
When considering the future performance of a company, financial analysts often use forecasts for earnings per share (EPS). Naturally, we are interested in the quality of these forecasts. We can define a forecasting error as follows:
- Forecasting Error = Predicted Value of the Variable – The Actual Value of the Variable.
The optimal forecast would have a
Please complete the following tasks (1–3) and provide an answer to the following question (4):
- Define μ as the population mean forecasting error and formulate the null and alternative hypothesis for a zero mean test of forecasting quality.
- For Analyst A, use both a t-test and a z-test to determine whether to reject the null hypothesis at the 0.05 and 0.01 levels of significance.
- For Analyst B, use both a t-test and a z-test to determine whether to reject the null at the 0.05 and 0.01 levels of significance.
- What conclusions do you reach about the forecasts for Analyst A and the forecasts for Analyst B?


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