Question #82

of 101 Rhonda Wilson, CFA, is analyzing sales data for the TUV Corp, a current equity holding in her portfolio. She observes that sales for TUV Corp. have grown at a steadily increasing rate over the past ten years due to the successful introduction of some new products. Wilson anticipates that TUV will continue this pattern of success. Which of the following models is most appropriate in her analysis of sales for TUV Corp? A) A log-linear trend model, because the data series can be graphed using a straight, upward-sloping line. B) A linear trend model, because the data series is equally distributed above and below the line and the mean is constant. C) A log-linear trend model, because the data series exhibits a predictable, exponential growth trend. Vikas Rathod, an enrolled candidate for the CFA Level II examination, has decided to perform a calendar test to examine whether there is any abnormal return associated with investments and disinvestments made in blue-chip stocks on particular days of the week. As a proxy for blue-chips, he has decided to use the S&P 500 index. The analysis will involve the use of dummy variables and is based on the past 780 trading days. Here are selected findings of his study: RSS 0.0039 SSE 0.9534 SST 0.9573 R-squared 0.004 SEE 0.035 Jessica Jones, CFA, a friend of Rathod, overhears that he is interested in regression analysis and warns him that whenever heteroskedasticity is present in multiple regression this could undermine the regression results. She mentions that one easy way to spot conditional heteroskedasticity is through a scatter plot, but she adds that there is a more formal test. Unfortunately, she can't quite remember its name. Jessica believes that heteroskedasticity can be rectified using White-corrected standard errors. Her son Jonathan who has also taken part in the discussion, hears this comment and argues that White correction would typically reduce the number of Type I errors in financial data.