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An investigation into the Efficient Market Hypothesis: a canonical correlation analysis approach

1 In this thesis we will consider the Efficient Market Hypothesis ( E M H ) . Fama (1970) defined three levels in which to test market efficiency: weak, semi-strong, and strong, each level depending on the particular set of information being used to assess efficiency. We will mainly address weak level efficiency in which the information set is past security data. Before the mid 1980's it was widely believed that the E M H was true at the weak and semi-strong levels. It was not until the pioneering work of Shiller (1984) and Summers (1986) that some doubt was cast on the E M H . They proposed an inefficient model in which prices consist of a sum of a random walk component and a stationary (predictable) component which represents the market valuation error. Since their initial conjecture about a stationary component in stock prices much effort has been spent in trying to determine if it exists and if it does, determining how much of the variations in stock prices it accounts for. To investigate this problem we will use a combination of data filtering, canonical correlation analysis, simulations and bootstrapping. Using industry price data obtained from the Toronto Stock Exchange over the period January 1956 to June 1995, we find some evidence against the E M H .