19d7e2e65ac282fc38b673332d7f5d3b_3ae87b70348139b4b38fcd596a039143

19d7e2e65ac282fc38b673332d7f5d3b_3ae87b70348139b4b38fcd596a039143

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Part 1: Recall the weak form of the efficient markets hypothesis. It states that there is no useful information in past prices or returns that would allow us to forecast future returns. You will test this hypothesis with a time series of daily returns for Apple. Suppose you could forecast future stock prices by examining patterns in past prices or returns. This would be a great way to make money, and there is a field of study, technical analysis, where practitioners try to identify recurring patterns in stock prices and returns. However, there is a considerable body of evidence suggesting there is no useful memory in past prices. Let's do a quick experiment. The spreadsheet attached to this assignment contains two years of daily stock returns for Apple. The experiment is simple. Is today's return explained by the returns generated over each of the previous five trading days? The regression approach can be modeled like this: R t = a + b 1 (R t-1 ) + b 2 (R t-2 ) + b 3 (R t-3 ) + b 4 (R t-4 ) + b 5 (R t-5 ) + e The spreadsheet contains 502 daily returns. These are your Rt, or dependent variables. You
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