UNIT CODE: ACFIM0013
UNIT NAME: Dissertation (MSc FinTech)
DEADLINE: [1 April 2025] before 13:00 (BST)
SUBMIT TO BLACKBOARD UNIT SUBMISSION POINT
Overview
• Your summative individual coursework represents 25% of the final mark for the unit.
• The coursework is in the form of an essay.
• Penalties will apply if the coursework is submitted late.
• You will be required to make a plagiarism statement and your submission will be tested for originality.
• The strict maximum word allowance is 2,000 words (excluding the title page, list of references, tables and figures). You must include a word count at the start of your essay.
Coursework requirement
Your task is to write a short research paper on one of the two topics.
A description of the topic, requirements and recommended reading are given below. You are required to formulate research question(s)/hypotheses and download appropriate data. Use relevant method/s, and present, interpret and discuss your results in a written report. The purpose of this coursework is to develop your analytical and research skills as a precursor to the dissertation.
Research Topic 1: Examine the impact of rising adoption of mobile banking on financial inclusion (access to and usage of formal financial services).
Recommended reading:
Erel, I., & Liebersohn, J. (2022). Can FinTech reduce disparities in access to finance? Evidence from the Paycheck Protection Program. Journal of Financial Economics, 146(1), 90-118.
https://doi.org/10.1016/j.jfineco.2022.05.004
Yang, T., & Zhang, X. (2022). FinTech adoption and financial inclusion: Evidence from household consumption in China. Journal of Banking & Finance, 145, 106668.
https://doi.org/10.1016/j.jbankfin.2022.106668
Requirements:
i. Use annual, country-level data from datasets such as Financial Access Survey (FAS) by the International Monetary Fund and the World Bank Development Indicators (WDI).
ii. Choose at least five countries. The final panel data must have at least 80 observations.
iii. Select an appropriate measure for mobile banking, for example number/density of mobile money accounts or value/number of mobile money transactions
iv. Select an appropriate measure for financial inclusion, for example number/density of bank accounts, depositors/borrowers, outstanding credit.
v. Focus on the model specification and the use of suitable independent/control variables.
vi. Use appropriate quantitative technique/s and relevant diagnostic/robustness tests to evaluate the validity of results.
Research Topic 2: Forecast the returns for two cryptocurrencies and compare the results.
Recommended Reading
Pečiulis, T., Ahmad, N., Menegaki, A. N., & Bibi, A. (2024). Forecasting of cryptocurrencies:
Mapping trends, influential sources, and research themes. Journal of Forecasting.
https://doi.org/10.1002/for.3114
Berger, T., & Koubová, J. (2024). Forecasting Bitcoin returns: Econometric time series analysis vs. machine learning. Journal of Forecasting, 43(7), 2904-2916.https://doi.org/10.1002/for.3165
Requirements
i. Choose any two cryptocurrencies.
ii. The final time series data must have at least 500 observations divided suitably between in- sample and out-of-sample.
iii. Use appropriate quantitiative technique/s and diagnostic tests.
iv. Justify the choice of model/s and number of lags if relevant.
v. Estimate both static and dynamic forecasts.
vi. Comment on the precision of the forecasts by calculating forecast error measures.
vii. Use graphs to support the interpretation and discussion of results.
Structure:
- TitIe page 一 a titIe and word count; your names shouId not appear anywhere in the document;
- Abstract 一 this is a short summary of the probIem considered, main resuIts and concIusions; check abstracts in papers pubIished in good journaIs for exampIes; it has to be between 100-150 words
- Introduction 一 this section wiII introduce your research question(s), give a theoreticaI context, say what data you use and briefIy outIine your resuIts; the introduction is aIways the most important seIIing point of academic work; try to present why reIevance and significance of the topic.
- Literature background 一 in this part you shouId present the context of your empiricaI work; the number of articIes you shouId cite may vary by research question, but we wouId normaIIy expect 8-12 references; do not cite more than 20 sources; if appIicabIe, be cIear on the theory behind your anaIysis; from the background you present it shouId be cIear what your expected resuIts are (i.e. what the academic Iiterature found in reIation to your research question); remember to make appropriate referencing; pIease review the accompanying materiaI on writing a criticaI Iiterature review (and the sources mentioned therein). Take this opportunity to review the readings of the Iecture about conducting empiricaI research.
- MethodoIogy 一 in this part you wiII briefIy expIain the approach and methodoIogy of your empiricaI tests; if you wish, you can combine this section with‘Data’; try to keep this part brief unIess you appIy“non-standard”methods, which shouId be discussed in detaiI. Methods not covered during this unit can be considered as“non-standard”.
- Data 一 this section wiII expIain how you seIected your sampIe, and what your data sources are; the description of your data and what you do with it shouId be detaiIed enough that the reader can reproduce your anaIysis; if possibIe, show how various restrictions affect your sampIe.
- ResuIts 一 in this section you wiII present aII your empiricaI resuIts; you shouId carefuIIy interpret and discuss your resuIts and criticaIIy present how they answer your research question(s); make reIevant references to the Iiterature and compare previous findings with yours.
- ConcIusions 一 this section wiII summarise the report, repeat your research question(s) and main findings; you shouId aIso briefIy comment on Iimitations of your study and present how it couId be extended in future research;
- References 一 this section wiII provide a Iist of sources you refer to in the text; it shouId be in aIphabeticaI order by author surname, it shouId be compIete and there shouId be a 1:1 mapping between the Iist and the citations in the text.
- TabIe(s) and Figure(s) 一 in this part you wiII present tabIes and figures (if reIevant) with aII your empiricaI resuIts; make them easy to read and understand; make sure they are aII properIy numbered and titIed; make sure they are seIf-expIanatory (the main text is not needed to interpret their content) and there is a short description (known as caption) under each tabIe and figure of what they present (see pubIished papers for exampIes); edit your tabIes appropriateIy and do not incIude any‘raw’outputs copied directIy from Stata’s output window; avoid too big tabIes, i.e., tabIes shouId not exceed the size of a page. It is up to you whether you pIace a few tabIes and figures in the appendix after the references.
Format: the strict word Iimit on the main text of the report (excIuding the titIe page, Iist of references, tabIes and figures) is 2,000 words. Remember to add the word count on the titIe page. If you exceed the word Iimit, onIy the first 2,000 words of your report wiII be read and marked with the rest assumed missing (pIease note that the markers wiII be abIe to check the Iength using Turnitin). Use a font not smaIIer than 11-point and Iine spacing not smaIIer than 1.5 Iines.
Data files and codes: Please keep all data files and codes. You are not required to submit them but may be asked to do so by the markers if they find it necessary to fully judge the quality of your work.
Marks will be awarded for:
- The background and motivation for your specific research questions;
- Presentation of the literature and reference to major published studies on the topic and research question;
- Data collection effort;
- The suitability and credibility of your statistical analysis;
- Presentation, discussion and interpretation of your evidence in relation to your chosen research question;
- Editorial preparation of your report.
The standards expected for marks in different ranges:
- 70+: An excellent piece of work. A very good attempt to develop an original piece of analysis with an outstanding ability to analyse, synthesise and apply knowledge and concepts. There is evidence of critical reflection, wider reading and research. Ideas are expressed clearly and written with authority and insight. A good attempt to apply a more complex approach and methodology as appropriate (e.g., alternative methods, robustness checks). A very clear report structure and excellent editorial preparation.
- 60-69: A good piece of work. A good attempt at analysis, synthesis and application of knowledge and concepts. There may be few gaps in the analysis leading to some errors. Some evidence of critical reflection, ideas are expressed with clarity, with some minor exceptions. The standard methodology is competently applied. Good report structure and clear exposition.
- 50-59: A fair piece of work. Grasp of major elements of the subject but with some gaps and areas of confusion. Only the basic ideas are covered. The attempt at analysis, synthesis and application of knowledge and concepts is superficial. Little critical reflection, some confusion and immaturity in the expression of ideas. The empirical analysis may contain some errors, and technical competence is at routine level only. Fair structure of the report and editorial preparation, with some weaknesses in the exposition.
- <50: A poor piece of work. Little familiarity with the subject, with major gaps and serious misconceptions. There is little or no attempt at analysis, synthesis or application of knowledge, and a low level of technical competence, with many errors. Inability to reflect critically on an argument or viewpoint. Ideas are confused and poorly expressed. Poor report structure and unclear graphical exposition.
Note that it is the quality of your analysis that is marked, and not your specific results. If you find insignificant results or results against your expectations, it will not affect your mark as long as the analysis is credibly executed.
Checklist before submission:
1. Does the Abstract state the research question?
2. Does the Abstract state the main results, including the most important estimates (numbers)?
3. Does the Introduction provide motivation for the research question? I.e. does it convince the reader that is it relevant to study this research question?
4. Does the Introduction state the main results and their economic/statistical significance?
5. Is the Literature Review well structured?
7. Does the Literature Review focus on articles that closely relate to the research question?
8. Would an interested reader be able to reproduce the main test results? i.e. are the sources of data, sample selection and applied methods discussed in sufficient detail?
9. Are all important results tabulated in Tables (including important test statistics)? I.e. if a reader only reads the Abstract and Tables/Figures with their captions, can the reader understand all the important results?
10. Does the report address the research questions with at least one econometric technique?
11. Are Tables self-explanatory and presented in the standard styles in journal articles? Can they be interpreted without the help of the main text? Do they have informative captions that explain the table contents?
12. Does the list of References contain all the articles cited in the main text? Do the citations follow standard styles?