ACFI3308: Financial Econometrics Assessment 1

Assessment Information – What you need to do

This assignment is an individual assignment.

You are the financial analyst for F&H Capital, a boutique investment firm located in New York. Your main task is to track US equities and make recommendations to the trading departments.

You are tasked to provide an “Equity Research Report” on a portfolio of 10 US equities based on a defined investment strategy.

The firm uses the Fama-French three-factor model to assess securities' return and risk characteristics.

The empirical Fama-French Three-Factor (FF3) model is specified as follows:

Rit = α + β1Rmt + β2SMBt + β3HMLt                          (1)

where:

 is the beta on the market portfolio (S&P 500).

 is the portfolio's alpha (intercept) and measures the underperformance or outperformance level.

β1 is the excess return on portfolio  at time 

α is the excess return on the market portfolio (S&P 500) at time 

Rit - RF Excess return of small cap over high cap firms at time 

Mkt - RFExcess return of value stock over growth stock at time 

The details of your report are itemised below.

SECURITY SELECTION AND PORTFOLIO CONSTRUCTION

1. Using an investment strategy, select 10 US equities from Refinitiv Eikon or Yahoo Finance. Explain how your investment strategy was implemented in the stock picking.

2. For each security, download the close price (or adjusted close price) series for the period

1 January 2018 to 31 July 2024.

3. Transform the monthly price series to a return series using the log return formula

4. Construct an equal-weighted portfolio return from the 10 stocks you selected.

5. Set the portfolio rebalancing to one (1) month.

PORTFOLIO RETURN AND STATISTICS

6. Plot the monthly return series of your equal-weighted portfolio.

7. Generate the following summary statistics for the equal-weight portfolio return.

(Mean, Median, Standard Deviation, Minimum, Maximum, Skewness, Kurtosis)

8. Discuss the portfolio summary statistics on profitability and volatility.

TIME SERIES REGRESSION

9. From the Fama-French website, download the monthly Fama-French-Three factor series directly into R from 1 January 2015 to 30 June 2023.

10. Estimate the Fama-French Three-Factor (FF3) regression using equation (2) above and the excess return on the equal-weighted portfolio as the dependent variable.

11. Interpret the coefficients on the FF3 regression and test for their statistical significance. Comment on the R-squared and F-statistics for the two asset pricing models.

12. Test for the unbiasedness of the CAPM regression model and discuss whether your model violates this theorem.

13. Re-estimate the CAPM and FF3 regression with heteroskedastic and autocorrelation consistent (HAC) standard errors. Comment on the difference between this result and the one estimated in step 10.

ROLLING REGRESSION MODEL

14. Re-estimate the FF3 model in equation (1), using a rolling regression model this time. The rolling regression should be based on a 36-month lookback window. The regression should be estimated using the heteroskedasticity and autocorrelation consistent (HAC) standard errors.

15. Plot the rolling betas (coefficients) on all the FF3 factors and the alpha (intercept) for your portfolio. This means you must plot the rolling window graphs for , , and the alpha (Intercept) term.

16. Discuss the pattern observed in these graphs and how they differ from those reported for FF3 in the previous section.

17. Using your plots of alpha and the beta on Mkt-Rf, comment on the impact of the COVID-19 pandemic on your portfolio’s performance.

Criteria for Assessment - How you will be marked

The marks will be allocated as follows:

SECURITY SELECTION AND PORTFOLIO CONSTRUCTION [10 MARKS]

· Rationale provided for the securities selected. [5 marks]

· Details on how the portfolio is constructed [5 marks]

PORTFOLIO RETURN AND STATISTICS                                                                                     [10 MARKS]

· Tabulation of summary statistics [5 marks]

· Discussion of economic rationale [5 marks]

TIME SERIES REGRESSION                                                                                                        [35 MARKS]

· Appropriate regression estimation outputs [5 marks]

· Interpretation and discussion of the regression estimates [10 marks]

· Comparison of the two asset pricing models [10 marks]

· Unbiasedness of OLS /autocorrelation/heteroskedasticity                                            [10 marks]

· Test of and heteroskedasticity

ROLLING REGRESSION MODEL                                                                                                 [30 MARKS]

· Appropriate regression estimation outputs [10 marks]

· Discussion of the rolling regression graphs [10 marks]

· Appropriate discussion of the impact of the Covid-19 pandemic on your

portfolio and choice of investment strategy [10 marks]

FORMAT OF REPORT [10 MARKS]

Executive summary, introduction, logical structure, and appropriate referencing.

Most of the marks will be given to students who produce evidence of:

· A good understanding of asset pricing models and time series analysis.

· A good understanding of time series regression analysis and forecasting.

· Critical thinking in the interpretation of the findings.

Further information on University mark descriptors can be found here.

Assessment Details

The written report should be 1,000 words (plus or minus 10%).

There will be a penalty of a deduction of 10% of the mark for work exceeding the word limit by 10% or more.

The word limit includes quotations and citations but excludes tables, figures, the references list, executive summary, and appendices.

Data analysis and model estimations are to be carried out using the R Statistical programme.

Using alternative packages/software will lead to a penalty of 15% of the total grade for this assessment.

This assignment is designed to assess the following learning outcomes:

(I) Evaluate the defining characteristics of the various types of stochastic processes as well as distinguish alternative financial econometric methodologies and effectively select the most appropriate one for the nature of the available data series.

(II) Perform and appraise business and economic forecasts using various econometrics techniques.

(III) Effectively communicate orally or in writing conceptually challenging concepts and ideas.

How to Submit your Assessment

Two separate files must be submitted for this assessment.

The assessment (Report) must be submitted by 12:00 noon (GMT/BST) on 6 July 2024 via Turnitin on the ACFI3308 module shell in LearningZone. No paper copies are required. You can access the submission link through the module web.

The R Script and data used for the assessment must be submitted separately using the OneDrive link below on 16 July 20924 at 12:00 noon.

OneDrive R Script and Data Submission Link

No paper copies are required. You can access the submission link through the module web.

· Your coursework will be given a zero mark if you do not submit a copy through Turnitin. Please take care to ensure that you have fully submitted your work.

· Please ensure that you have submitted your work using the correct file format, unreadable files will receive a mark of zero. The Faculty accepts Microsoft Office and PDF documents, unless otherwise advised by the module leader.

· All work submitted after the submission deadline without a valid and approved reason will be subject to the University regulations on late submissions.

o If an assessment is submitted up to 24 hours late the mark for the work will be capped at the pass mark of 40 per cent for undergraduate modules or 50 per cent for postgraduate modules

o If an assessment is submitted beyond 24 hours late the work will receive a mark of zero per cent

o The above applies to a student’s first attempt at the assessment. If work submitted as a reassessment of a previously failed assessment task is submitted later than the deadline the work will immediately be given a mark of zero per cent

o If an assessment which is marked as pass/fail rather than given a percentage mark is submitted later than the deadline, the work will immediately be marked as a fail

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