Market Efficiency

Plan for Discussion Efficiency and its Forms Misconceptions of EMH Anomalies Testing Weak form of Market Efficiency Case Study of selected NSE indices S&P CNX Nifty CNX Nifty Junior

Efficiency : defined An efficient capital market is a market that is efficient in processing information… In an efficient market, prices ‘fully reflect’ available information..

Efficient Market In an efficient market, Market price is an unbiased estimate of the true value of the investment. Market Efficiency does not require that the market price be equal to true value at every point in time.

Efficient Market Errors in the market price be unbiased implying that prices can be greater than or less than true value, as long as these deviations are random. Randomness implies that there is an equal chance that stocks are under or over valued at any point in time.

In 1960s and early 1970s Fama (1965) concluded that Most of the evidences are consistent with Efficient Market Hypothesis Stock prices showed Random walk Predictable variations in equity return were statistically insignificant Reference: Fama EF (1965) “The behaviour of stock market prices”. Journal of Business. 38:34–105

Forms of Market Efficiency Fama (1970) defined three form of market efficiency : Weak Form Semi-Strong Form Strong Form Reference : Fama, E F (1970): ‘Efficient Capital Markets: A Review of Theory and Empirical Work’, Journal of Finance, 25, pp 383-417.

Weak Form Weak form of efficiency implies that : The current price reflects the past information or the history of prices. Suggesting that charts and technical analyses that use past prices alone would not be useful in finding valuable stocks.

Semi-Strong Form Semi-strong form of efficiency implies that the current price reflects the information contained not only in past prices but all publically available information (financial statements/reports).

Semi-Strong Form Academic research supports the semi-strong form of the EMH by investigating various corporate announcements, such as: Stock splits Cash dividends Stock dividends

Strong Form Strong form of efficiency implies that: the current price reflects all information, public as well as private, and no investors will be able to consistently find under valued stocks.

Example of Efficiency

Example of Inefficiency

Misconceptions on EMH

Misconceptions of EMH No group of investors will beat the market in the long term. Given the number of investors in markets, the laws of probability suggests that a fairly large number can beat the market consistently over long periods, not because of their investment strategies but because they are lucky.

Misconceptions of EMH An efficient market does not imply that stock prices cannot deviate from true value; there can be large deviations from true value. The deviations do have to be random.

Fama’s new View Fama (1998) suggests that apparent anomalies require: new behavioural based theories of the stock market and the need to continue the search for better models of asset pricing. Reference: Fama, E F (1998): ‘Market Efficiency, Long-term Returns, and Behavioural Finance’, Journal of Financial Economics, 49, pp 283-306.

Anomalies Definition Low PE Effect Low-Priced Stocks Small Firm and Neglected Firm Effect Market Overreaction January Effect Day-of-the-Week Effect Chaos Theory

Definition A financial anomaly refers to unexplained results that deviate from those expected under finance theory Especially those related to the efficient market hypothesis

Low PE Effect Stocks with low PE ratios provide higher returns than stocks with higher PEs

Low-Priced Stocks Stocks with a “low” stock price earn higher returns than stocks with a “high” stock price There is an optimum trading range

Market Overreaction The tendency for the market to overreact to extreme news Investors may be able to predict systematic price reversals Results because people often rely too heavily on recent data at the expense of the more extensive set of prior data

January Effect Stock returns are inexplicably high in January Small firms do better than large firms early in the year Especially pronounced for the first five trading days in January

Day-of-the-Week Effect Mondays are historically bad days for the stock market Wednesday and Fridays are consistently good Tuesdays and Thursdays are a mixed bag

Chaos Theory Chaos theory refers to instances in which apparently random behavior is systematic or even deterministic

Testing Weak form of Market Efficiency

Random walk hypothesis Ko and Lee (1991), If the random walk hypothesis holds, the weak form of the efficient market hypothesis must hold, Thus, evidence supporting the random walk model is the evidence of market efficiency. Reference : Ko, K.S. and Lee, S.B. (1991) A comparative analysis of the daily behavior of stock returns: Japan, the U.S and the Asian NICs. Journal of Business Finance and Accounting, 18, 219-234.

Case Study- NSE This study attempts, to seek evidence for the weak form efficient market hypothesis using the daily data for stock indices of the National Stock Exchange for the period of 1 January 2000 to 31 Oct 2008

Research Methodology Following test are done to analyze the data : Jarque Bera Test Unit Root Test Autocorrelation test Run Test K-S Test

Descriptive Statistics

Analysis Stock returns are not normally distributed, Also verified with the Jarque-Bera statistic, which is a test statistic for testing whether the series is normally distributed. The hypothesis of normal distribution is rejected at the conventional 5% level.

Unit Root Test A test to determine whether a time series is stationary or not, whether the null hypothesis of a unit root can be rejected.

ADF Test

PP Test

Analysis The null hypothesis that there is a unit root cannot be rejected for both Nifty and Nifty Junior , in the level form. For the first differences of both , the null hypothesis of a unit root is strongly rejected. Both indexes contain a unit root, that is, non-stationary in their level forms, but stationary in their first differenced forms.

Runs Test Runs Test is for the randomness of the series. Runs test investigates serial dependence in share price movements

Run Test

Analysis It can be seen that the total number of runs are 8 and 15 for S&P CNX Nifty and CNX Nifty Junior respectively. Therefore, the hypothesis of randomness for both the series is rejected.

Autocorrelations Autocorrelation is the correlation of a series with itself .The autocorrelation function (ACF) test is examined to identify the degree of autocorrelation in a time series.

Analysis Time Series Error term is stationary

Kolmogorov Smirnov Test KS is used to determine how well a random sample of data fits a particular distribution (uniform, normal, poisson). It is based on comparison of the sample’s cumulative distribution against the standard cumulative function for each distribution. .

K-S Test

Analysis The Kolmogorov Smirnov Goodness of Fit Test (KS) shows 0.00 significance for the Z at the 5 percent level. Null hypothesis of normal distribution for both is rejected

Conclusion Jarque Bera : No Normality K-S Test : Does not fit in Normal Distribution Run Test : No Random Walk Autocorrelation : Time series error : Stationary Unit Root Test : Random Walk

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