Research methods for finance

This module provides you with the necessary background to understand and plan empirical research in finance. It discusses some basic methodological approaches to research and develops relevant data analytics skills, including linear regression analysis, in Microsoft Excel. Finally, this module introduces you to the free and powerful statistical and econometric software R, which has become very popular amongst finance professionals. Whilst this is more technical than our other finance modules, it is exciting because it brings you closer to academic research in finance.

Register

Start	End	Fee	Register
07 Nov 2026	Apr 2027	Not yet available	Registration closes 15/10/26 (places subject to availability) Click to register
This module is expected to start for the last time in November 2030.

What you will study

This module is made up of the following six units:

Unit 1 provides a general introduction to social research. It deals with issues of research methodology, the differences between qualitative and quantitative research and the distinction between primary and secondary data sources. It also discusses possible ethical issues and challenges that a researcher may encounter in social research in general and financial research in particular.

Units 2, 3 and 4 develop relevant data analytics skills in Microsoft Excel by focusing on descriptive statistics and basic probability theory. This part of the module not only discusses the most common probability distributions and their applications in finance research but also shows you how to carry out hypothesis tests for single variables and draw conclusions for a variety of statistical problems.

Unit 5 introduces you to linear regression analysis in Microsoft Excel. Regression analysis is a powerful and arguably the most widely used statistical method in empirical finance research. One particular type of regression analysis, linear regression, aims to explain one variable as a linear combination of one or several other variables.

Finally, Unit 6 introduces you to the powerful statistical and econometric software R. More specifically, we show how R can be used to assemble and manage large datasets, produce descriptive statistics and graphs, perform regression analysis, and interpret regression results. While Unit 6 has a distinct practical and applied feel, it uses the combined knowledge of the preceding Units 1 to 5.

Given the technical nature of this module, you may find parts of it challenging. The study activities will help you to understand the concepts and apply them to real-life problems, so it is important to allow time to complete them.

You will learn

By completing this module, you will be able to:

examine the range of methods available for the collection of evidence (data) in finance
use relevant descriptive statistics to describe data
identify and explore relationships within the data
demonstrate proficiency in conducting data visualisation, statistical tests and basic regression analysis in Microsoft Excel
practice conducting data visualisation, statistical tests and regression analysis in the R software
conduct literature reviews of academic papers in finance confidently and effectively
identify relevant theories in finance literature and use prior literature to propose and test research hypotheses
design a quantitative research methodology to explore a finance research problem.

Vocational relevance

This module is essential if you are working or planning to work in the finance sector, especially in financial institutions. It will also be beneficial if you work, or intend to work, outside of the finance domain, such as conducting academic research in finance. This module will also be of interest if you wish to expand your knowledge and skills in order to increase future opportunities by acquiring key transferable skills.

Entry

All entrants must hold a BA/BSc degree awarded by a recognised university or equivalent.

Various higher education and professional qualifications are considered equivalent to a degree. If you hold a qualification that you believe is an equivalent level to a UK degree you should contact us. The Open University Business School Masters Programme Committee is responsible for judging whether applicants' qualifications meet the requirements for admission.

You will also need an appropriate facility in English language, sufficient to be able to work effectively at postgraduate level; generally, this means capability equivalent to an International English Language Test System (IELTS) score of 6.5. To assess your English language skills in relation to your proposed studies, you can visit the IELTS website. If you think either of these possibilities may apply to you, please speak to an adviser.

It is strongly recommended that you are comfortable with the use of numerical methods and use of spreadsheets. If you're unsure about these skills, we suggest you familiarise yourself with illustrative numerical skills and methods prior to study. To help you decide whether you are ready, you may want to try this diagnostic quiz.

If you have any doubt about the suitability of the module, please speak to an adviser.

Qualifications

B817 is a compulsory module in our:

Excluded combinations

Sometimes you will not be able to count a module towards a qualification if you have already taken another module with similar content. To check any excluded combinations relating to this module, visit our excluded combination finder or check with an adviser before registering.

If you have a disability

This module is delivered online, and time spent using a computer and the internet will therefore be extensive. Some interactive online material may not be available or fully accessible.

If you’re using printed materials as part of reasonable adjustments to support your studies, note that printed versions of online materials are unavailable for this module.

To find out more about what kind of support and adjustments might be available, contact us or visit our disability support pages.

Study materials

What's included

You'll be provided with a printed textbook and have access to a module website, which includes:

a week-by-week study planner
course-specific module materials
audio and video content
assignment details and submission section
online tutorial access
published articles
access to The Open University library.

Computing requirements

Primary device – A desktop or laptop computer. It’s possible to access some materials on a mobile phone, tablet or Chromebook; however, they will not be suitable as your primary device.
Peripheral device – Headphones/earphones with a built-in microphone for online tutorials.
Our OU Study app operates on supported versions of Android and iOS.
Operating systems – Windows 11 or latest supported macOS. Microsoft will no longer support Windows 10 as of 14 October 2025.
Internet access – Broadband or mobile connection.
Browser – Google Chrome and Microsoft Edge are recommended. Mozilla Firefox and Safari may be suitable.

Teaching and assessment

Support from your tutor

Your tutor will help you with the study material, mark and comment on your assignments and provide advice and guidance. You'll be able to contact your tutor by email, telephone or via your tutor group forum on the module website.

Assessment

The assessment details can be found in the facts box.

Future availability

Research methods in finance starts once a year – in November. This page describes the module that will start in November 2025. We expect it to start for the last time in November 2030.

How to register

To register a place on this module return to the top of the page and use the Click to register button.

Regulations

As a student of The Open University, you should be aware of the content of the academic regulations which are available on our Student Policies and Regulations website.

PG Postgraduate

Course facts

About this course:
Course code	B817
Credits	30
OU Level	Postgraduate
SCQF level	11
FHEQ level	7
Course work includes:
2 Tutor-marked assignments (TMAs)
End-of-module assessment
No residential school