thanks for.

A) Assume that a financial analyst wants to forecast daily return of stock A. He has analyzed the data and fitted model #1, Y. Now the financial analyst wants to test this model (and resulting forecast) for optimality. He has decided to conduct test by running the following regression of the forecast errors: X=0, Y=3, Z=1 ettilt = data, * ent-1 + Ut+1 Please comment (1) what kind of loss function do you think the financial analyst applied, (2) what is the null and alternative hypothesis in terms of the model's parameters, and (3) what do each of parameters mean? B) You have run the above regression and obtained the following results: Estimate Standard error -0.1 0.OY 1.Y 0.5 Comment on the forecast optimality in terms of provided results. What can be inferred from the information given? C) Now assume that the financial analyst has fitted another two models, Y? and Y?. And he wants model that would be both optimal and the best one. He has decided to conduct test for forecast optimality (the confidence level is 10%) and calculate the Akaike Information Criterion (AIC). The results are following: p-value AIC Model #2 (Y?) 0.5 600 Model #3 (Y?) 0.7 60X Which model should the financial analyst choose? Please describe in details the financial analyst's next steps considering information given. Do not forget to provide clear justification for your