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Using the regression output the null hypothesis of no serial correlation at the 0.05 significance level. The unemployment rate is estimated using the following model:URt= b0 + b1t+ €tUsing monthly observations from January 2015 to December 2019 you estimate the following.  Regression Statistics R Squared 0.9314 Standard Error 0.1405 Observations 60 Durbin-Watson 0.9099   Coefficients Standard Error t Stat Intercept 5.5098 0.0367 150.03 Trend -0.0294 0.001 -28.07

Use the following information:   Number of Forecast Mean Forecast Error SD of Forecast Errors Analyst A          101             0.05 0.10 Analyst B          121            0.02 0.09      The 95% confidence interval for Analyst’s A’s mean forecasting error is:

In the following table Ri is the return on stock i and Rm is the return on market. You test for the significance of βi at 5% level of significance. Your hypothesis is: t Ri Rm (Rm-Rmbar)^2 error^2 Rm^2 1 0.080 0.100 5.625E-05 0.0000 0.01 2 -0.040 0.130 0.000506 0.0005 0.0169 3 0.040 0.120 0.000156 0.0007 0.0144 4 0.130 0.080 0.000756 0.0001 0.0064 Total 0.21000 0.43000 0.001475 0.0013 0.0477 Mean 0.05250 0.10750 variance 0.00516 0.00049 covariance -0.00153   SEE 0.02535

In the following table Ri is the return on stock i and Rm is the return on market. The estimate of the tstat for βi is closest to: t Ri Rm (Rm-Rmbar)^2 error^2 Rm^2 1 0.080 0.100 5.625E-05 0.0000 0.01 2 -0.040 0.130 0.000506 0.0005 0.0169 3 0.040 0.120 0.000156 0.0007 0.0144 4 0.130 0.080 0.000756 0.0001 0.0064 Total 0.21000 0.43000 0.001475 0.0013 0.0477 Mean 0.05250 0.10750 variance 0.00516 0.00049 covariance -0.00153   SEE 0.02535

You have 64 companies in your portfolio. The average return of portfolio is 0.14 and the standard deviation is 0.16. The standard error of the mean is closest to:

There are ____ number of steps in hypothesis testing?

What is the mean-reverting level to which changes in the unemployment rate converge? The unemployment rate is estimated using the following model:∆URt= b0 + b1∆URt-1+ €tUsing monthly observations from March 2015 to December 2019 you estimate the following.  Regression Statistics R Squared 0.2184 Standard Error 0.1202 Observations 58 Durbin-Watson 2.1852   Coefficients Standard Error t Stat Intercept -0.0405 0.0161 -2.51 ∆URt-1 -0.4674 0.1181 -3.96

For a standard normal distribution F(0) equals:

You believe that there should be a positive relationship between returns and systematic risk. The appropriate alternate hypothesis is:

Consider thefollowing information on two securities Expected rate  of return on Security Ri   = 0.10                      Expected rate of return on Security Rj    = 0.20 Variance of ROR of security Ri      =  0.16       Variance of ROR of security Rj      = 0.25Covariance between Ri and Rj = -0.04The variance of Global Minimum Variance portfolio is: