The Efficient Market Hypothesis: Empirical Evidence

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International Journal of Statistics and Probability; Vol. 1, No. 2; 2012 ISSN 1927-7032 E-ISSN 1927-7040 Published by Canadian Center of Science and Education

The Efficient Market Hypothesis: Empirical Evidence
Martin Sewell1

Faculty of Economics, University of Cambridge, Cambridge, United Kingdom

Correspondence: Martin Sewell, Faculty of Economics, University of Cambridge, Sidgwick Avenue, Cambridge CB3 9DD, United Kingdom. Tel: 44-797-414-5461. E-mail: Received: June 6, 2012 Accepted: August 3, 2012 Online Published: October 17, 2012

doi:10.5539/ijsp.v1n2p164 Abstract


The efficient market hypothesis (EMH) has been the central proposition of finance since the early 1970s and is one of the most well-studied hypotheses in all the social sciences, yet, surprisingly, there is still no consensus, even among financial economists, as to whether the EMH holds. Five statistical analyses are conducted in an attempt to explicate such apparently contrary convictions. An analysis of daily, weekly, monthly and annual Dow Jones Industrial Average log returns found that first-order autocorrelation is small but positive for all time periods, with the autocorrelations for daily and weekly returns closest to zero, and thus an efficient market. A standard runs test showed that the hypothesis of independence is strongly rejected for daily returns, but accepted for weekly, monthly and annual returns, whilst the results of a more sophisticated runs test showed that daily, weekly and decreasing returns are the least consistent with an efficient market. Rescaled range analysis was conducted on the same data sets, and there was no significant evidence for the existence of long memory in the returns, a result consistent with market efficiency. Finally, from an analysis of investment newsletters it may be concluded that technical analysis— as applied by practitioners—fails to outperform the market. I reconcile the fact that daily stock market log returns pass linear statistical tests of efficiency, yet non-linear forecasting methods can still generate above-average riskadjusted returns, whilst discretionary technical analysts fail to make abnormal returns. Keywords: efficient market hypothesis, Dow Jones Industrial Average, dependence, autocorrelation, runs test, long memory, investment newsletters 1. Introduction Just over a decade ago Mark Rubinstein published ‘Rational markets: Yes or no? The affirmative case’ in the Financial Analysts Journal (Rubinstein, 2001). The current article lends empirical support to the validity of the question, and provides a more complex answer. The central paradigm in finance is the ‘efficient market hypothesis’, which is covered in the following section. This paper describes five pieces of research, each of the first four analyse daily, weekly, monthly and annual data from a major US stock market index. The first and most straightforward test is a measurement of the autocorrelation of stock market returns. The second and third investigations involve a simple and an advanced version of the runs test (a non-parametric statistical test of the mutual dependence of the elements of a sequence). The fourth investigation tests for the existence of long memory. Finally, the fifth piece of work involves an analysis of the performance of investment newsletters. All five analyses (potentially) have implications apropos market efficiency. 2. Efficient Market Hypothesis The efficient market hypothesis (EMH) has been the central proposition of finance since the early 1970s and is one of the most controversial and well-studied propositions in all the social sciences. Despite improvements in the quality and quantity of data, advances in statistical analysis and improvements in theoretical models, there is little consensus among financial economists as to the validity of the EMH. For example, just under half of the papers reviewed in Sewell (2011) support market efficiency. A market is said...
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