Economics Question

ECM1002 – ECONOMETRICS

ASSIGNMENT

This assignment is worth 40% of the total mark and has a length of a maximum of 1500 words, excluding the reference list. Specifically, maximum word count is 800 words in Section 1, and is not bound in Section 2. Your report should contain your answers to the questions from Sections 1 and 2 below and supporting Eviews outputs for Section 2. The data for Section 2 is stored in the file “ECM1002_Assignmentdata.wf1”, which is available in LMS. Note that this file is too large for the Student version of Eviews, so you will need to use the full version available from Virtual Desktop.

The assignment report should be handed into the drop box in LMS (in PDF form) by 23.59 pm Sunday in Week 11.

Required Assignment format: Font: Times New Roman, Font size: 12, Lines spacing: 1.5 lines.

Section 1 (15 marks: You can start this section now)

(Note: Maximum word count in this section: 800 words)

Read the following articles:

Fama, E.F and French, K.R. (1993). “Common risk factors in the returns on stocks and bonds”, Journal of Financial Economics, Vol. 33 (1), 3-56, https://doi.org/10.1016/0304-405X(93)90023-5.

Fama, E.F and French, K.R. (2015). “A five-factor asset pricing model”, Journal of Financial Economics, Vol. 116 (1), 1-22, https://doi.org/10.1016/j.jfineco.2014.10.010.

Question 1. (5 marks)

What are the advantages or disadvantages of Fama-French 5-factors in comparison with Fama-Frech 3-factors that was developed in 1993?

(Hint: You should read other related articles in the literature to have ideas for answering this question).

Question 2. (10 marks)

Perform an informative and attractive literature survey on the recent applications of the Fama-Frech five-factor asset pricing model.

(Hint: You are expected to synthesize, summarise, and compare recent articles that apply the Fama-French 5-factors model. There is no unique formula for this literature survey nor the number of papers you should read. However, you can keep in mind some questions while doing the survey, such as: What research questions do authors try to answer? What fields/areas of research that this model often is applied? What are the data (time, location, frequency, location/country/industry/fund/stock) of related articles? What are the author’s findings? Are these findings consistent/contradictory across similar papers? Are there any authors’ suggestions to improve the Fama-French 5-factors model?

Based on the literature survey, you can also give your own comments/suggestions for the future applications/extensions of the Fama-French 5-factors.

An example of a literature survey article:

Bhatti, M.I and Do, Q.H. (2019). “Recent Development in Copula and its Applications to the Energy, Forestry and Environmental Sciences”, International Journal of Hydrogen Energy, Vol. 44 (36), 19453-19473, https://doi.org/10.1016/j.ijhydene.2019.06.015.)

Section 2 (25 marks: You can start this section after Week 4)

(Note: Maximum word count is not bound in this section)

In this section, the following Fama-French five-factor asset pricing model is applied to answer econometrics-related questions.

in which:  is the excess return of stock/industry/portfolio i at time t.

and is the market excess return (or market risk premium).

The data for this section is stored in the file “ECM1002_Assignmentdata.wf1” in LMS. This is daily price data for the US market from 01 July 1963 to 29 April 2022. The data is collected from Kenneth R. French – Description of Fama/French Factors (dartmouth.edu).

Variables’ definitions for “ECM1002_Assignmentdata.wf1”:

the risk-free return (the 1-month T-bill return) at time t;

MKT_FT: the market excess return at time t;

SMB (Small Minus Big): difference between average return on small stock portfolios and average return on big stock portfolios at time t, indicating size premium;

HML (High Minus Low): difference between average return on value portfolios (high B/M stocks) and average return on growth portfolios (low B/M stocks) at time t, indicating value premium;

RMW (Robust Minus Weak): difference between the average return of robust portfolios and average return of weak portfolios at time t;

CMA (Conservative Minus Aggressive): difference between average return on conservative portfolios and average return on aggressive portfolios at time t;

NODURBL: the return on “Consumer Nondurables” industry at time t;

DURBL: the return on “Consumer Durables” industry at time t;

MANUF: the return on “Manufacturing” industry at time t;

ENERGY: the return on “Energy” industry at time t;

HITEC: the return on “Business Equipment” industry at time t;

TELCM: the return on “Telephone and Television Transmission” industry at time t;

SHOPS: the return on “Wholesale, Retail, and Some Services” industry at time t;

HEALTH: the return on “Healthcare, Medical Equipment, and Drugs” industry at time t;

UTILITIES: the return on “Utilities” industry at time t;

OTHER: the return on “Other” industry at time t.

The industry return data is allocated to you based on the last digit of your Student ID as below:

Question 1. (2.5 marks)

Estimate and report the Fama-French 5-factor estimated equation based on your allocated Industry return series. Interpret the meaning of the Coefficient of Determination.

(Note: Eviews outputs must be shown here. Incorrect use of industry return data will result in a Zero mark for this question)

Hint: Supported documents to answer this question can be found in week 5 materials.

Question 2. (2.5 marks)

Comment on the significance of the estimated coefficients and interpret the meanings of the slope estimates.

Hint: Supported documents to answer this question can be found in week 5 materials.

Question 3. (5 marks)

Perform a test for the model specification.

(Showing detailed steps including hypothesis, test statistics, decision rule, decision, and conclusion. Eviews outputs must be shown here).

Hint: Supported documents to answer this question can be found in week 8 materials.

Question 4. (5 marks)

Perform a test for the heteroskedasticity in the residuals.

(Showing detailed steps including hypothesis, test statistics, decision rule, decision, and conclusion. Eviews outputs must be shown here).

Hint: Supported documents to answer this question can be found in week 9 materials.

Question 5. (5 marks)

Perform a test for the autocorrelation in the residuals. Are the residuals follow a white noise process?

(Showing detailed steps including hypothesis, test statistics, decision rule, decision, and conclusion. Eviews outputs must be shown here).

Hint: Supported documents to answer this question can be found in weeks 10 and 11 materials.

Question 6. (5 marks)

1. (2 marks) Generate a time plot for your industry return series (it is not industry excess return) and discuss their basic time-series properties in relation to their main components.
2. (3 marks) Estimate an AR(1) model for your industry return series and discuss the estimation result. Check if the residual SACF shows a pattern of a white noise. Is the AR(1) model statistically adequate for your industry return series?

(Eviews outputs must be shown in the answers)

Hint: Supported documents to answer this question can be found in weeks 10 and 11 materials.