The Efficient Market Hypothesis: Empirical Evidence

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 analysisas 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.

Are Stock Markets Driven More by Sentiments than Efficiency?

“…There is evidence supporting each of the hypotheses, however, there is no consensus whether indeed the markets are efficient and the prices are unpredictable see, e.g. Borges (2010), Lo and MacKinlay (2011), Sewell (2011Sewell ( , 2012 and the preceding discussion on the role of psychology at the stock market. Several quantitative studies towards measuring general sentiment and its relation to the stock market prices have been conducted.…”

The Effi cient Market Hypothesis

“…The model is preferred to have no serial correlation (Sewell, 2012). Many economists like Fama indicated the exhibition of serial correlation in stocks prices (Fama, 1970).…”

“…Many economists like Fama indicated the exhibition of serial correlation in stocks prices (Fama, 1970). However, detrending the data is not the solution because the results will not change accordingly (Sewell, 2012).…”

Analyzing Chaos Systems and Fine Spectrum Sensing Using Detrended Fluctuation Analysis Algorithm

“…Besides, DFA is widely used to detect and/or characterize if a time series is random or not. DFA algorithm has been applied in different areas, for example, weather, economy, biology, meteorology, and climate [1,2]. According to the new research trends, the DFA algorithm is implemented to analyze the WEB [3], to estimate synchrophasor measurements [4], to analyze oil reservoirs [5], to study volcano seismicity [6], and to study earthquakes [7].…”