Journal ArticleDOI
Information Theory and Market Behavior
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In this article, the authors show that most empirical evidences about market behaviors documented in the literature can be explained by a new information theory generalized from Shannon's entropy theory of information.Abstract:
Some recent empirical works indicate that investor performance and market patterns are primarily information driven instead of a behavioral phenomenon. However, Grossman and Stiglitz information theory and its variations offer little guidance in identifying informed investors and in distinguishing between securities with scarce information and those with widely available information. We show that most empirical evidences about market behaviors documented in the literature can be explained by a new information theory generalized from Shannon's entropy theory of information. Investor performance and market patterns are the results of information processing by investors of different sizes with different background knowledge.read more
Citations
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Journal ArticleDOI
Mutual Fund Performance: An Empirical Decomposition into Stock-Picking Talent, Style, Transactions Costs, and Expenses
Journal ArticleDOI
Algorithmic complexity of financial motions
TL;DR: The main applications of algorithmic (Kolmogorov) complexity to the problem of price dynamics in financial markets are surveyed and a general algorithmic framework is put forward in order to highlight its potential for financial data analysis.
BookDOI
Market Risk and Financial Markets Modeling
TL;DR: In this article, the authors focus on the dynamics of the relations between hedge fund performance and various microeconomic factors and quantifies shifts in the average hedge fund alpha that result from changes in hedge fund style, age, size, and fee structure.
Journal ArticleDOI
The Informational Theory of Investment: A Comparison with Behavioral Theories
TL;DR: In this paper, a new theory of investment based on a newly developed information theory is developed, which states that information is the reduction of entropy, not only in a mathematical sense, as in Shannon's theory, but also in a physical sense.
References
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A mathematical theory of communication
TL;DR: This final installment of the paper considers the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now.
Book
Judgment Under Uncertainty: Heuristics and Biases
Amos Tversky,Daniel Kahneman +1 more
TL;DR: The authors described three heuristics that are employed in making judgements under uncertainty: representativeness, availability of instances or scenarios, and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available.
Journal ArticleDOI
On Persistence in Mutual Fund Performance
TL;DR: Using a sample free of survivor bias, this paper showed that common factors in stock returns and investment expenses almost completely explain persistence in equity mutual fund's mean and risk-adjusted returns.
Journal ArticleDOI
Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency
TL;DR: In this article, the authors show that strategies that buy stocks that have performed well in the past and sell stocks that had performed poorly in past years generate significant positive returns over 3- to 12-month holding periods.
Book
The Mathematical Theory of Communication
TL;DR: The Mathematical Theory of Communication (MTOC) as discussed by the authors was originally published as a paper on communication theory more than fifty years ago and has since gone through four hardcover and sixteen paperback printings.