a) Estimate a regression of monthly S&P 500 returns (ersandp) on a constant and the change in credit spreads (dspread) only. Report and comment on your results.
b) Examine graphically the residual plots. Copy/paste the residual plot into your problem set write up. Is there visual evidence of serial correlation and/or heteroskedasticity?
c) Conduct all the various diagnostic tests for autocorrelation and heteroskedasticity we have encountered in class and report/comment on your results.
d) Explain why serial correlation might be more of a problem in higher frequency vs. lower frequency data. For example, in Empirical Handout 2 we saw strong autocorrelation in daily returns, but what about monthly returns as we have here? [This is more of a finance-intuition type question].
e) Based on your results in (c), is it necessary to use the HAC adjustment? Perform the regression with HAC standard errors and comment on any difference you find. Is the estimated relationship now stronger or weaker?
f) As a final test of the predictability of stock market returns, include in the regression above one lag of S&P 500 returns, ersandp(-1), and perform a robust regression (i.e., using HAC). Report and comment on the significance of the individual estimates. Discuss your results in light of weak-form and strongform stock market efficiency
CS 340 Milestone One Guidelines and Rubric Overview: For this assignment, you will implement the fundamental operations of create, read, update,
Retail Transaction Programming Project Project Requirements: Develop a program to emulate a purchase transaction at a retail store. This
7COM1028 Secure Systems Programming Referral Coursework: Secure
Create a GUI program that:Accepts the following from a user:Item NameItem QuantityItem PriceAllows the user to create a file to store the sales receip
CS 340 Final Project Guidelines and Rubric Overview The final project will encompass developing a web service using a software stack and impleme
