Testing the S&P/TSX Composite Index for Weak Form Market Efficiency

Orumwense, Elisha Uwa (2020) Testing the S&P/TSX Composite Index for Weak Form Market Efficiency. Masters thesis, Dublin, National College of Ireland.

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Abstract

In an efficient market, stock prices are accurately priced and the opportunity of making abnormal returns through predicting prices, is impossible. This research, tested the daily closing price of the S&P/TSX Composite Index for weak form market efficiency, from the period of 11th of December 1996 to 11th of December 2019. This was carried out by using tests like Autocorrelation, Ljung box (Q) statistics, runs test, Augmented Dickey Fuller test, Variance ratio test and One-sample Kolmogorov Smirnov test. The Autocorrelation and Ljung box (Q) statistics results revealed that, the stock price movement are not independent. The runs test showed that, there is presence of serial independence, which implies that the stock prices are random. The ADF test is in line with the autocorrelation test and showed that there is no presence of unit root in the S&P/TSX Composite Index (1996-2019), which implies that, there is a trend in the series. The variance ratio test is in line the runs test, as it failed to reject the random walk for all periods observed. We observed that the K-S test, kurtosis and skewness all showed non-normality for the S&P/TSX Composite Index and is also in line with the ADF test. The robust variance ratio test and runs test, are better deterministic factors for the state of efficiency of a stock market. As it test for the presence of random walk. Therefore, the S&P/TSX Composite Index is weak form efficient through time. Hence, investors cannot make abnormal profits by using past data. The study serves as an updated information for investment banks, fund managers and most importantly investors, who are looking to expand their investments.

Key words: Weak Form Market Efficiency, Random walk, Variance ratio, Runs Test

Item Type:	Thesis (Masters)
Subjects:	H Social Sciences > HG Finance H Social Sciences > HG Finance > Investment
Divisions:	School of Business > Master of Science in Finance
Depositing User:	Dan English
Date Deposited:	16 Feb 2021 10:20
Last Modified:	16 Feb 2021 10:20
URI:	https://norma.ncirl.ie/id/eprint/4768

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