John Nankervis Email: email@example.com
Carlo Rosa Email: firstname.lastname@example.org
(Empirical Methods in Finance)
The assessment for BE953 is by this coursework and a Final Examination. This piece of coursework is worth 50% of the overall assessment of BE953. The requirements for this coursework are as follows:
The coursework consists of data manipulation, analysis and interpretation. Although you may discuss the project with others, the coursework must be written up individually. You may receive reduced or no marks if there are strong similarities between the work handed in by two or more people. All questions are to be answered. The word count of the project must be printed on the first page of the coursework. The maximum word count is 2000. The project should be double spaced and word processed. Your project should include a title page and a bibliography, which includes the full reference for all articles, books and other sources you have cited in the body of the text. The bibliography (and any footnotes) need not be included in the word count. EViews output should NOT be pasted directly into the project. You should present your EViews equation estimation output as it would be in published academic papers. (Look at some papers – sometimes output is in Tables, sometimes as estimated equations with s.e.s/t stats/p-values in brackets under the corresponding coefficient, together with appropriate diagnostic statistics and their p-values). Note that your coursework is to be submitted via Online Coursework Submission (OCS). The coursework should be uploaded to OCS by 23:59:59 on Thursday 28 January 2010 (Week 17). You will be offered the choice of printing off a watermarked copy (the watermark on the spine shows the lecturer, amongst other things, and the time of submission to the OCS). You should
print off ONE watermarked copy and submit this to the Graduate Administrator (Room 5N.5.6) by 4.00 p.m. on Friday 29th January, 2010. The printed copy will be marked and returned to you within 4 weeks. • More information concerning late submission of coursework or absence from in-class tests, can be found here: http://www2.essex.ac.uk/academic/services/students/crswk_pol.htm
YOU MUST READ THE INFORMATION WHICH FOLLOWS: In submitting coursework online it must be assumed that you have read and understood the following guidelines about plagiarism. Furthermore in doing so you are agreeing to your work being monitored by the JISC Plagiarism Detection System if a lecturer should deem it necessary to do so. University Regulation 6.12 & 6.13 states that 6.12(a) It is an academic offence for a student to cheat in any examination, or in any other submitted part of his or her University work, whether or not such work is formally assessed. "To cheat" includes: (i) to copy the work of another candidate or otherwise communicate with another candidate in an examination; (ii) to introduce any written, printed or electronically-stored information into an examination, other than material expressly permitted in the instructions for that examination; (iii) to use the work of others (whether in written, printed or some other form) without acknowledgement, where a judgement is made that the work has been the result of serious negligence or of intention to deceive; (iv) to repeat work previously submitted for a different assessed assignment without full acknowledgement of the extent to which that previous work has been used. (b) It is an academic offence for a student knowingly to assist another student to cheat in any examination, or in any other piece of work, the mark for which will count either towards the student's result for the year, or towards his or her final degree classification. (c) Allegations of academic offences involving cheating shall be dealt with in accordance with the Progress Procedures as determined by the Senate. Previous offences shall be taken into account. 6.13 In submitting any piece of University work (eg dissertation, thesis, essay or report) a student shall acknowledge any assistance received or any use of the work of others.
Data The data to be used can be found on Moodle under the heading "Coursework", and consists of two EViews workfiles: "interest_rates.wf1" and "question_2.wf1".
Questions 1. Open the workfile "interest_rates.wf1" and use the r_usa series (daily U.S. dollar-interest rate swaps of one-year maturity) which we will label rt and consider the following sample period: 01/02/1999 29/12/2000 (Note that this is not using all available data). Changes in interest rates can be formed by constructing the variable:
rt = rt – rt-1
(a) Graph rt and then calculate the correlogram. What does the correlogram suggest about the structure of the data? Estimate an ARMA(1,1) model for rt and express the results in equation form. Also estimate all other ARMA models from order (0,0) to (2,2) for rt . From your estimations which is the preferred model order? Explain why? (You do not need to report coefficient estimates for all the estimated models; just present a Table containing appropriate statistics). [25 marks] 2. Open the workfile "Question_2.wf1" and consider the following sample period: 1990M01 2002M01. Estimate the following regression: yt = 0 + 1x1t +2x2t + 3x3t + t (a) (b) Report and comment on the regression results. Conduct diagnostic checks of your regression results for: • • • (c) Heteroscedasticity (use White’s Test); Autocorrelation (1st order and 12th order); Normality.
Do you find any problem(s)? How do you suggest fixing it/them? [25 marks]
Open the workfile "interest_rates.wf1" and use the r_usa and r_euro (daily euro interest-rate swaps of one-year maturity) series in the worksheet "interest_rates" and consider the following sample period: 4/01/1999 29/12/2000 (Note that this is not using all available data). (a) Using an Augmented Dickey-Fuller test (Maximum lags: 25, Selection by Schwarz Information Criterion), assess whether r_usa and r_euro are unit root processes. In the context of the linear regression: r_eurot = 0 + 1 r_usat + t use the Engle-Granger method to assess whether r_usa and r_euro are cointegrated. (c) What is the economic interpretation of your results in part (b)? [25 marks]
Open the workfile "interest_rates.wf1" and use the r_usat series which we will label rt and consider the following sample period: 4/01/1999 30/06/2007. Estimate the following regression:
rt+1 = 0 + 1MPSt + t+1
where rt+1 is defined as rt+1 – rt and MPSt stands for the monetary policy shock, i.e. the surprise component of monetary policy actions as defined in Kuttner (2001). (a) Comment on your results. Moreover, explain the implications of the result obtained above for the concept of monetary policy effectiveness. Use the variable Dummyt (a dummy variable that is set to 1 for those observations where MPS is positive and zero otherwise) to estimate the following regression:
rt+1 = 0 + 1MPSt + 2 Dummyt MPSt + t+1
where the rest of the notation is the same as before. Comment on your results. (c) Discuss the potential for omitted variable bias in Equation (*) above. [25 marks]
Some useful references include (in order of increasing difficulty): Kuttner, K., 2001. Monetary policy surprises and interest rates: evidence from the Fed Funds futures markets. Journal of Monetary Economics, 47, 523–44. Wongswan, J., 2009. The response of global equity indexes to U.S. monetary policy announcements, Journal of International Money and Finance, 28, 344–365. Bernanke, B., Kuttner, K., 2005. What explains the stock market’s reaction to Federal Reserve policy? Journal of Finance, LX(3), 1221-1257. [mostly 1233-1235] Rigobon, R., Sack, B.P., 2004. The impact of monetary policy on asset prices. Journal of Monetary Economics, 51, 1553-1575. [advanced reading]