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Question: the ceo of jp morgan analyzed the data for exchange...

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The CEO of JP Morgan analyzed the data for exchange rates between Japanese Yen and US Dollars for the past 12 months and found the first three autocorrelation coefficients to be 0.75, 0.37 and 0.10 respectively (i.e. r1 = 0.75, r2 = 0.37 and r3 = 0.10). Based on his findings, he believes that the exchange rate can be predicted using lagged data. (a) Set up a hypothesis and test for the significance of r1 (i.e. H0 : r1 = 0). What is your conclusion? (b) Set up a joint hypothesis to test H0 : r1 = r2 = r3 = 0 and compute associated LBQ statistic. What is your conclusion on the hypothesis? (c) Based on your findings, what are your suggestions to the CEO?

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