean-variance portfolio theory; more beneficial for graduate (PhD) student in Finance seeking a mathematically rigorous treatment of investment theory than for an undergraduate seeking practicable applications.

End of chapter problems test mathematical ability without much real-life application.

Would recommend prior knowledge of theoretical linear algebra (kernel, rank-nullity theorem, matrix inverse, etc.) and Multivariable Calculus/Optimization (Lagrangian multipliers).

Overall, good at what it does, but don't expect to learn how to go out and build a successful portfolio with only this book. Extremely good for learning mathematics needed for stock analysis however.

[Haim Cohen · Rating 4 out of 5]

Great book to understand options pricing models. Clear explanations accompanied by examples.