Performance analysis of single structural break test with an empirical study on efficient market hypothesis"
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In this thesis, performance of the single structural break tests is examined. Since it has proved superiority of Sequential F test on other single break tests, it is chosen as single break test. Monte Carlo simulation is run for different scenarios and performances of the test with respect to estimating break points, and parameters, and rejecting or accepting the joint null hypothesis is observed. For all cases small sample bias is observed. The test estimates parameters correctly for large samples but for small samples it underestimates or overestimates parameters. Another common problem is about joint null hypothesis. When test rejects the joint null, it doesn’t identify which of the joint hypothesis is rejected. Therefore in this study, we utilize the t-statistic of the parameters to determine the individual hypothesis rejected. In addition to these common problems we illustrate other scenario specific problems in this study. We examine the implications of our Monte Carlo findings by applying the break test to real life data and investigate the efficient market hypothesis using stock market data on SP&500. Application of the sequential F test shows evidence against the efficient market hypothesis.