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# Finance & Accounting 作业代写

*Part 1 (10 marks)*

Compare and discuss the alpha, beta, factor loadings and idiosyncratic volatility for each stock for the full sample period. Specifically:

As can be seen from appendix, the level of significanceALPHA = 0.05, the five proposed portfolioCo-linear regression coefficients were 1.00,1.00,0.998,1.001,and0.998. The adjusted coefficient of determination were 0.998,0.999,0.999,0.999, 0.999, which are very close to 1; standard error estimates are very close to zero, corresponding to the F statistics.

Finance & Accounting 作业代写

Probability values are measured 0.000, highly significant, indicating that the regression model with three factors fit well, a high degree of interpretation.

By appendix we can see that excess market returns (coefficient b), asCAPM single-factor model and the three-factor model common explanatory variables, all combinations of coefficients. By the t-test, and all signs of the coefficients are positive. On five combinations were transported using Excel statistical analysis software stepwise multiple regression analysis method, we found that the earliest

Finance & Accounting 作业代写

Into the regression equation, i.e. the most relevant explanatory variables is the excess market returns. ThisDescription although excess market returns alone insufficient to fully explain a variable cross-section stock returns, Changes in the surface data, but yield different stocks and the market risk factor is indeed the difference betweenStock returns is caused by changes in cross-sectional data is one important reason. In other words, threeFactor model to a certain extent is the further improvement of the CAPM.

Company size factor coefficients s, a combination of the three small companies are positive, and both passafter a significant level of 1% t-test. Although large-scale company s portfolio significantly through the 1%Level test, but the sign is negative. Excluding the Loss City than factors, only from company sizeup analysis, showing large and small two combinations respective coefficients s are positive, and the big combination

Stock returns affect a significant factor. And from a point of view explains the small companies rather than large firms have higher excess returns of reasons - coefficient of sensitivity stronger.

Book market ratio factor coefficient h, high book-market ratio for the four combinations, exceptB / M portfolio outside the rest of the sign is positive, two low-book market combined with a slope of more thanNegative. In addition to carrying a small middle-market ratio portfolio, the coefficients of the remaining five combinations througha significance level of 1% of the t test.

Through the above models and the overall coefficient of each explanatory variable significance analysis results can be drawn

Factors that affect stock returns by no means only this three, as well as price-earnings ratio, price, distributionMarket, a number of factors such as the company's fundamentals, but considering there is no different between the explanatory variablesCorrelation with the degree, all factors are included in the regression equation will create multiple collinearProblems, but reduces the model's credibility. And of course, the model contains too many variables andCloser to the real world, but the ease of use is obviously greatly reduced. Therefore, I believe that threeFactor model can be used as a convenient and practical tools to help investors in the stock marketfor analysis and forecasting.

*Part 2 (6 marks)*You need to estimate the Fama-French three-factor model over two sub-periods: 1. August 2005 to July 2008, and 2. August 2008 to June 2012 Discuss the differences in betas and factor loadings that you observe between the two periods for each company. What do the results imply about the Fama-French three-factor model?

Regression model for the FF, the empirical results show that systemic risk population t-test values were passed l% significantLevel. Single factor CAPM model for reunification, also found that systemic risk population t-test values were adopted1% level of significance, once again confirms the mouth is an important impact on asset price volatility and reliability factors.

XOM |
||||||||

2005-2008 |
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |

Intercept |
0.00292648 | 0.000183429 | 15.95429446 | 1.09454E-18 | 0.00255546 | 0.0032975 | 0.00255546 | 0.0032975 |

Excess Returns (step 2) |
1.006216612 | 0.003367137 | 298.834449 | 3.8369E-67 | 0.999405934 | 1.01302729 | 0.999405934 | 1.01302729 |

Size Factor |
-0.00966143 | 0.008999226 | -1.073584515 | 0.289606899 | -0.027864082 | 0.008541223 | -0.027864082 | 0.008541223 |

Value Factor |
0.019146924 | 0.007066706 | 2.709455059 | 0.0099611 | 0.004853161 | 0.033440687 | 0.004853161 | 0.033440687 |

2008-2013 |
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |

Intercept |
5.39284E-05 | 8.8872E-06 | 6.068093198 | 5.63678E-07 | 3.59043E-05 | 7.19524E-05 | 3.59043E-05 | 7.19524E-05 |

Excess Returns (step 2) |
0.999824857 | 0.000174657 | 5724.495378 | 7.1725E-109 | 0.999470636 | 1.000179079 | 0.999470636 | 1.000179079 |

Size Factor |
0.000460753 | 0.000366394 | 1.257534619 | 0.216656868 | -0.000282329 | 0.001203835 | -0.000282329 | 0.001203835 |

Value Factor |
0.000326047 | 0.000361124 | 0.902867076 | 0.37259823 | -0.000406347 | 0.001058441 | -0.000406347 | 0.001058441 |

GOOG |
||||||||

2005-2008 |
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |

Intercept |
0.002934 | 0.000179 | 16.43176623 | 4.00768E-19 | 0.002573246 | 0.003296 | 0.002573 | 0.003296 |

Excess Returns (step 2) |
1.003926 | 0.001666 | 602.458042 | 5.14459E-79 | 1.000555381 | 1.007297 | 1.000555 | 1.007297 |

Size Factor |
-0.01427 | 0.008839 | -1.6142714 | 0.114531592 | -0.03214693 | 0.00361 | -0.03215 | 0.00361 |

Value Factor |
0.023921 | 0.006965 | 3.434643988 | 0.001421101 | 0.009833642 | 0.038008 | 0.009834 | 0.038008 |

2008-2012 |
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |

Intercept |
5.21E-05 | 8.99E-06 | 5.790695052 | 1.32342E-06 | 3.38204E-05 | 7.03E-05 | 3.38E-05 | 7.03E-05 |

Excess Returns (step 2) |
1.000017 | 0.000107 | 9354.206657 | 1.5065E-116 | 0.999799797 | 1.000233 | 0.9998 | 1.000233 |

Size Factor |
0.000478 | 0.000373 | 1.282419258 | 0.207892091 | -0.00027782 | 0.001233 | -0.00028 | 0.001233 |

Value Factor |
0.000284 | 0.000369 | 0.770477146 | 0.446044059 | -0.00046393 | 0.001032 | -0.00046 | 0.001032 |

BA |
||||||||

2005-2008 |
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |

Intercept |
0.003038 | 0.000174 | 17.49189 | 4.64999E-20 | 0.002686 | 0.003389 | 0.002686 | 0.003389 |

Excess Returns (step 2) |
1.006629 | 0.002179 | 461.9364 | 1.61871E-74 | 1.002221 | 1.011037 | 1.002221 | 1.011037 |

Size Factor |
-0.01145 | 0.008401 | -1.36321 | 0.180633926 | -0.02844 | 0.00554 | -0.02844 | 0.00554 |

Value Factor |
0.016331 | 0.006734 | 2.42521 | 0.020030155 | 0.00271 | 0.029951 | 0.00271 | 0.029951 |

2008-2012 |
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |

Intercept |
5.33E-05 | 9.38E-06 | 5.685699 | 1.82853E-06 | 3.43E-05 | 7.24E-05 | 3.43E-05 | 7.24E-05 |

Excess Returns (step 2) |
0.999955 | 0.000135 | 7419.815 | 6.3105E-113 | 0.999682 | 1.000228 | 0.999682 | 1.000228 |

Size Factor |
0.000497 | 0.000372 | 1.335089 | 0.190228842 | -0.00026 | 0.001252 | -0.00026 | 0.001252 |

Value Factor |
0.000362 | 0.000418 | 0.865601 | 0.39244125 | -0.00049 | 0.001209 | -0.00049 | 0.001209 |

NAFC |
||||||||

2005-2008 |
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |

Intercept |
0.002949 | 0.00019 | 15.51 | 2.84471E-18 | 0.002565 | 0.003334 | 0.002565 | 0.003334 |

Excess Returns (step 2) |
1.001013 | 0.001935 | 517.205 | 1.97394E-76 | 0.997098 | 1.004928 | 0.997098 | 1.004928 |

Size Factor |
-0.01201 | 0.009439 | -1.27238 | 0.2107716 | -0.0311 | 0.007082 | -0.0311 | 0.007082 |

Value Factor |
0.019936 | 0.007473 | 2.667864 | 0.011060929 | 0.004821 | 0.035052 | 0.004821 | 0.035052 |

2008-2012 |
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |

Intercept |
5.09E-05 | 8.67E-06 | 5.866771 | 1.04709E-06 | 3.33E-05 | 6.85E-05 | 3.33E-05 | 6.85E-05 |

Excess Returns (step 2) |
0.99986 | 9.83E-05 | 10174.74 | 7.3009E-118 | 0.999661 | 1.00006 | 0.999661 | 1.00006 |

Size Factor |
0.000596 | 0.000369 | 1.6147 | 0.115107815 | -0.00015 | 0.001346 | -0.00015 | 0.001346 |

Value Factor |
0.000303 | 0.000355 | 0.8549 | 0.39826046 | -0.00042 | 0.001023 | -0.00042 | 0.001023 |

LAD |
||||||||

2005-2008 |
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |

Intercept |
0.003077 | 0.000201 | 15.2722 | 4.78E-18 | 0.00267 | 0.003485 | 0.00267 | 0.003485 |

Excess Returns (step 2) |
1.002782 | 0.001789 | 560.4921 | 8.59E-78 | 0.999163 | 1.006401 | 0.999163 | 1.006401 |

Size Factor |
-0.01535 | 0.009452 | -1.62407 | 0.112417 | -0.03447 | 0.003768 | -0.03447 | 0.003768 |

Value Factor |
0.018058 | 0.00731 | 2.470389 | 0.017975 | 0.003273 | 0.032844 | 0.003273 | 0.032844 |

2008-2012 |
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% |

Intercept |
5.36E-05 | 9.17E-06 | 5.841158 | 1.13E-06 | 3.5E-05 | 7.21E-05 | 3.5E-05 | 7.21E-05 |

Excess Returns (step 2) |
0.99998 | 3.97E-05 | 25219.09 | 4.7E-132 | 0.999899 | 1.00006 | 0.999899 | 1.00006 |

Size Factor |
0.000565 | 0.000403 | 1.403241 | 0.169112 | -0.00025 | 0.001382 | -0.00025 | 0.001382 |

Value Factor |
0.0003 | 0.000364 | 0.826267 | 0.414096 | -0.00044 | 0.001038 | -0.00044 | 0.001038 |

As shown, each combination of RMRF yields are the same factors that the market excess return factors significantly correlated correlation coefficient close to 1, ie, the greater the market excess return factors, each combination of greater yields, which CAPM model analysis results are the same factors that each group of contracts SMB factors also positively related to firm size, but they are not very significant, BH, BL and BM three combinations of the correlation coefficient is low, averaging about 0.03, indicating that factors on the book market than large companies little effect on the yield of the stock and SH, SM and SL with three factors combined income rates with SMB correlation coefficients are high, an average of about 0.1, indicating that stocks relative to large firms in terms of small-scale company stock returns rate is influenced by its scale factor Similarly, five combined market value than its book income rates with the correlation coefficient factor is less than 0, and are more significant, the average correlation coefficients are about -0.2, indicating that the greater the company's HML factor , its stock will lower the yield.

*Part 3 (4 marks)*Provide a recommendation as to which of the five stocks you would advise an investor to purchase. You will need to provide an explanation as to how you reached your recommendation and any potential pitfalls of your recommendation.

In determining the financial asset prices in a variety of factors, systemic risk is fundamental factors session. FamaandFrench (1993) study suggests that except B, the scale factors and the difference between the carrying value ratio reflects the listed companiesProfitability and sustainability of its characteristics differ significantly, so in addition to systemic risk, the need to add two pairs of risk-sensitiveFactors that sense of scale factor (Size) and book value ratio factor (B / M). The easiest method of proof that recognize highRisk bring high returns - small companies and low book value means a higher risk than the company, but also meansHigher expected rate of return.

The recommendation for the investors should be the XOM and GooG , since they have a higher beta in the FF model as well as a more steady performance on the analysis above.From the above analysis of the correlation regression analysis, we draw: in the stock market, there are not only significant market premium, but there is also a significant size premium and the premium that book market than either large or small companies company stock returns , not only by the market premium factors, but also by the scale factors and the company carrying market ratio factors significantly affected, but the factors on stock returns of effect size is not the same market premium factors on stock returns the greatest impact, and presented positive stock returns and scale factors are also positively correlated, but the scale factors on stock returns significantly less than the impact of the stock market premium factor

Income rates with the company carrying a negative correlation factors than market value, ie the yield value stocks than growth stocks yield regression results from the model, we have seen the goodness of fit for each model were higher, indicating that the model interpretation ability, namely the applicability of the model in the national stock market strong.

### APPENDIX

XOM
SUMMARY OUTPUT |
IR=var of residuals |
|||||||

Regression Statistics |
||||||||

Multiple R |
0.999489919 | |||||||

R Square |
0.998980097 | |||||||

Adjusted R Square |
0.998941367 | |||||||

Standard Error |
0.001712989 | |||||||

Observations |
83 | |||||||

ANOVA |
||||||||

df | SS | MS | F | Significance F | Upper 95% | Lower 95.0% | Upper 95.0% | |

Regression |
3 | 0.227056734 | 0.075685578 | 25793.12391 | 4.9283E-118 | 0.001922696 | 0.001163921 | 0.001922696 |

Residual |
79 | 0.000231812 | 2.93433E-06 | 1.009380063 | 0.994915653 | 1.009380063 | ||

Total |
82 | 0.227288546 | 0.005059145 | -0.028913543 | 0.005059145 | |||

0.022889156 | -0.00723498 | 0.022889156 | ||||||

Coefficients | Standard Error | t Stat | P-value | Lower 95% | ||||

Intercept |
0.001543309 | 0.000190604 | 8.096936423 | 5.64336E-12 | 0.001163921 | |||

Excess Returns (step 2) |
1.002147858 | 0.003633452 | 275.8115037 | 1.208E-119 | 0.994915653 | |||

Size Factor |
-0.011927199 | 0.00853392 | -1.397622484 | 0.166138992 | -0.028913543 | |||

Value Factor |
0.007827088 | 0.007567167 | 1.034348615 | 0.304129201 | -0.00723498 |

GOOG

SUMMARY OUTPUT |
IR=var of residuals |
|||||||

Regression Statistics |
||||||||

Multiple R |
0.999854 | |||||||

R Square |
0.999708 | |||||||

Adjusted R Square |
0.999697 | |||||||

Standard Error |
0.001711 | |||||||

Observations |
83 | |||||||

ANOVA |
||||||||

df | SS | MS | F | Significance F | Lower 95.0% | Upper 95.0% | ||

Regression |
3 | 0.792289 | 0.264096429 | 90216.86939 | 1.6822E-139 | 0.001165 | 0.001921 | |

Residual |
79 | 0.000231 | 2.92735E-06 | 0.997556 | 1.005298 | |||

Total |
82 | 0.792521 | -0.03031 | 0.003887 | ||||

-0.00633 | 0.023594 | |||||||

Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |||

Intercept |
0.001543 | 0.00019 | 8.129671999 | 4.87204E-12 | 0.001165405 | 0.001921 | ||

Excess Returns (step 2) |
1.001427 | 0.001945 | 514.948733 | 4.7165E-141 | 0.99755644 | 1.005298 | ||

Size Factor |
-0.01321 | 0.00859 | -1.537993792 | 0.128046016 | -0.03031052 | 0.003887 | ||

Value Factor |
0.008631 | 0.007517 | 1.148165988 | 0.254364923 | -0.00633168 | 0.023594 |

BA

SUMMARY OUTPUT |
||||||||

Regression Statistics |
||||||||

Multiple R |
0.999787 | |||||||

R Square |
0.999574 | |||||||

Adjusted R Square |
0.999558 | |||||||

Standard Error |
0.001715 | |||||||

Observations |
83 | |||||||

ANOVA |
||||||||

df | SS | MS | F | Significance F | ||||

Regression |
3 | 0.544789 | 0.181596 | 61775.03424 | 5.3E-133 | |||

Residual |
79 | 0.000232 | 2.94E-06 | |||||

Total |
82 | 0.545021 | ||||||

Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |

Intercept |
0.001564 | 0.00019 | 8.245759 | 2.89233E-12 | 0.001187 | 0.001942 | 0.001187 | 0.001942 |

Excess Returns (step 2) |
0.998859 | 0.002513 | 397.5391 | 3.5363E-132 | 0.993858 | 1.00386 | 0.993858 | 1.00386 |

Size Factor |
-0.01194 | 0.008555 | -1.39563 | 0.166735081 | -0.02897 | 0.005089 | -0.02897 | 0.005089 |

Value Factor |
0.009604 | 0.008017 | 1.197934 | 0.234524535 | -0.00635 | 0.025561 | -0.00635 | 0.025561 |

NAFC

SUMMARY OUTPUT |
||||||||

Regression Statistics |
||||||||

Multiple R |
0.999849 | |||||||

R Square |
0.999699 | |||||||

Adjusted R Square |
0.999687 | |||||||

Standard Error |
0.001708 | |||||||

Observations |
83 | |||||||

ANOVA |
||||||||

df | SS | MS | F | Significance F | ||||

Regression |
3 | 0.76422 | 0.25474 | 87350.84236 | 6E-139 | |||

Residual |
79 | 0.00023 | 2.92E-06 | |||||

Total |
82 | 0.764451 | ||||||

Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |

Intercept |
0.001565 | 0.000189 | 8.296996 | 2.29744E-12 | 0.001189 | 0.00194 | 0.001189 | 0.00194 |

Excess Returns (step 2) |
1.001849 | 0.002017 | 496.7978 | 8.0243E-140 | 0.997835 | 1.005863 | 0.997835 | 1.005863 |

Size Factor |
-0.01364 | 0.00861 | -1.5847 | 0.11702912 | -0.03078 | 0.003493 | -0.03078 | 0.003493 |

Value Factor |
0.007431 | 0.007559 | 0.983038 | 0.328589906 | -0.00762 | 0.022477 | -0.00762 | 0.022477 |

LAD

SUMMARY OUTPUT |
||||||||

Regression Statistics |
||||||||

Multiple R |
0.999965 | |||||||

R Square |
0.99993 | |||||||

Adjusted R Square |
0.999928 | |||||||

Standard Error |
0.001682 | |||||||

Observations |
83 | |||||||

ANOVA |
||||||||

df | SS | MS | F | Significance F | ||||

Regression |
3 | 3.21289 | 1.070963 | 378332.4 | 4.3E-164 | |||

Residual |
79 | 0.000224 | 2.83E-06 | |||||

Total |
82 | 3.213114 | ||||||

Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |

Intercept |
0.001575 | 0.000186 | 8.472455 | 1.04E-12 | 0.001205 | 0.001945 | 0.001205 | 0.001945 |

Excess Returns (step 2) |
0.998147 | 0.001027 | 971.7088 | 7.8E-163 | 0.996103 | 1.000192 | 0.996103 | 1.000192 |

Size Factor |
-0.00645 | 0.008965 | -0.71993 | 0.473696 | -0.0243 | 0.011391 | -0.0243 | 0.011391 |

Value Factor |
0.010024 | 0.007441 | 1.347138 | 0.181787 | -0.00479 | 0.024834 | -0.00479 | 0.024834 |