Background information for Question One
In Question One, we have provided cross-market time series data for Bitcoin (one of the popular
cryptocurrencies floating in the market). The Bitcoin is traded in various currencies, such as in Euros,
USD, Korea, etc. The data have been collected from Coincheck (one of the platforms that provides
aggregate price data for Bitcoin). In the Blackboard site of the course (see Assignment folder), we
have included Bitcoin price data for six exchange markets (Europe, USA, Australia, Korea, Japan,
You can choose ANY file(s) depending on your interest. Eviews, Stata, R, Python or other any
econometric software may be used for empirical estimation purpose.
Tasks for Question One
(1) By plotting the selected Bitcoin price series, explain if you find any ‘trend’ in the price
behaviour. Use Hodrick-Prescott (H-P) Filtering Technique and Hamilton Filtering Techniques
respectively to extract the ‘cycles’ from the ‘trends’. Plot the Autocorrelation Function and
comment on the persistence behaviour of the series.
(2) Test for (non-)stationarity in the selected series by using Augmented Dickey-Fuller, PhillipsPerron, and KPSS tests. Use options of intercept with and without trend term to compare your
results. What implications do the ‘presence or absence of a unit root’ imply for the selected
Bitcoin price regarding ‘weak, strong, semi-strong efficiency’ of the Bitcoin market?
(3) Assume that the Bitcoin series you selected is neither I(1) nor I(0). Then what would an I(d)
with 0<d<1 assumption imply for the Bitcoin market with respect to Efficient Market
(4) Use any THREE Bitcoin prices from the list and find if there is any error-correction mechanism
at work among them. Describe in detail, with regard to these specific selected series, a 3-
variables cointegration and Vector Error Correction system.
Background information for Question Two
Your task is to test a hypothesis (see topics below). You need to discuss the following steps:
(1) data collection (e.g. method of sampling, data sources, selection criteria);
(2) definition of variables (e.g. control variables);
(3) model specification (e.g. Unit root, Cointegration framework; ARCH/GARCH models);
(4) interpretation of findings and conclusion.
SEMESTER 2 2020/21
Faculty of Social Sciences
To illustrate your empirical findings, you are expected to use tables and figures.
Recommended data sources: Datastream, Bankscope, FAME, Yahoo Finance
Please select one of the following topics / hypothesis.
2.1. Economic policy uncertainty is known to exert a statistically significant and negative
impact on bond yields. This is consistent with the theory that investors tend to increase
their demands in bonds during periods of higher economic or government policy
uncertainty and thereby increasing bond prices and reducing their yields.
HINT: You can examine the relationship between Economic Policy Uncertainty (EPU) of a country
(see data here: https://www.policyuncertainty.com/) on future bond excess return across maturities
and holding periods for the chosen markets.
You can collect bond data from the database of the US Treasury for the US data and the Bank of
England for the UK data, for instance. The data of US government bonds are updated daily at website:
https://www.treasury.gov/resource-center/data-chart-center/interest-rates. The data of UK government
bonds are daily updated at website: https://www.bankofengland.co.uk/statistics/yield-curves.
You can try to use unit root tests (to identify non-stationarity) and cointegration methods to
understand the nature of co-movement between the variables.
2.2. Test the following hypothesis: “(Regional) housing prices depict strong spillover effects”.
HINT: You can calculate volatility in housing prices (within a country across regions or if you want
across countries within a common economic union, such as Europe Economic Union). Try to use
different types of GARCH models to estimate spillover effects (read literature).
SEMESTER 2 2020/21
Faculty of Social Sciences
Nature of Assessment: This is a SUMMATIVE ASSESSMENT. See ‘Weighting’ section above for the percentage that this
assignment counts towards your final module mark.
Word Limit: +/-10% either side of the word count (see above) is deemed to be acceptable. Any text that exceeds an
additional 10% will not attract any marks. The relevant word count includes items such as cover page, executive
summary, title page, table of contents, tables, figures, in-text citations and section headings, if used. The relevant word
count excludes your list of references and any appendices at the end of your coursework submission.
You should always include the word count (from Microsoft Word, not Turnitin), at the end of your coursework
submission, before your list of references.
Title/Cover Page: You must include a title/ cover page that includes: your Student ID, Module Code, Assignment Title,
Word Count. This assignment will be marked anonymously, please ensure that your name does not appear on any part
of your assignment.
References: You should use the Harvard style to reference your assignment. The library provide guidance on how to
reference in the Harvard style and this is available from: http://library.soton.ac.uk/sash/referencing