Directions are copy and pasted in here as well as attached. Excel sheets with information are attached as well. Please help. Deadline is 9pm tonight.

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.

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 December 2016. You must use end-of-month data!

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:

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 your 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:

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.

This project must be completed individually. 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. 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 December 2016. You must use end-of-month data! 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: Note that t(Alpha) above means the t-statistic for the alpha estimate and that t(Beta-MRP) means the tstatistic 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 your 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, SmallGrowth: 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. Date 201401 201402 201403 201404 201405 201406 201407 201408 201409 201410 201411 201412 201501 201502 201503 201504 201505 201506 201507 201508 201509 201510 201511 201512 201601 201602 201603 201604 201605 201606 201607 201608 201609 201610 201611 201612 MRP -0.0332 0.0465 0.0043 -0.0019 0.0206 0.0261 -0.0204 0.0424 -0.0197 0.0252 0.0255 -0.0006 -0.0311 0.0613 -0.0112 0.0059 0.0136 -0.0153 0.0154 -0.0604 -0.0308 0.0775 0.0056 -0.0217 -0.0577 -0.0007 0.0696 0.0092 0.0178 -0.0005 0.0395 0.0050 0.0025 -0.0202 0.0486 0.0181 SMB 0.0087 0.0034 -0.0185 -0.0419 -0.0185 0.0301 -0.0422 0.0040 -0.0380 0.0428 -0.0205 0.0259 -0.0051 0.0051 0.0307 -0.0301 0.0090 0.0285 -0.0407 0.0052 -0.0261 -0.0193 0.0362 -0.0281 -0.0336 0.0083 0.0086 0.0068 -0.0027 0.0061 0.0290 0.0094 0.0200 -0.0441 0.0568 -0.0004 HML -0.0213 -0.0037 0.0503 0.0110 -0.0036 -0.0066 -0.0002 -0.0055 -0.0119 -0.0168 -0.0298 0.0212 -0.0347 -0.0173 -0.0045 0.0184 -0.0132 -0.0080 -0.0421 0.0271 0.0058 -0.0011 -0.0057 -0.0246 0.0226 -0.0048 0.0111 0.0325 -0.0179 -0.0149 -0.0098 0.0318 -0.0134 0.0415 0.0844 0.0352 RF Obs No. 0.0000 1 0.0000 2 0.0000 3 0.0000 4 0.0000 5 0.0000 6 0.0000 7 0.0000 8 0.0000 9 0.0000 10 0.0000 11 0.0000 12 0.0000 13 0.0000 14 0.0000 15 0.0000 16 0.0000 17 0.0000 18 0.0000 19 0.0000 20 0.0000 21 0.0000 22 0.0000 23 0.0001 24 0.0001 25 0.0002 26 0.0002 27 0.0001 28 0.0001 29 0.0002 30 0.0002 31 0.0002 32 0.0002 33 0.0002 34 0.0001 35 0.0003 36 List of Stocks in the S&P 500 Index on December 31, 2016: Ticker No. Ticker Symbol Company 3M Co 1 MMM 2 ABT Abbott Laboratories 3 ABBV AbbVie Inc. 4 ACN Accenture plc 5 ATVI Activision Blizzard 6 AYI Acuity Brands Inc. 7 ADBE Adobe Systems Inc 8 AAP Advance Auto Parts Inc. 9 AES AES Corp 10 AET Aetna Inc 11 AMG Affiliated Managers Group, Inc. 12 A Agilent Technologies Inc 13 APD Air Products & Chemicals Inc 14 AKAM Akamai Technologies Inc 15 ALK Alaska Air Group Inc. 16 ALB Albemarle Corp. 17 AA Alcoa Inc 18 ALXN Alexion Pharmaceuticals Inc 19 ALLE Allegion 20 AGN Allergan PLC 21 ADS Alliance Data Systems 22 LNT Alliant Energy Corp. 23 ALL Allstate Corp 24 MO Altria Group Inc 25 GOOGL Alphabet Class A 26 GOOG Alphabet Class B 27 AMZN Amazon.com Inc 28 AEE Ameren Corp 29 AAL American Airlines Group 30 AEP American Electric Power 31 AXP American Express Co 32 AIG American Intl Group Inc 33 AMT American Tower Corp A 34 AWK American Water Works Co. Inc. 35 AMP Ameriprise Financial Inc 36 ABC AmerisourceBergen Corp 37 AME Ametek 38 AMGN Amgen Inc 39 APH Amphenol Corp A 40 APC Anadarko Petroleum Corp 41 ADI Analog Devices Inc 42 ANTM Anthem Inc (formerly WellPoint Inc) 43 AON Aon plc 44 APA Apache Corp 45 AIV Apartment Investment & Mgmt 46 AAPL 47 AMAT 48 ADM 49 AJG 50 AIZ 51 T 52 ADSK 53 ADP 54 AN 55 AZO 56 AVGO 57 AVB 58 AVY 59 BHI 60 BLL 61 BAC 62 BK 63 BCR 64 BAX 65 BBT 66 BDX 67 BBBY 68 BRK.B 69 BBY 70 BIIB 71 BLK 72 HRB 73 BA 74 BWA 75 BXP 76 BSX 77 BMY 78 BF.B 79 CHRW 80 CA 81 COG 82 CPB 83 COF 84 CAH 85 KMX 86 CCL 87 CAT 88 CBG 89 CBS 90 CELG 91 CNC 92 CNP 93 CTL Apple Inc. Applied Materials Inc Archer-Daniels-Midland Co Arthur J. Gallagher & Co. Assurant Inc AT&T Inc Autodesk Inc Automatic Data Processing AutoNation Inc AutoZone Inc Avago Technologies AvalonBay Communities Inc Avery Dennison Corp Baker Hughes Inc Ball Corp Bank of America Corp The Bank of New York Mellon Corp Bard C.R. 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