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FINM7403 Assignment
Creation date：2024-05-06 16:58:51
Belonging category：金融Finance
Assignment

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FINM7403 Assignment


Assignment Overview
This is an individual assignment total of 100 marks counting towards 30% of your final grade.
Assignment due: 20th May 2022 14:00. Submit electronically on Blackboard and Turnitin.
Part I: Testing the CAPM (20 marks)
In this part you are required to test the Capital Asset Pricing Model on 25 U.S. portfolios formed on
Size and Operating Profitability for the sample period from January 1963 to December 2020. You need
to download returns data from Professor Kenneth French’s website.1 The data includes:
1) 25 portfolios formed on U.S. Size and Operating Profitability returns (use monthly value-
weighted including dividend returns).
2) Fama/French 3 factors returns (monthly value-weighted returns).
Complete the following task:
A. Perform the CAPM test. Does the CAPM work empirically for the sample period from January
1963 to December 2020? Present the evidence to support the conclusion. (20 marks)

FINM7403 S1 2022 Assignment
2

Part II: Is the CAPM really dead? (45 marks)

The US Federal Reserve (FED) controls three tools of monetary policy - open market operations, the
discount rate, and reserve requirements. While the Board of Governors of the FED is responsible for
the discount rate and reserve requirements, the Federal Open Market Committee (FOMC) is responsible
for the open market operations. The FOMC holds eight regularly scheduled meetings per year. At these
meetings, the Committee reviews economic and financial conditions and determines the appropriate
stance of monetary policy. Based on the assessments, they will make important interest rate
announcements. FOMC announcements are perhaps the most-watched events in the financial markets
across the globe.

Download from the Assignment folder the “FOMC_dates.csv” file which contains all of the FOMC
scheduled meeting dates from 1997 to 2020.

Complete the following tasks:
A. Perform the CAPM test for FOMC periods as well as non-FOMC periods. Does the CAPM
work? Present evidence to support the conclusion. You need to perform the CAPM test on the
same 25 portfolios in Part I from 1997 to 2020. (10 marks)
B. Why do you think that the CAPM works/does not work in two different subperiods? Your
answer should demonstrate your understanding of relevant economic theories. Your
arguments/reasonings/discussions should be supported by academic and/or industry research.
(15 marks)
C. Repeat the analyses in Part II.A with 25 developed portfolios excluding U.S. portfolios formed
on Size and Book-to-Market Value.2 Is your conclusion similar or different from those of Part
II.B? Discuss the economic implications of your results. Your answer should demonstrate your
understanding of relevant economic theories. Your arguments/reasonings/discussions should
be supported by academic and/or industry research. (20 marks)

FINM7403 S1 2022 Assignment
3

Part III – Cash Flow Duration Strategy – Performance Evaluation (35 marks)

Goncalves (2021) proposes an active equity trading strategy – buy short-duration firms and sell long-
duration firms. You are required to evaluate the performances of ten portfolios formed on cash flow
duration as well as the long-short SML (buy short duration and sell long duration firms) portfolio from
July 1973 to June 2018.
You will need to download the data “duration_port.zip” from the Assignment Folder.3 Complete the
following tasks using value-weighted portfolio returns from July 1973 to June 2018.
A. Is SML profitable? Your answer should depend on several performance evaluation metrics
learnt in the course. For factor risk-adjusted returns, use CAPM and Fama-French factors. The
risk free rate and factors information can be downloaded in Part I above. (15 marks)
B. Do you think the SML profitability comes from risk or from mispricing? Your
arguments/reasonings/discussions should demonstrate your understanding of academic and/or
industry research. (20 marks)
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CMP7000A CMP-7038B Math 263 LAW3016 CS371 STAT 334 FIN0008 ACC3004 STAT 371 ​COMP1921 MTH201 ACCT2000 UN3412 CIV6000 MATHS 3021 MATE7014 ECON1 CIBC6035 LAW121G COMM 321 CSC8204R TTM2033 CSCI 2600 MAE 115 LNG302 CENV6175W1 ECON30019 CPS2015 BST969 DDES9015 AMATH242 CS 1151 N1592 ACCT600 EG503G SMM519 EC318 Ecstatistics EEE 471 MARK2051 Topology COM00037H ACCT3000 MTHM501 EG501V COM00055H BUSN9085 GGR273 MATH 2B ITD102 MA214 ECON0060 ECE3114 ECMM447 Mechanics CCT361H5S BSAN3210 WELF2001 Fin3001 RESP5001 STA 137 Linguistics 101 CSCI368 CMPSC497 LUBS3655 OMBA 5355 BUSM2562 ​BFF5902 CYBR7001 CULT2005 ECON 7720 MTRX3760 FSE598 ​LUE1001 MGSC 7100 CS3240 COSC7500 ACCT3091 INFOGR TRAN 2080 DESIGN CIVE215001 CIVE2360 CPSC 8430 FNCE2003 Stoichiometry INFS6023 Quantitative Method Math 21D ECE5179 Design ​ECON8022 Chemical DMS 213 ADM1370 BFF5902 BFF2701 AGRI10051 AMN400 ECON7322 ​FINC5090 ​MATH1052 ​SciComp Elec4622 ​FINS5516 ENG 101 MMM143 CS431CA2 BSAN2201 EBSC7070 ES9v9-10 PLIN0009 DATA 8 MATH 101 BCPM0097 ​MAT 237 BISM2201 EEE8099 Physics 11 ECE2238B Biostat 234 ​ECON30009 INF10025 CHEM252 CCMA4008 CIVE 3007 STAT0031 ELEC ENG 3108 MGMT90140 CHEM 252 STAT3016 MMM095 ​MMGT6016 Legal STAT 311 ELEC9764 COMP 370 TCS 3053 EECS 1021 FIT1051 C/C++ EE3C COMP2003J COM398 COMP51915 Simulator FIN42330 8PRO102 PGD ELEC5160 XJCO1921 COMP5123M INFS 2042 CHE1148H ECA5313 IN3329 Microsoft Modeling B15 2TT COMP3687 COMP2432 DMS2030 KAN4TSF CFKG CSE 5322 CSE 445 STATS 3DA3 CHC5223 COMP1048 EL3105 EECS 3221 CS231 ME 4434 ITP4510 ITP4501 CSCI 5708 Controller EECE 5699 CPEN 231L CPN programs CSC8016 MATU9D2 ENGN4213 2. SVM. (10 points) Consider an SVM classifier using RBF kernel, and finish the following python code to search for the optimum kernel parameter γ. You are required to calculate the RBF function and search yourself, instead of using functions in Scikit-Learn (sklearn). def parameter search(gamma list ,Xtr,ytr,Xts,yts ,...): """ Parameters gamma list: A list of RBF kernel parameter gamma to search for Xtr: Training data, shape (ntr,nrow,ncol) ytr: Training labels, shape (ntr,) Xts: Test data, shape (nts,nrow,ncol) yts: Test labels, shape (nts,) ... Add other parameters as needed Returns: gamma optimum: The gamma with minimum error on Xts, yts """ ... return gamma optimum
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