Studying at York
Individual Research Project - Finance - MAN00162M
- Department: The York Management School
- Credit value: 60 credits
- Credit level: M
- Academic year of delivery: 2024-25
- See module specification for other years: 2023-24
- Notes: This is an independent study module
Related modules
Pre-requisite modules
Co-requisite modules
- None
Prohibited combinations
- None
Module will run
| Occurrence | Teaching period |
|---|---|
| A | Summer Semester 2024-25 |
Module aims
This module acts as the final element of Type 1 finance postgraduate programmes and for the Accounting and Finance MSc. The module enables learners to undertake an individual research project on a topic related to their MSc. programme. This is to be undertaken for all type 1 programmes including the MSc. Accounting and Finance (MSc. Finance, MSc, Finance and Investments, MSc. Corporate Finance, MSc. Accounting and Finance, MSc Finance and Management and MSc Investments, Finance and Economics.. Learners from the type 2 finance postgraduate programmes (including MSc. Financial Economics, MSc Financial Engineering and MSc. Mathematical Finance will not take this module – rather they will undertake the dissertation module.
Within this project the learners are expected to produce a substantial piece of discussion, analysis and reflection reflecting the key skills underlying a dissertation module. This module is split into two parts.
Initially, we provide a refresher and revision course as to the research methods embedded in the finance programme taken by the learner. This part of the module will focus on developing econometric analytical skills, revisiting methods for accessing, organising and developing data sets, how to develop a critical literature review and considering how we use research, write conclusions and derive the implications of our research. This element for the module will be assessed through the development of an individual project proposal and data collection as to how the learner will undertake their individual research project.
The second part of the module involves the completion of the individual research project. The learner will attend and engage in a series of lectures as to the purpose and use of appropriate research designs and apposite empirical testing frameworks to assess issues of concern or debate with contemporary finance. This instruction will introduce project areas for students to follow and to focus on when developing their individual research project. The project areas considered will reflect the programme goals and subject matter in the different programmes.
Lastly, we will offer three online surgeries and writing workshops to support learners over this module.
Module learning outcomes
After successful completion of the module students will be able to:
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Independently author an extended piece of focused writing, longer than a module assessment, using a contemporary research design and methods drawn from modern finance and financial economics.
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Synthesise complex information to develop original findings and critically assess assumptions necessary to draw certain conclusions.
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Demonstrate a mastery of information literacy skills by critically engaging with a range of sources
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Understand how to draw upon secondary data to make original conclusions
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Comprehend the requirements and expectations needed to produce robust research work in a cogent area of finance.
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Interpret and analyse financial data by selecting appropriate theoretical and statistical concepts and tools
Academic and graduate skills
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Advanced subject specific knowledge and understanding
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Cognitive (thinking) skills: through self-study and assessment
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Problem solving and analytical skills required to undertake finance analysis and/or estimations.
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Ability to conduct research into financial issues using data collection from Refinitiv, WRDS and other financial databases and platforms made available by the university.
- Numeracy through the application and use of financial techniques and econometric methods.
Module content
This teaching will be undertaken in a two-week block after the completion of semester 2 examinations.
Study skills for econometric and financial analysis – First Week
This session is common to all learners undertaking the module.
Day 1: Collecting financial data. Collecting data from the Refinitiv, WRDS and other financial databases and platforms made available by the University.
Days 2 and 3: Revisiting and developing econometric, analytical and interpretative skills.
Day 4: Reviewing and interpreting the financial academic literature, developing a critical literature review and skills for effective academic writing. Comprehending how we use financial research, how we interpret and report our research findings, the expectations of research users and how to develop useful conclusions.
The individual research project – the research design week. (Second week)
In this element of the module, the learner will consider different research designs and empirical frameworks which can be employed to address different research questions and settings. Contemporary issues or debate in corporate finance, financial markets or macro-finance pertinent for the programme will be considered. This will be introduced over a three-day period in which different research designs and empirical frameworks appropriate for the assessment of different research questions will be considered.
The three areas of study offer opportunities across a wide range of topics and research methods. In each area they include:
Corporate Finance
Manifest Content Analysis and Testing – developing new data sets for the quantitative analysis of qualitative data sets. This will be developed using the example of quantifying the effects of corporate misconduct.
Financial Markets
Analyse the behaviour of returns in a particular market or set of markets using a suitable dataset. This may involve the assessment of investment strategies and market anomalies using appropriate econometric methods. It may employ event studies which assess the impact of external changes in regime on asset performance or natural experiments which measure the outcomes from different policies and interventions.
Economics and Finance
Analyse the interaction between the behaviour of the macro economy and financial markets using a suitable dataset. It may employ event studies which assess the impact of external changes in regime on asset performance or natural experiments which measure the outcomes from different policies and interventions.
Financial Statement Analysis Project (Accounting)
The project aims to assess the drivers of profitability for a sample of companies in an industry chosen by each individual student. Following a methodology frequently used by financial analysts, students will adopt the DuPont analysis framework.
This instruction will be undertaken over three days with a day allocated to each topic. All learners are encouraged to attend all days. The structure of the days will include first an outline of the research design, apposite theory and academic literature and move on the different research questions which have been addressed using this design and associated techniques. This session will involve the use of multiple examples drawn from contemporary academic literature.
Assessments
After these sessions it is required that the learner produces two assessments.
One a research proposal outlining the subject of assessment, the pertinent academic literature they wish to consider, the data they intend to collect and use and the research design and empirical framework they wish to adopt.
It is proposed to organise this assessment around a question-based or pitch-based format whereby learners choose a topic to consider (from the three choices outlined Corporate Finance, Financial Markets and Economics and Finance), a research design to follow from choices detailed in the research design week, and data to collect from datasets discussed. These choices will be accompanied by a brief discussion of the following issues:
(A) Working Title and Basic Research Question
(B) Key academic paper(s) in this field of study
(C) Motivation/Puzzle, Idea?
(D) Data?
(E) Tools and Techniques employed?
(F) What’s New? So What? Contribution?
(G) Other Considerations
It is essential in this proposal the learner can discuss why the decisions made are appropriate and incorporate a critical interpretation of the decision made.
The second assessment is more substantial and involves the development of an individual research project. The individual research project is expected to include the following elements:
An introduction (10%) This section will outline the scope and elements contained within the individual research project, explain the question being consider and why this is important to consider from both academic and public (policy, corporate) perspectives
A literature review (30%) This section will consider the apposite academic literature from peer reviewed journal articles and other sources when appropriate. It is expected the critical interpretation of the literature is adopted.
Data collection, econometric analysis and interpretation (40%) The data collection should use the datasets provided by the University such as the data sets offered through the Refinitiv platform. The analysis is expected to use some of the econometric and statistical techniques discussed in the study week one. All results must be written up professionally and include a detailed interpretation as to their veracity and meaning.
Conclusions (20%) This element will draw out reflections upon the analysis and the evaluation and meaning of the results. It is important to consider both the stronger elements and the drawbacks of the work undertaken. Reflection as to the implications of the IRP are important to include.
Formative feedback on the project will be provided in the sixth week with the submission of a chapter outline from the individual research project, for review and feedback only. The final individual research project is expected to be submitted by week 11.
Research Methods Surgery and Writing Workshops
To support learners through their journey through the module an online Research Methods Surgery and Writing Workshop will be provided so students can access academic support and guidance at periodic intervals. We will be running three of these events. It is expected that learners would attend at least one of these three, two-hour Surgeries/workshops to share their experiences working on the project and reflect on the assignments’ expectations.
Indicative assessment
| Task | % of module mark |
|---|---|
| Essay/coursework | 90 |
| Essay/coursework | 10 |
Special assessment rules
None
Indicative reassessment
| Task | % of module mark |
|---|---|
| Essay/coursework | 90 |
Module feedback
For the IRP proposal, written feedback is provided by week 6. Written feedback on the IRP will be released to students after the final exam board. In cases of a marginal fail where minor amendments are permitted, students will be given written guidance on the required amendments and deadlines for submission in accordance with university regulations on reassessment and resubmission.
Indicative reading
Brooks, C., (2019) Introductory Econometrics for Finance, 4th ed, Cambridge.
Indicative readings will be provided for each of the following topics for a contemporary issue of debate identified for further discussion and evaluation.
Corporate Finance
Manifest Content Analysis and Testing – developing new data sets for the quantitative analysis of qualitative data sets. This will be developed using the example of quantifying the effects of corporate misconduct.
Financial Markets
Analyse the behaviour of returns in a particular market or set of markets using a suitable dataset. This may involve the assessment of investment strategies and market anomalies using appropriate econometric methods. It may employ event studies which assess the impact of external changes in regime on asset performance or natural experiments which measure the outcomes from different policies and interventions.
Economics and Finance
Analyse the interaction between the behaviour of the macro economy and financial markets using a suitable dataset. It may employ event studies which assess the impact of external changes in regime on asset performance or natural experiments which measure the outcomes from different policies and interventions.