This exercise allows you to execute a performance evaluation similar to the examples provided in the lesson and reading.

Download theFSCRX Data (EXCEL)that will be used for this assignment.

A spreadsheet containing 36 months of data (2016-2018) for the Fidelity Small Cap Discovery Fund and risk factors is provided here. Using the FSCRX data spreadsheet,

A. Estimate a one factor, or CAPM, regression analysis of the following form:

R_i- R_f=_i+_i(R_M- R_f)

Or, using the labels provided with the dataset

Rfund-rf=_i+_i(mktrf)

B. Estimate a three factor, orFama-French, regression analysis of the following form:

R_i- R_f=_i+_i(R_M- R_f) + s_iSMB + h_iHML

Or, using the labels provided with the dataset

Rfund-rf=_i+_i(mktrf) + s_i(smb) + h_i(hml)

C. Estimate a four factor regression analysis of the following form:

1. R_i- R_f=_i+_i(R_M- R_f) + s_iSMB + h_iHML + u_iUMD

Or, using the labels provided with the dataset

Rfund-rf=_i+_i(mktrf) + s_i(smb) + h_i(hml) + u_i(umd)

1. Provide the Excel output for each regression analysis.
2. Discuss the results as they relate to exposures to the risk factors in each model. Is there evidence that this fund had particularly noteworthy performance during the 36-month period analyzed?

dateff mktrf smb hml umd rf Rfund Rfund-rf

20160129 -0.0577 -0.0336 0.021 0.0137 0.0001 -0.06359 -0.06369

20160229 -0.0007 0.0078 -0.0048 -0.0409 0.0002 0.025465 0.025265

20160331 0.0696 0.0087 0.0112 -0.0514 0.0002 0.079227 0.079027

20160429 0.0092 0.0068 0.0326 -0.0623 0.0001 0.015705 0.015605

20160531 0.0178 -0.0026 -0.0181 0.0194 0.0001 0.011147 0.011047

20160630 -0.0005 0.0065 -0.0149 0.0421 0.0002 -0.01956 -0.01976

20160729 0.0395 0.0265 -0.0113 -0.0305 0.0002 0.044251 0.044051

20160831 0.005 0.0115 0.0331 -0.0309 0.0002 0.003473 0.003273

20160930 0.0025 0.0202 -0.0148 -0.0055 0.0002 0.002077 0.001877

20161031 -0.0202 -0.0437 0.0418 0.0065 0.0002 -0.04318 -0.04338

20161130 0.0486 0.0549 0.0827 -0.0422 0.0001 0.119856 0.119756

20161230 0.0182 0.0007 0.036 -0.0036 0.0003 0.024528 0.024228

20170131 0.0194 -0.0102 -0.0278 -0.0097 0.0004 0.005373 0.004973

20170228 0.0357 -0.02 -0.018 -0.0166 0.0004 0.001257 0.000857

20170331 0.0017 0.0119 -0.0318 -0.0092 0.0003 0.000628 0.000328

20170428 0.0109 0.0073 -0.019 0.0053 0.0005 0.005648 0.005148

20170531 0.0106 -0.0255 -0.0378 0.0147 0.0006 -0.01779 -0.01839

20170630 0.0078 0.0216 0.0132 -0.0025 0.0006 0.025836 0.025236

20170731 0.0187 -0.014 -0.0028 0.0163 0.0007 -0.00226 -0.00296

20170831 0.0016 -0.0169 -0.0224 0.0357 0.0009 -0.02391 -0.02481

20170929 0.0251 0.0454 0.0303 -0.012 0.0009 0.04237 0.04147

20171031 0.0225 -0.0194 -0.0006 0.043 0.0009 0.021912 0.021012

20171130 0.0312 -0.0066 -0.0005 -0.0075 0.0008 0.017402 0.016602

20171229 0.0106 -0.0126 0.0014 -0.016 0.0009 0.001762 0.000862

20180131 0.0558 -0.0303 -0.0137 0.0393 0.0011 0.018054 0.016954

20180228 -0.0365 0.0028 -0.0119 0.0398 0.0011 -0.02726 -0.02836

20180329 -0.0235 0.0393 -0.0011 -0.0126 0.0012 -0.00439 -0.00559

20180430 0.0029 0.011 0.0053 0.0027 0.0014 0.004069 0.002669

20180531 0.0265 0.0524 -0.0316 0.0376 0.0014 0.032421 0.031021

20180629 0.0048 0.0117 -0.0239 -0.0243 0.0014 -0.00645 -0.00785

20180731 0.0319 -0.0215 0.0039 -0.0161 0.0016 0.005313 0.003713

20180831 0.0344 0.0123 -0.0412 0.053 0.0016 0.020008 0.018408

20180928 0.0006 -0.0237 -0.0134 -0.0009 0.0015 -0.01851 -0.02001

20181031 -0.0768 -0.0468 0.0341 -0.0182 0.0019 -0.08107 -0.08297

20181130 0.0169 -0.0074 0.0019 -0.014 0.0018 0.017234 0.015434

20181231 -0.0955 -0.026 -0.0151 0.0173 0.0019 -0.09717 -0.09907