Table of Contents

Handbook of Behavioral Finance

Handbook of Behavioral Finance

Elgar original reference

Edited by Brian Bruce

The Handbook of Behavioral Finance is a comprehensive, topical and concise source of cutting-edge research on recent developments in behavioral finance.

Chapter 19: The Information-Adjusted Noise Model: Theory and Evidence from the Australian Stock Market

Sinclair Davidson and Vikash Ramiah

Subjects: economics and finance, behavioural and experimental economics, economic psychology, financial economics and regulation


Sinclair Davidson and Vikash Ramiah Eugene Fama (1998) has set the benchmark for comparing the efficient market hypothesis (EMH) and behavioural finance theories. He indicates that many alternatives to the EMH are vague and unspecified. Quite rightly, he argues that alternatives to the efficient market hypothesis need to be well specified and testable. In particular, he suggests that much of the evidence against markets being informationally efficient is, in fact, consistent with market efficiency – this is especially so if anomalies are split evenly between underreaction and overreaction. We show, using daily data from the Australian Stock Exchange (ASX), that the underreaction and overreaction anomalies do not split evenly and that, contrary to EMH-type arguments, information traders do not necessarily correct pricing errors introduced into the market by noise traders. Consistent with the market being behaviourally efficient (Shefrin and Statman, 1994), however, this does not translate into supernormal profit opportunities. Our model describes the interaction between information traders and noise traders. Unlike much of the behavioural finance literature, we do not assume that information traders necessarily return markets to fundamental values. Information traders trade on the basis of information, but may well make errors in interpreting that information. Noise traders trade in the absence of information. Information traders may well correct the pricing errors introduced by noise traders – this is just one of the outcomes we describe. On the other hand, information traders may undercorrect, or overcorrect, noise errors. This gives rise to either underreaction or overreaction. In this respect we...

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