ACFI5041 Assignment Brief
\nPage 1 of 7
\nFaculty of Business and Law
\nACFI5041 – Assignment Brief
\nModule Title Financial Econometrics Assignment
\nNumber
\n1
\nModule Code ACFI5041 Assignment
\nTitle
\nFinal Assignment
\nModule Leader Freddie Ahiabor Assignment
\nWeighting
\n100%
\nAssignment Release
\nDate:
\n23rd February 2023
\nSubmission
\nDate\/Time:
\n11th May 2023
\nAssessment Information \u2013 What you need to do
\nThis assignment is an individual assignment.
\nThis assignment requires is split into four parts. The relevant data is provided on Blackboard.
\nPart One: Asset pricing and abnormal returns
\nSelect any ten (10) equities listed on the New York Stock Exchange (NYSE) or NASDAQ and
\ndownload their daily adjusted close price series from Yahoo Fund Screener or Refinitiv Eikon. In
\naddition, download data on the daily S&P 500 return (MKT-RF) and the risk-free rate (RF), small minus-big (SMB), and high-minus-low (HML) portfolios from the Fama-French website. The data
\nseries should cover the period from 1 January 2010 to 31 December 2022. Compile your data series
\ninto a single excel file and upload it to EViews.
\na) Construct an equal-weighted and price-weighted portfolios of all the 10 stocks you selected
\nand estimate the excess return on the two portfolios.
\nNote: The price-weighted portfolios should be estimated using the end-of-year adjusted
\nclose price for the equities and rebalanced annually. For instance, the end-of-year price of
\n2010 should be used as the weight for 2011, and so on.
\nThis document is for De Montfort University use and should not be passed to third parties or posted on any website.
\nACFI5041 Assignment Brief
\nPage 2 of 7
\nb) Estimate the capital asset pricing model (CAPM) and Fama-French Three Factor (FF3)
\nregressions for the equal-weighted and price-weighted portfolios and test for abnormal
\nreturn in each case.
\nc) Interpret the coefficients on the CAPM and FF3 regressions for the price-weighted
\nportfolios and comment on the statistical significance of all the coefficients.
\nd) Compare the CAPM and FF3 regression models using the Adjusted R-Squared and comment
\non how the model fits the data series.
\ne) Conduct a hypothesis test to determine if the residuals of the price-weighted regression
\noutputs are different from 0.
\nf) Discuss the normality of the residuals from the price-weighted portfolio regression using
\nthe Jarque-Bera and Kolmogorov-Smirnov tests.
\ng) Check for heteroskedasticity in the residuals for the price-weighted portfolio using the
\nWhite Test and BPG Test. Interpret your results.
\nh) Check for autocorrelation in the residuals for both equal-weighted and price-weighted
\nportfolios using the DW test and BG test. Interpret your results.
\n(30 marks)
\nPart 2: Time Series Modelling
\nChoose any two (2) equities from your portfolio in Part One and carry out the following analysis.
\na) Perform the Augmented Dickey-Fuller (ADF) and Phillip Perron (PP) testsfor stationarity on
\nthe price and return series of the equities you selected. Interpret your results fully.
\nb) Fit an appropriate ARMA (p, q) model for the return series using the Box-Jenkins
\nmethodology. Explain the Box-Jenkins procedure and how you implemented it.
\nc) Conduct an \u201cout-of-sample\u201d forecast for the last year (2022) based on the ARMA model
\nspecified in b) above and analyse the forecast accuracies using RMSE, MAPE and the Theil
\nInequality Coefficient. Comment on the quality of the forecast from the ARMA model.
\nd) Fit an ARCH(q) model for the two equity stocks. Comment on your choice of order q and
\ninterpret your ARCH (q) results.
\ne) Fit the appropriate GARCH model for the two equity stocks and test for the leverage effects.
\n(40 marks)
\nThis document is for De Montfort University use and should not be passed to third parties or posted on any website.
\nACFI5041 Assignment Brief
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\nPart 3: VAR and VECM models
\nChoose only one question from this section
\nPart 3A Vector Autoregressive Models
\nCollect quarterly on the following series from the FRED Database (Federal Reserve Bank
\nEconomic Data).
\n\u2022 Real Gross Domestic Product [GDPC1]
\n\u2022 Industrial Output [INDPRO]
\n\u2022 Consumer price index [USACPIALLMINMEI]
\n\u2022 Federal fund effective rate [FEDFUNDS]
\n\u2022 Yield spreads (difference between the US 3 months T-Bill and 10-Year Treasury Constant
\nMaturity Rate) [T10Y3M].
\nMerge the above data with:
\n\u2022 The quarterly returns on your price-weighted portfolio.
\n\u2022 The quarterly returns on the SP 500 index.
\nCompile all your data series in a single excel file for the period 2010Q1 to 2022Q4 and upload it
\nto EViews.
\na) Estimate an unrestricted vector autoregressive model for all the seven variables indicated
\nabove.
\nb) Conduct a Granger causality test between the returns on your price-weighted portfolio
\nand all the variables. Comment on your results thoroughly.
\nc) Conduct an impulse response analysis of all the factors on your price-weighted portfolio
\nreturns (ignoring all other impulse responses). Comment on your results thoroughly.
\n(20 marks)
\n3B Modelling long-run relationships (VECM)
\nFrom the Country data.xlsx file, select any six (6) market index series and
\na) Make five (5) pairs of data with one data series fixed and test for cointegration among the
\nvariables.
\nb) Critically comment on the assumptions used forthe co-integration tests and on your results
\nfor each of the cointegration tests in light of the following issues:
\nThis document is for De Montfort University use and should not be passed to third parties or posted on any website.
\nACFI5041 Assignment Brief
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\na) Is cointegration found for each pair of series?
\nb) What is the order of this cointegration?
\nc) Then perform a Johansen cointegration test on ALL FIVE pairs. Comment on whether
\ncointegration is present.
\nd) For any cointegrated pair of market indices, carryout a vector error correction modelling
\nand discuss if there are any long-run relationship
\n(20 marks)
\nPresentation of Report
\nThe written report should be around 3,500 words in length and word-processed. The main results
\nshould be reported in the main body of the report, while estimated outputs (EViews printouts)
\nshould be reported in the appendix.
\nWhere graphs and diagrams are relevant, they should be reported in the main report.
\nIn the report, you should:
\n\u2022 Explain the rationale behind your empirical tests and the methodology adopted also clearly
\nstate any assumptions made for any particular requirement. This part has to be concise and
\nprecise.
\n\u2022 You have to use the appropriate scientific rhetoric. Therefore, you should define clearly
\nyour null and alternative hypotheses tested in each stage of the analysis.
\n\u2022 Provide a clear definition and rationale of the techniques\/statistical tests used.
\n(10 marks)
\nCriteria for Assessment – How you will be marked
\nThe majority of the marks will be awarded to students that produce evidence of:
\n\u2022 Good understanding of the theory of models estimated.
\n\u2022 Good understanding of statistical procedures.
\n\u2022 Ability to link properly the first two points above and critical interpretation of the findings.
\nTherefore, the final assignment will be a report with all the Econometric output in the appendix.
\nThis document is for De Montfort University use and should not be passed to third parties or posted on any website.
\nACFI5041 Assignment Brief
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\nThe grade you achieve for this assignment will depend entirely on the level of understanding
\ndemonstrated in your report and your sound empirical backing.
\nFurther information on University mark descriptors can be found here.
\nThis assignment is designed to assess the following learning outcomes:
\n\u2022 Appraise the problems of non-stationarity in the data series and how these problems can
\nbe detected using unit roots and cointegration tests.
\n\u2022 Produce forecasts for ARMA and volatility models and evaluate the usefulness, relative
\nadvantages and disadvantages of VAR, ARCH and GARCH modelling.
\n\u2022 Apply the various techniques using standard econometric software (EViews, or STATA).
\nAssessment Details
\nLength: Maximum 3500 words.
\nStyle: Report using the Harvard system of referencing.
\nWeighting: 100% of total course assessment
\nThis is an individual exercise.
\nThere will be a penalty of a deduction of 10% of the mark for work exceeding the word limit by
\n10% or more.
\nThe word limit includes tables, figures, quotations and citations, but excludes the references list
\nand appendices
\nHow to Submit your Assessment
\nThe assessment must be submitted by 12:00 noon (GMT\/BST) on 11 May 2022. No paper copies
\nare required. You can access the submission link through the module web.
\n\u2022 Your coursework will be given a zero mark if you do not submit a copy through Turnitin.
\nPlease take care to ensure that you have fully submitted your work.
\n\u2022 Please ensure that you have submitted your work using the correct file format, unreadable
\nfiles will receive a mark of zero. The Faculty accepts Microsoft Office and PDF documents,
\nunless otherwise advised by the module leader.
\n\u2022 All work submitted after the submission deadline without a valid and approved reason will be
\nsubject to the University regulations on late submissions.
\no If an assessment is submitted up to 14 days late the mark for the work will be capped at the
\npass mark of 40 per cent for undergraduate modules or 50 per cent for postgraduate modules
\no If an assessment is submitted beyond 14 calendar days late the work will receive a mark of
\nzero per cent
\nThis document is for De Montfort University use and should not be passed to third parties or posted on any website.
\nACFI5041 Assignment Brief
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\no The above applies to a student\u2019s first attempt at the assessment. If work submitted as a
\nreassessment of a previously failed assessment task is submitted later than the deadline the
\nwork will immediately be given a mark of zero per cent
\no If an assessment which is marked as pass\/fail rather than given a percentage mark is
\nsubmitted later than the deadline, the work will immediately be marked as a fail
\n\u2022 The University wants you to do your best. However, we know that sometimes events happen
\nwhich mean that you can\u2019t submit your coursework by the deadline \u2013 these events should be
\nbeyond your control and not easy to predict. If this happens, you can apply for an extension
\nto your deadline for up to two weeks, or if you need longer, you can apply for a deferral,
\nwhich takes you to the next assessment period (for example, to the re-sit period following the
\nmain Assessment Boards). You must apply before the deadline. You will find information
\nabout applying for extensions and deferrals here.
\n\u2022 Students MUST keep a copy and\/or an electronic file of their assignment.
\n\u2022 Checks will be made on your work using anti-plagiarism software and approved plagiarism
\nchecking websites.
\nReturn of Marked Work
\nYou can expect to have feedback returned to you on 2 June 2023 (15 working days). If for any
\nreason there is a delay you will be kept informed. Marks and feedback will be provided online. It
\nis important that you access the feedback you receive as this will help to make improvements to
\nyour later work, you can request a meeting with your Module Leader or Personal Tutor to discuss
\nyour feedback in more detail.
\nMarks will have been internally moderated only, and will therefore be provisional; your mark will
\nbe formally agreed later in the year once the external examiner has completed their review.
\nMore information on assessment and feedback can be found here.
\nAcademic Integrity
\nIn submitting a piece of work for assessment it is essential that you understand the University’s
\nrequirements for maintaining academic integrity and ensure that the work does not contravene
\nUniversity regulations. Some examples of behaviour that would not be considered acceptable
\ninclude plagiarism, re-use of previously assessed work, collusion with others and purchasing your
\nassignment from a third party. For more information on academic offences, bad academic
\npractice, and academic penalties, please read chapter four of our academic regulations.
\nThis document is for De Montfort University use and should not be passed to third parties or posted on any website.
\nACFI5041 Assignment Brief
\nPage 7 of 7
\nAcademic Support and Your Well-being
\nReferencing is the process of acknowledging other people\u2019s work when you have used it in your
\nassignment or research. It allows the reader to locate your source material as quickly and easily
\nas possible so that they can read these sources themselves and verify the validity of your
\narguments. Referencing provides the link between what you write and the evidence on which it is
\nbased.
\nYou identify the sources that you have used by citing them in the text of your assignment
\n(called citations or in-text citations) and referencing them at the end of your assignment (called
\nthe reference list or end-text citations). The reference list only includes the sources cited in your
\ntext. The main referencing guide can be found here and includes information on the basics of
\nreferencing and achieving good academic practice. It also has tabs for the specific referencing
\nstyles depending on whether you require Harvard style used in business or OSCOLA style used by
\nthe Law school.
\nThe University has a wealth of support services available to students; further information can be
\nobtained from Student Gateway, the Student Advice Centre, Library and Learning Services and,
\nmost importantly, your Personal Tutor. If you are struggling with your assessments and\/or
\ndeadlines please do seek help as soon as possible so that appropriate support and guidance can
\nbe identified and put in place for you. More information can be found on the Healthy DMU
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