Question

Given the monthly returns that follow, find the R', alpha, and beta of the portfolio. Compute the average return differential with and without sign. Do not round intermediate calculations. Round your answers to two decimal places. Month January February March April May Portfolio Return 5.3% -2.5 -1.9 S&P 500 Return 5.6% -3.4 -1.3 1.7 0.4 -0.8 June July 0.6 -0.3 August September October November December -3.2 1.8 0.3

Can you please show calculations.

Answer 1

To calculate alpha, we have to perform regression of Portfolio return (dependent variable) with S&P returns (independent variable)

R-square = 0.95

Alpha = 0.11%

Beta = 0.92

Average return difference (with signs)	0.09%
Average return difference (without signs)	0.51%

A B C J H K L M N O P I Q SUMMARY OUTPUT 1 Month 2 Jan 3 Feb 4 Mar 5 Apr 6 May 7 Jun 8 Jul 9 Aug 10 Sep 11 Oct 12 Nov 13 Dec Portfolio return 5.3% -2.5% -1.9% 2.2% 0.7% -1.2% 0.2% 1.8% -0.6% -3.2% 2.7% 0.5% S&P 500 return 5.6% -3.4% -1.3% 1.7% 0.4% -0.8% 0.6% 2.3% -0.3% -4.0% 1.8% 0.3% D E F G Average Average return return differenc difference e (with (without signs) Formula signs) Formula -0.3% =B2-C2 0.3% =ABS(D2) 0.9% =B3-C3 0.9% =ABS(D3) -0.6% =B4-C4 0.6% =ABS(D4) 0.5% =B5-C5 0.5% =ABS(D5) 0.3% =B6-C6 0.3% =ABS(D6) -0.4% =B7-C7 0.4% =ABS(D7) -0.4% =B8-C8 0.4% =ABS(D8) -0.5% =B9-09 0.5% =ABS(D9) -0.3% =B10-C10 0.3% =ABS(D10) 0.8% =B11-C11 0.8% =ABS(D11) 0.9% =B12-C12 0.9% =ABS(D12) 0.2% =B13-C13 0.2% =ABS(D13) Regression Statistics Multiple R 0.975052 R Square 0.950726 Adjusted R Square 0.945799 Standard Error 0.005651 Observations ANOVA df 14 Regression Residual Total SS M S F ignificance F 1 0.006161 0.006161 192.9476 7.3E-08 10 0.000319 3.19E-05 11 0.006481 15 Average return difference (with signs) 16 Average return difference (without signs) 0.09% 0.51% Intercept S&P 500 return Coefficientsandard Errit Stat P-value Lower 95% Upper 95%ower 95.0% pper 95.0% 0.11% 0.001639 0.676021 0.514357 -0.00254 0.00476 -0.00254 0.00476 0.920794 0.066289 13.89056 7.3E-08 0.773092 1.068496 0.773092 1.068496 20