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Applied Financial Econometrics
创建日期：2024-07-06 17:15:25
所属分类：金融Finance
标签： Financial
Applied Financial Econometrics

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Applied Financial Econometrics


Assessed Individual Project

Instructions

General instructions:

. This is an individual project.  It consists of two parts and is worth 35% of the marks for this course. Please complete both parts.

.  This project is due on Monday, 25 March 2024.  Please submit your work on Learn. The submission deadline is 12:00 pm.  Any submission received after the deadline will incur a default late penalty.

.  Please note that the project has a  15-page limit for texts, tables, figures, other related outputs, and references  (but not including do files).   Each part provides some guidance on page allocation. Because marks are not awarded for the amount written, you do not need to aim for this page limit (10 pages are likely enough).

Instructions on presentation:

.  Please include relevant estimated regression equations, figures, and tables in the main body of your document.  In terms of regression outputs, you are encouraged to type out the equations rather than pasting Stata outputs directly.  For example, if Stata produces the following output for an AR(1) model

.  reg  p  L.p

Source  |               SS                       df              MS             Number  of  obs       =          1,304

-------------+----------------------------------    F(1,  1302)            =   40302.75

Model  |     1.00989004                  1    1.00989004      Prob  >  F                =         0.0000

Residual  |     .032624992          1,302    .000025058      R-squared              =        0.9687

-------------+----------------------------------      Adj  R-squared      =        0.9687

Total  |     1.04251503          1,303     .000800088      Root  MSE                =        .00501


p

|

+

|

|

|

Coefficient

 

 

.9843575

Std .  err .

t

P>|t|

[95%  conf .

interval]

p L1 .

 

.0049033

 

200.76

 

0.000

 

.9747384

 

.9939767

_cons

|

.0180276

.0056456

3.19

0.001

.0069521

.0291031

you can present the equation as

 = 0.0180*** + 0.9844***pt−1 .

(0.0056)              (0.0049)

T = 1304, R2  = 0.9687

Alternatively, you can present a table with different sets of estimates, for example:

 

AR(1)

pt

AR(2)

pt

pt−1

0.9844*** (0.0049)

0.9409*** (0.0277)

pt−2

 

0.0441  (0.0277)

Constant

0.0180*** (0.0056)

0.0173*** (0.0057)

T

1304

1303

R2

0.9687

0.9688

* p<0.10.  ** p<0.05.  *** p<0.01.

. Equations, figures, or tables that you refer to should be appropriately and informa- tively labelled. For figures, please include axis titles and legend when appropriate.

.  State the significance level when you conduct a hypothesis test.

.  Make sure that you are aware of the requirements for appropriate citation of ref- erences and data sources.  Read the guidance on plagiarism in Section 4.4.1 of the Economics Honours Handbook and/or the general University guidance.  If you in- clude anything from another source it must be properly acknowledged, whether it’s a figure/table or a text passage or anything else.

.  Please format everything such that the marker can easily mark your work.  (For instance, please avoid using small fonts and single spacing.)

.  Penalty may be imposed on poorly presented work.

Instructions on do files:

.  Please include the do file in your submission. Projects submitted without a do file will incur the default penalty of a late submission.

. The do file should be written in such away that anyone with access to the raw data files can replicate the analysis.

. You are welcome to complete this project using other statistical software.  The same rules apply: Please submit an executable script. and include relevant output in the manuscript.

Part A

Note:   This part  is  worth  12%  of the final grade.   It  is  recommended  that you  allocate around three to four pages to this part.

Testing for unit root is crucial in financial econometrics, for many financial series contain unit roots that can affect statistical inference.  In class, we examined the Dickey-Fuller framework.  The framework has been extended in various ways since its introduction. Examples include

. allowing for structural breaks;

. different approaches to detrending the data;

. testing with stationarity as the null hypothesis.

Write a short essay (around 3–4 pages) on an extension(s) of the Dickey-Fuller framework. The essay can take one of the following broad and not necessarily mutually exclusive forms:

. An empirical analysis of a specific extension(s);

. A theoretical analysis of a specific extension(s);

. A literature review of the extensions proposed to date;

. A proposal of an extension(s) that fills a gap in the literature.

Some general guidelines:

.  Section 5.4 in the textbook provides a good starting point.

. Use appropriately defined mathematical notations when applicable.

.  Explain how the extension(s) complements the Dickey-Fuller framework.

. Discuss the limitations of the extension(s).

. Explore existing (or potential) applications of the extension(s).

Part B

Note:  This part is worth 23% of the final grade with each question weighted equally.  It is recommended that you allocate around one to two pages to each question.

Set-up:  For this part, you are invited to choose an exchange rate series for a pair of currencies.   Examples  include  GBP/EUR  (British pound to Euro) or USD/JPY  (US dollar to Japanese yen).

Sample period: You can decide which sample period to use, but the sample period should include an event (such as the COVID-19 pandemic) for later analysis.  A good rule would be to use 5 years of daily exchange rate data.

Time series: You will be working with two time series, the exchange rate series and the return series.  You can treat closing prices as the exchange rate series.  Then, construct the return series using either the simple return formula or the log return formula.

B1.  Provide appropriate descriptive statistics of the exchange rate series you have cho- sen to study.  Does your series exhibit characteristics that conform. to the stylised facts of financial returns data?

B2.  Use an appropriate model to produce ex ante forecasts for  exchange  rate  5  days ahead. Why have you chosen this model?

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ACCOUNTING BUSS1040 CHEM 181 MAT136H1 GY 6183 COMP3170 AGRI90089 PHYSICS 1002 ECON10003 IEOR E4004 ACS61012 MATH 40550 MKTG2113 TELE4653 ENSC1004 ECE 232E MK726 MTRX2700 SHEET 3 CSCA08 COMP30027 Math 2XX3 statistic MMAN3200 BISM7213 ECMM109 ECON 2022 FNCE 20005 GR5067 CSCB09 ME 3017 CS 5100 PHYS 2903 COMS 4771 COMP222 COMP 1046 CSC148H1 ISYS2038 FINS2615 OT5206 COMP2048 A6 MECH5770M MA826/20 CMPT 726 STA457 INFS6071 INFS588 integral ECON 216 IRDR 0017 MA323 PA 15213 PSYC2001 ENV222 Statistics ACCT5930 ACCT12 LAND2121 ME 5405 COMM1180 TELE3113 A7 ECE 568 ACCT2019 INFS1200 ENGG1340 CS 1400 ASST3 FINM7409 SWEN30006 INFO2222 FIN20150 SOSS1000 CSSE7231 FINS5513 COMS3200 CECN 702 ECON4060H MN3515 HW2 PSYA02H3 ECON 2112 COMP90051 CS 1652 MA30059 AF1605 MKTG7501 ECO-6003B COM4521 CTM ECON3350 COMP 3804 ELEC9762 BISM 7255 ST22 MATH20014 MNE3122 COMP343 MATH5165 ELE7029 ENGR30002 SEEM3500 ECON7350 RISK5002 FINM7405 COMP90059 MOS 3320B STAT 431 BISM7221 MATH3014 MTH783P EBA 35302 ACS133 BUS2206 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