Simple Test of Chilime Stock

Random Walk Theory

An investment theory which claims that market prices follow a random path up and down, without any influence by past price movements, making it impossible to predict with any accuracy which direction the market will move at any point. In other words, the theory claims that path a stock's price follows is a random walk that cannot be determined from historical price information, especially in the short term. Investors who believe in the random walk theory feel that it is impossible to outperform the market without taking on additional risk, and believe that neither fundamental analysis nor technical analysis have any validity. The random walk theory proclaims that it is impossible to consistently outperform the market, particularly in the short-term, because it is impossible to predict stock prices.

To test the random walk of the stock price of Chilime Hydro power, I have taken the recent 100 trading days price. The stock price from 24th February 2013 to 23rd July 2013 is taken as a sample data. The data is analyzed is analyzed using SPSS software. To determine whether the price of Chilime follow random path or not is tested using run test and auto correlation test. The results are summarized below:

1.      Runs Test
	Price_Chilime
Test Valuea	1152.0900
Cases < Test Value	66
Cases >= Test Value	34
Total Cases	100
Number of Runs	10
Z	-8.045
Asymp. Sig. (2-tailed)	.000
a. Mean

Run-test is used in order to examine the randomness behavior of stock price of Chilime Hydropower Company Ltd. Here the test value is 1152 and the price below test value is 66 and above the test value is 34. The number of runs is 10. Randomness behavior will be determined by the total number of runs. Too many or few number of runs indicates the existence of dependency The null hypothesis that states the random behavior of stock price will be rejected if the observed number of run is significantly different from the expected number of runs. Thus, to accept the null hypothesis on as much as 95% confidence level, the probability value that the event will be occurred should be greater than α (0.05). The hypothesis testing is stated as:

H₀= Price of Chilime’s Stock is follow random pattern

H₁= Price of Chilime’s Stock does not follow random pattern

Here the p-value is less than α, so null hypothesis is rejected and alternative hypothesis is accepted. Hence the price of Chilime’s Stock does not follow the random walk theory.

Autocorrelations
Series:Price_Chilime
Lag	Autocorrelation	Std. Errora	Box-Ljung Statistic
			Value	df	Sig.b
1	.849	.099	74.328	1	.000
2	.712	.098	127.019	2	.000
3	.539	.098	157.528	3	.000
4	.417	.097	175.978	4	.000
5	.327	.097	187.445	5	.000
6	.261	.096	194.824	6	.000
7	.190	.095	198.781	7	.000
8	.095	.095	199.777	8	.000
9	.038	.094	199.940	9	.000
10	-.006	.094	199.945	10	.000
11	-.029	.093	200.040	11	.000
12	-.039	.093	200.213	12	.000
13	-.041	.092	200.409	13	.000
14	-.070	.092	200.986	14	.000
15	-.083	.091	201.821	15	.000
16	-.081	.091	202.619	16	.000
a. The underlying process assumed is independence (white noise).
b. Based on the asymptotic chi-square approximation.

Autocorrelation of a random process describes the correlation between values of the process at different times, as a function of the two times or of the time lag. Autocorrelation is used in order to examine the randomness behavior of stock price of Chilime Hydropower Company Ltd. To test weather autocorrelation exists or not, a hypothesis can be set as follow:

H_o = there does not exist autocorrelation or zero autocorrelation i.e. the stock price of Chilime’s follow random walk theory

H₁ = there exist autocorrelation or non-zero autocorrelation i.e. the stock price of Chilime’s does not follow random walk theory

The null hypothesis that states the random behavior of stock price and alternative hypothesis state the non-randomness of stock price of Chilime.  Thus, to accept the null hypothesis on as much as 95% confidence level, the probability value that the event ( in every lag 1-16) will be occurred should be greater than α (0.05). Here the p-value is less than α in every lag i.e. (lag 1-16), so null hypothesis is rejected and alternative hypothesis is accepted. Hence the stock price of Chilime does not follow random walk theory. Furthermore, this result of autocorrelation analysis has provided evidence of the weak form of market inefficiency.

Conclusion:

Using run test and autocorrelation test, we can conclude that the stock price of Chilime’s do not follow the random walk theory rather it can be predicated using past information of the company.

Submitted by: Mr. Bikram Thapa (03)

Manikkya, Apex College