TESTING RANDOM WALK BEHAVIOR OF MAJOR ASIAN STOCK MARKETS Mohammad Anees1 Sumit Kumar2 Abstract In the era of open market economy the growth of any country is truly reflected by its capital markets operation. With the inception of 21 century, capital markets of developing countries have been the focal point of investment for the investors across the world. The major consideration for such investment remained the level of efficiency of these markets. Among Asian countries, stock markets of India, China and Japan, have attracted the substantial Foreign Institutional Investment in comparison to the other Asian capital markets. The present study examines the Random Walk Behavior of three major stock exchanges of Asian countries namely; China, Japan and India. For this purpose the stock indexes representing the three countries BSE30-India, SSEC-China and N225-Japan have been considered. The data for a period of 5 years from 2009 to2014 have been taken from the respective countries' stock exchanges websites. With the help of Run-Test and Autocorrelation, the weak form of market efficiency has been tested. Results of the study clearly reveal that all the three stock market of Asia follow Randomwalk i.e. all these markets are in weak form of efficiency and such markets offer tremendous opportunity to the investors to earn a fairly high return by just working systematically on the information and trading strategies. To our knowledge this is the contemporary study which covers the emerging Asian markets for the period after the global financial crises of 2007-2009, hence a significant evidence on market efficiency of this kind is being contributed in the literature. Such a study may be useful for present and potential local and global capital market investors. Keywords: Market efficiency, Asian stock market, Run test, Random walk. 1.

Introduction Capital markets have a significant role in the economic growth of a country. Capital markets reflect the actual level of economic development of a country, as they serve the industries and governments to raise long term funds. The market is broadly divided into the equity (stock) and debt (bond) segment. The important attribute of capital market is its efficiency; the term market efficiency in stock market is used to measure the extent of logical, ethical and desirable trading operation on the basis of available relevant information. The concept of Efficient Market Hypothesis (EMH) is based on the arguments of Samuelson (1965) that predictable price of an asset swings in random manner. In finance, the efficient-market hypothesis (EMH) assures that financial markets are "informational efficient”. That 1. 2.

Mohammad Anees, Assistant professor, Department of Business Administration, University of Lucknow, Lucknow, (UP), INDIA Sumit Kumar, Junior Research Fellow, Department of Business Administration, University of Lucknow, Lucknow, (UP), INDIA

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Mohammad Anees1 Sumit Kumar2

is, one cannot consistently earn returns in excess of average market returns on a risk-adjusted basis, on the base of the information publicly available at the time the investment is made. With regards to EMH theory in corporate finance Fama (1970) has put a landmark through his work by extending EMH in three major versions of the hypothesis: “weak”, “semi-strong”, and “strong” and proposed three models for testing market efficiency, The Fair Game model, the Sub martingale model, and the Random Walk model. Random walk Model is used to identify the weak form of market efficiency. In a market in the weak-form, future prices of an asset cannot be predicted easily but there is a possibility of managing all the available information and other inefficient related factors to earn the fair return.A high level of nonsystematic risk prevails in the market. Each technical analyst will not be able to produce consistently excess returns than market return. Share prices exhibit no serial dependencies, meaning that there are no “patterns” to asset prices. In other words the movement of future price of an asset is determined entirely on the bases of information not contained in the historical price series. Hence, current asset prices must follow a random walk. However, in the presence of weak form of market efficiency, the investors will be able to earn extra return than the market, with the application of various specific trading strategies and statistical techniques. 2.

Literature Review Market efficiency has significant role in the investor's portfolio and investment choice on the risk

bases. The weak form of market efficiency has been tested around all the stock exchanges of the world. Several researches have been done on this topic on various stock markets of different countries or regions. In the 21 century, Asian stock markets have attracted the attention of the investors for the investment and researcher to explore the literature. India, China and Japan are leading stock markets of Asia. Several researches have been done in the developed market. A. C. Worthington and H. Higgs (2006) inspect the weak-form of market efficiency of ten emerging Asian market of China, India, Indonesia, Korea, Malaysia, Pakistan, Philippines, Sri Lanka, Taiwan and Thailand and five developed markets Australia, Hong Kong, Japan, New Zealand and Singapore. The result reveals that none of the emerging Asian markets are following the random walks model and hence are not weak-form efficient, where as except the Australian market only the developed markets in Hong Kong, New Zealand and Japan are strongly supporting the random walk hypothesis. Nikunj R. Patel, Nitesh Radadia and J (2012) have studied the weak form of market efficiency of four selected Asian stock markets for the periods of 1st January 2000 to 31st March 2010 and concluded that BSE Sensex and NIKKEI are in the weak inefficient form. On the other hand HANSENG and SSE Composite follows weak form of efficiency. Integral Review- A Journal of Management, Vol.7 No. 2, December 2014

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Testing Random Walk Behavior Of Major Asian Stock Markets

Saqib Nisar and Muhammad Hanif (2012) examined the weak form of efficient market hypothesis on the four major stock exchanges of South Asia including, India, Pakistan, Bangladesh and Sri Lanka. Historical index values on a monthly, weekly and daily basis for a period of 14 Years (19972011) for this purpose they applied four statistical tests including runs test, serial correlation, unit root and variance ratio test and concluded that none of the four major stock markets of south-Asia follows Random-walk and hence all these markets are not the weak form of efficient market. Jae H. Kim (2004) tests for the martingale (or random walk) hypothesis in the stock prices of a group of Asian countries. The selected countries represent well-developed markets Hong Kong and Japan as well as emerging markets Korea, Taiwan and Thailand. They found that the stock prices of Japan, Korea, and Hong Kong are found to follow the martingale, indicating that their stock markets have been efficient. The results of these three researchers are similar. The contradictory results in reference of emerging economics were founds by the Arusha V. Cooray, G. Wickramasighe(2007) as they use different econometric tests of Augmented Dickey Fuller (ADF-1979, 1981), the Phillips-Perron (PP-1988), the Dicky-Fuller Generalized Least Square (DFGLS-1996) Elliot-Rothenberg-Stock (ERS – 1996) and found that the stock markets of India, Sri Lanka, Pakistan and Bangladesh during the period of 1996 to 2005 are Weak form efficient. Hin Yu Chung (2006) has examined the random walk hypothesis for two major stock markets in China. Using Daily returns from February 21, 1992 to December 30, 2006 for the Shanghai A-share, Shanghai B-share, Shanghai Composite and Shenzhen Composite and from October 5, 1992 to December 30, 2005 for Shenzhen A-share and Shenzhen B-share, he concluded that both the Chinese stock markets are weak-form inefficient, a contradictory results for this study is done by the Kian-Ping et.al. They Study the random walk behavior of Shanghai and Shenzhen Stock Exchanges and founds that both of the markets are consistent with random walk for long periods of time, after the 1997 there exists a serial dependency between both the market which reveals that the both the market reacts in similar fashion to the information related to politics, economic, social and institutional changes, continuation with this Faiq Mahmood et.al.(2010) has studied the behavior of Chinese stock market before and after recession by using ADF, DFGLS, PP and KPSS tests on for both the market Shenzhen and Shanghai stock exchanges separately. They concluded that Chinese stock market is consistently weak form efficient and the global financial crisis has no significant impact on the efficiency of Chinese stock market. From the above discussion, in respect of the Chinese stock market it is found that most of the researchers have found the similar results which shows that the market is weak form efficient, there is no opportunity to the investors to beat the market return just with exploiting the private information or using other trading practices. Integral Review- A Journal of Management, Vol.7 No. 2, December 2014

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R. Vaidyanathkant, Kumargali (1994) have tested the weak form of efficiency of the Indian capital market for the period 1989 to1994. On the bases of the ten actively traded share prices on Bombay stock exchange, by using Run test and serial correlation they argue that market follows the weak form of Efficient Market Hypothesis. Similar results are founds by the Rakesh Gupta and Junhao Yang (2011) for two major Indian equity markets BSE and NSE for the sample period 2007 to 2011, but for period 1997 to 2007 it did not support the weak form efficiency. Sunil Poshakwale (1996) argues that over the period of 1987-1994, BSE exhibits the evidence of day of the week effect and weak form inefficient, the market conditions provide the opportunity to the investor by using different buy and hold strategy issues they get extra returns. Similar results were found by the Alan Harper Zhenhu Jin for July 1997 to 2011,the Indian stock market are not weak form efficient which provide the opportunity to the investors to earn extra return from exploiting the trading strategy. By Augment using Dickey-Fuller (1979) test and the Phillips-Perron (198l), P. Srinivasan (Nov 2010) concluded that the daily stock market returns of two major indices, S&P CNX NIFTY and the SENSEX does not follow the random walk behavior, Divyang J Joshi (2012) using Run test concluded that 6 major Indian Stock market indices, BSE 30, BSE 100,200,500, BSE SMALL CAP and BSE MIDCAP for the period from 1st January 2001 to 31st December 2010, do not follow the random walk model and the markets are in weak form inefficient. In relation with the Indian stock market most of the researches supported that these markets are in weak form inefficient that means the returns in these market are predictable up to some extent, and investor have an opportunity to get extra return where as in respect of the Japanese the short literature and its markets are compared with the other stock markets there are also similar conclusions arrived by the researches as Chinese markets Market efficiency is the topic for the discussion among the researchers, several researches have examined market efficiency over the decades, and found the conflicting results. Some of them are inefficient and others are efficient but there are few of the cases which prove the efficient form of the market around the Asia. This study is also an attempt to investigate the empirical results and try to test weak form of market efficiency during the current period just after the great global recession. 3.

Data Analysis and Research Methodology The stock prices of BSE 30, N225, SSEC, on the daily and weekly bases over the period of 2009 to 2014 has been collected from the website of yahoo finance which provides all the data related to the major stock market in all region of the world. For the validity of the data it is cross checked from the website of these stock markets and assured that they are valid.Returnsfor the selected period are calculated with help of following equation. Integral Review- A Journal of Management, Vol.7 No. 2, December 2014

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Testing Random Walk Behavior Of Major Asian Stock Markets

Rt = log (pt / pt-1) Where Rt is return, log is natural log, pt is current price and pt-1 is previous day price. For the calculation of continuously compounded rate of return we used the natural logarithms. To test the weak form of efficiency we applied the Run test and for the validation of the results of Run test is done with the Auto-Correlation test with the help of SPSS20. Runs Test: To check the randomness in the series, Run test is conducted. The Null hypothesis stated as H0: There is no sequence present in the series. Following equation was used.

Z = R – X /ó If we assume that there is a random walk in time series R = Total number of runs X = 2n1n2+1/ n1+ n2 n1 = Number of positive runs n2 = Number of negative runs

ó z = Normal variant, at 5 % level of significance the Z

-value is≥　 -1.96 and≤　 ＋　 1.96.

Auto-Correlation test Another approach to detecting the random walk of the stock returns is the autocorrelation test Autocorrelation (serial correlation coefficient) measures the relationship between the stock return at current period and its value in the previous period. It is given as follows:

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Mohammad Anees1 Sumit Kumar2

Where ñk is the serial correlation coefficient of stock returns of lag k, N is the number of observations, Rt is the stock return over period t and Rt+1 is the stock return over period t+1 is the sample mean of stock returns; and k is the lag of the period. The test aims to determine whether the serial correlation coefficients are significantly different from zero. Statistically, the hypothesis of weak-form efficiency should be rejected if stock returns (price changes) are serially correlated is significantly different from zero. To test the joint hypothesis that all autocorrelations are simultaneously equal to zero, the Ljung–Box portmanteau statistic (Q) is used.Under the null hypothesis of zero autocorrelation at the first k autocorrelations (ñ1=ñ2=ñk= 0), the Q-statistic is distributed as chi-squared with degrees of freedom equal to the number of autocorrelations (k).the null hypothesis is stated as, H0: No serial correlation exits in the series 4.

Results and Findings

Table No 1 shows the outcome of the Descriptive statistics for all three markets. Table no 2, 3 showing the output of Run test performed for three marketson basis of daily, monthly and yearly. Table No. 1: Descriptive Statistics Mean Std. Variance Skewness Deviation

N Statistic SSEC Daily

Statistic

Statistic

Statistic

Statistic

Kurtosis

Std. Statistic Std. Error Error .069 2.378 .138

1248

.000094

.0136339

.000

-.385

SSEC Weekly SSEC Monthly

255 59

.000412 .001035

.0291072 .0713054

.001 .005

.138 -.533

.153 .311

.128 1.477

.304 .613

N225 Daily N225 Weekly

1228 259

.000479 .002362

.0148138 .0296880

.000 .001

-.604 -.220

.070 .151

4.005 .672

.140 .302

N225 Monthly BSE30 Daily

59 1233

.012067 .000611

.0569492 .0138400

.003 .000

-.264 1.153

.311 .070

-.378 15.491

.613 .139

BSE30 Weekly BSE30 Monthly

261 60

.002884 .013465

.0294998 .0630494

.001 .004

.301 .936

.151 .309

2.112 2.326

.300 .608

Valid N (listwise)

59

The Descriptive statistics table shows the mean, variance, standard deviation for all the selected market for daily weekly, Monthly, the series of daily return for all markets showing highest value of the Integral Review- A Journal of Management, Vol.7 No. 2, December 2014

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Testing Random Walk Behavior Of Major Asian Stock Markets

skewness and Kurtosis which indicate that these series do not follow the normal distribution for the Monthly and weekly. The return series are showing the acceptable value of skewness and kurtosis that mean we can say that this series follow the normal distribution. For the monthly standard deviation is highest in SSEC fallowed by BSE and N225 which indicates that these markets are risky. Table No. 2: Out Put of Runs Test 1 Daily SSEC Test Value

a

Weekly Monthly SSEC

SSEC

Daily

Weekly

Monthly

Daily

Weekly

Monthly

N225

N225

N225

BSE30

BSE30

BSE30

.0001

.0013

.0064

.0007

.0048

.0097

.0006

.0040

.0031

Cases < Test Value

624

127

29

614

129

29

616

130

30

Cases >= Test Value

624

128

30

614

130

30

617

131

30

1248

255

59

1228

259

59

1233

261

60

Number of Runs

625

123

30

655

118

32

602

131

35

Z

.000

-.690

-.129

2.284

-1.556

.396

-.883

-.062

1.042

1.000

.490

.897

.022

.120

.692

.377

.951

.298

Total Cases

Asymp. Sig. (2-tailed) a. Median

Test Value a Cases < Test Value Cases >= Test Value Total Cases Number of Runs Z Asymp. Sig. (2tailed)

Table No. 3: Runs Test 2 Monthly Daily Weekly SSEC N225 N225

Daily SSEC

Weekly SSEC

.000094

.000412

623

127

29

605

121

30

617

128

36

625

128

30

623

138

29

616

133

24

1248

255

59

1228

259

59

1233

261

60

625

123

30

653

118

30

600

131

39

.000

-.690

-.129

2.178

-1.493

-.129

-.997

-.056

2.497

1.000

.490

.897

.029

.135

.897

.319

.955

.013

.001035 .000479

Monthly Daily N225 BSE30

Weekly Monthly BSE30 BSE30

.002362 .012067 .000611 .002884

.013465

a. Mean

From the above table of Run test using median significance value is > 0.05 i.e the null hypothesis of random walk is accepted for all three levels of the SSEC and BSE-30 market, in case of daily return of N225 the value is