In my first year as an undergraduate in computer science at the University of Illinois, I took two classes that set the course for my 54-year career (6 years at TRW Systems aerospace firm, and 48 years teaching at Harvard and Princeton Universities): 1) introduction to optimization, and 2) computer algorithms. These topics continue to fascinate me, especially as they relate to improving investment performance via modern optimization technology and data sciences. Optimization plays a critical role in many domains, including supply chains, quantitative finance, and machine learning algorithms. Everyone interested in improving performance ought to understand the successful uses of this proven technology.
As a loyal Princeton University alum, Jack Bogle often visited us and participated in discussions at the Bendheim Center for Finance, at our investment workshops, and at reunions, as well as lectures in my and others’ courses at Princeton. Jack had a remarkable ability to take a complicated problem and distill it into simple, intuitive, and understandable terms.
This highly readable book provides several topics worth studying for individuals interested in improving their wealth and risk management activities. It shows Jack’s philosophy and his direct attitude to managing money to minimize costs; it provides an excellent starting point for establishing sound investing steps.
John C. Bogle shares his extensive insights on investing in mutual funds
Since the first edition of Common Sense on Mutual Funds was published in 1999, much has changed, and no one is more aware of this than mutual fund pioneer John Bogle. Now, in this completely updated Second Edition, Bogle returns to take another critical look at the mutual fund industry and help investors navigate their way through the staggering array of investment alternatives that are available to them.
Written in a straightforward and accessible style, this reliable resource examines the fundamentals of mutual fund investing in today's turbulent…
This book is an outgrowth of a course at Stanford University on applying quantitative methods to improve financial decision making.
Professor Luenberger has a superior talent at writing clear and logical textbooks on optimization topics. He shows the benefits of employing nonlinear programs for several applications, including pricing complex options, and achieving rebalancing gains over time. In his telling, volatility provides an opportunity to improve performance. The linkage of optimization and investing is a special treat.
Investment Science, Second Edition, provides thorough and highly accessible mathematical coverage of the fundamental topics of intermediate investments, including fixed-income securities, capital asset pricing theory, derivatives, and innovations in optimal portfolio growth and valuation of multi-period risky investments. Eminent scholar and teacher David G. Luenberger, known for his ability to make complex ideas simple, presents essential ideas of investments and their applications, offering students the most comprehensive treatment of the subject available. New to this edition Three new chapters: Risk Management, Credit Risk, and Data and Statistics Updated content and expanded coverage of many topics, including the capital asset pricing…
Ed Thorp is one of the most successful quantitative investors of all time. He proved the advantages of a systematic approach to take advantage of special edges that occur from time to time in markets and even games of chance – such as card counting in Blackjack.
The underlying strategy is to maximize the expected log of capital – sometimes called the growth optimal or Kelly strategy. This strategy has multiple benefits but can suffer from limitations – as reviewed in this book – including the chances of large drawdown during shorter time periods.
Still, the growth optimal strategy provides an upper bound on pursuing leverage and taking excessive risks, providing a motivation for systematic risk controls and the enduring advantage of long-short strategies such as betting-against-beta.
This volume provides the definitive treatment of fortune's formula or the Kelly capital growth criterion as it is often called. The strategy is to maximize long run wealth of the investor by maximizing the period by period expected utility of wealth with a logarithmic utility function. Mathematical theorems show that only the log utility function maximizes asymptotic long run wealth and minimizes the expected time to arbitrary large goals. In general, the strategy is risky in the short term but as the number of bets increase, the Kelly bettor's wealth tends to be much larger than those with essentially different…
There is much evidence that individuals often suffer from inertia when it comes to making significant decisions – including investment choices.
This engaging book by Professor Milkman at the Wharton School aims to create a climate in which “change” can be accomplished in an efficient, systematic, and relatively painless way. There are numerous examples of improvements by both individuals and organizations. This highly readable book is a must for anyone interested in creating and sustaining positive change habits, for example, to encourage increased savings and systematic investment policies.
Professor Milkman is one of our successful undergraduate alums and participates on the advisor committee of the ORFE Department at Princeton. She is a terrific teacher and writer. The lessons in this book are most appropriate for investors who are interested in establishing and maintaining sound habits to improve their investment performance.
'Game-changing. Katy Milkman shows in this book that we can all be a super human' Angela Duckworth, bestselling author of Grit
How to Change is a powerful, groundbreaking blueprint to help you - and anyone you manage, teach or coach - to achieve personal and professional goals, from the master of human nature and behaviour change and Choiceology podcast host Professor Katy Milkman.
Award-winning Wharton Professor Katy Milkman has devoted her career to the study of behaviour change. An engineer by training, she approaches all challenges as problems to be solved and, with this mind-set, has drilled into the roadblocks…
Danny Kahneman is a colleague (now emeritus) at the Bendheim Center for Finance, Princeton University who has been instrumental in creating the field of behavioral economics and finance – along with Amos Tversky and others.
Professor Kahneman has written numerous and well-cited papers and books on the topic of systematic biases when rendering decisions under uncertainty.
This bestselling book provides a delightful survey of these tendencies and approaches for helping individuals overcome their biases. It behooves every investor to become familiar with these natural tendencies when implementing strategies to maximize the probabilities of attaining their investment goals.
The phenomenal international bestseller - 2 million copies sold - that will change the way you make decisions
'A lifetime's worth of wisdom' Steven D. Levitt, co-author of Freakonomics 'There have been many good books on human rationality and irrationality, but only one masterpiece. That masterpiece is Thinking, Fast and Slow' Financial Times
Why is there more chance we'll believe something if it's in a bold type face? Why are judges more likely to deny parole before lunch? Why do we assume a good-looking person will be more competent? The answer lies in the two ways we make choices: fast,…
Most investors understand the idea that accumulated wealth is largely aimed at achieving financial goals in the future – such as saving for a comfortable retirement. Unfortunately, traditional portfolio models largely ignore these goals and thereby result in sub-optimal investment decisions. This edited book expands asset-only models to address future goals, liabilities, and quasi-liabilities. Since volatility was proposed by the late Harry Markowitz for evaluating investment risks, there has been considerable debate about defining “risks.” The volatility measure is poorly linked to critical investment issues: such as, the probability of reaching a desired investment goal – amount/time, or the ability to pay future liabilities. The technology of ALM and goal-driven models is discussed, along with successful applications for both individuals and institutions.
