Lynn University Yahoo Finance Stock Analysis this is the project for investment class (finance) about stocks. I have the screenshot of the requirements and

Lynn University Yahoo Finance Stock Analysis this is the project for investment class (finance) about stocks. I have the screenshot of the requirements and it explains there what mainly needs to be done. The objectives of this exercise:
1. To perform multiple regression with real financial data.
2. To estimate the Fama – French 3-factor model for a list of twenty
stocks and interpret the regression output.
3. To discern whether individual stocks are small, mid or large cap
and value, neutral or growth.
Learning Outcomes:
Students should be able to:
1. Perform Ordinary Least Squares regression to estimate the Fama –
French 3-factor model.
2. Perform proper inference with correct interpretation of t-statistics
or p-values.
3. Discern whether a stock return significantly loads on one or more
of the three factors.
4. Tabulate regression results and discuss empirical findings.
Guidelines:
1. You will be assigned twenty (20) stocks from the current S&P 500
index. You must use the same 20 stocks (or, more precisely, the ticker
symbols) you used for Project 1. The last month of return data should
be August 2019. You must use end-of-month data! (This data
should be what you already collected from Yahoo Finance for Project
1.)
2. You must estimate the Fama and French 3-factor model. Thirty-six
months of the three factors along with the risk-free-rate in decimal
form will be provided in the accompanying Excel spreadsheet. Use
these factors and the risk-free rate provided to you. The factors are
MRP (BKM call this RM), SMB and HML. Note, you need excess
returns for your stocks. Estimating the Fama and French 3-factor
model requires the use of regression software. Answer the following
question:
a. How, exactly, do Fama and French construct their SMB and HML
factors?
3. For each firm, perform a multiple regression to estimate the
parameters in equation (10.11) of BKM 9th ed. Then complete a
Table:
Beta –
Beta –
Alpha t (Alpha) MRP t (Beta-MRP) SMB
Beta
t (Beta-SMB) HML
t(Beta-HML)
Firm
ABC
DEF
GHI
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C
Monthly returns in decimal
Sheet2
Sheet3
Obs No.
1
2
3
4
5
6
7
8
9
Date
201609
201610
201611
201612
201701
201702
201703
201704
201205
201206
201707
201702
201709
201710
201711
201712
201801
201802
201803
201804
201805
201806
201807
201808
201809
201810
201811
201812
201901
201902
201903
2019014
201905
201906
201907
201908
MRP
0.0025
-0.0202
0.0486
0.0182
0.0194
0.0357
0.0017
0.0109
0.0106
0.0078
0.0187
0,0016
0.0251
0.0225
0.0312
0.0106
0.0558
-0.0365
-0.0235
0.0029
0.0265
0.0048
0.0319
0.0144
0.0006
-0.0768
0.0169
-0.0955
0.0841
0.034
0.011
0.0396
-0.0694
0.0693
0.0119
-0.0287
SMB
0.0202
-0.0439
0.0547
0.001
-0.0104
-0.0202
0.012
0.0071
-0.0254
0.0216
-0.0141
-0.0167
0.0455
-0.0194
-0.0166
-0.0128
-0.0304
0.0025
0.0395
0.0112
0.0523
0.0118
-0.0218
0.0115
-0.0237
-0.0476
-0.0X179
-0.0263
0.0301
0.0206
-0.0313
-0.0168
-0.012
0.0033
-0.0206
-0.0326
HMI
-0.0149
0.0416
0.0829
0.0358
-0.0278
-0.0179
-0.0317
-0.0187
-0.0378
0.0135
-0.0028
-0.0224
0.0303
-0.0005
-0.0005
0.0014
-0.0138
-0.0119
-0.0012
0.0054
-0.0316
-0.0238
0.004
-0.0408
-0.013
RF
0.0002
0.0002
0.0001
0.0003
0.0004
0.0004
0.0003
0.0005
0.0006
0.0006
0.0007
0.0009
0.0009
0.0009
0.0008
0.0009
0.0011
0.0011
0.0012
0.0014
0.0014
0.0014
0.0016
0.0016
0.0015
0.0019
0.0018
0.0019
0.0021
0.0018
0.0019
0.0021
0.0021
0.0018
0.0019
0.0078
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
0.0025
-0.0147
-0.0062
-0.0284
-0.0407
0.0193
-0.0239
-0.0108
0.0012
-0.0239
26
27
28
29
30
31.
32
33
34
35
36
< 3. For each firm, perform a multiple regression to estimate the parameters in equation (10.11) of BKM 9th ed. Then complete a Table: Beta - Beta - Beta - Alpha t (Alpha) MRP t(Beta-MRP) SMB t(Beta-SMB) HML t (Beta-HML) Firm ABC DEF GHI JKL Etc. Note that t(Alpha) above means the t-statistic for the alpha estimate and that t(Beta-MRP) means the t-statistic for the beta coefficient estimated for the MRP factor, etc. 4. Then, using the results from your multiple regressions, identify the "style” for each of your 20 firms. In our write-up, be sure to explain how you identified the various styles. Styles include Large-Neutral, Large-Value, Large-Growth, Mid-Neutral, Mid -Value, Mid-Growth, Small-Neutral, Small-Value, Small-Growth: Style Firm ABC DEF GHI JKL Etc. Output: You must submit a brief write-up of your results. Your paper should be detailed enough so that someone else could pick up your paper and replicate your results. So, you will need a brief introduction describing your data sources, how you manipulated the data, how you calculated the Fama-French betas, 2 Tables, and a brief summary and discussion of your findings. In total, you must submit: 1. Your write-up as a Word file. 2. An Excel spreadsheet (one sheet) containing the two Tables detailed above. 3. Another Excel spreadsheet detailing how, exactly, you calculated the results in your Table (i.e., replicate the detailed findings for your stocks). Note that the Excel spreadsheets in points 2 and 3 should be in one file with two different labeled worksheet tabs. Alternatively, you may use 20 Excel sheets named with the ticker symbol if you wish to combine the date, ticker symbol, adjusted closing prices, and calculations and/or regressions separately for each of your 20 companies. Purchase answer to see full attachment