Core Module Information
Module title: Statistics, Probability and Risk

SCQF level: 11:
SCQF credit value: 20.00
ECTS credit value: 10

Module code: FIN11101
Module leader: George Kladakis
School The Business School
Subject area group: Accounting and Finance


Description of module content:

Nature of economic and financial data
Graphical and numerical summaries of data. Applications to market efficiency
Discrete probability distributions. Applications to option pricing and default risk
Continuous probability distributions. Applications to stock prices and returns
Bayesian probability and behavioural finance.
Sampling distributions and statistical inference
Simple and multiple regression. Potential difficulties, and applications to CAPM
Forecasting with time series
Use of software packages
Report writing

Learning Outcomes for module:

LO1: Identify, search and retrieve relevant academic and finance based information.
LO2: Evaluate secondary information collecting techniques, analytical tools, interpretation and presentation.
LO3: Investigate and compare a range of software packages for the analysis of economic/financial data.
LO4: Explore techniques for managing risk.
LO5: Develop report writing skills in a technical context.

Full Details of Teaching and Assessment
2022/3, Trimester 1, BLENDED, Edinburgh Napier University
Occurrence: 001
Primary mode of delivery: BLENDED
Location of delivery: CRAIGLOCKHAR
Partner: Edinburgh Napier University
Member of staff responsible for delivering module: George Kladakis
Module Organiser:

Learning, Teaching and Assessment (LTA) Approach:
The learning & teaching methods of this module are in line with the learning outcomes and include a combination of statistics theory and practice. More specifically, in the lectures, you will be taught statistics theory; in the tutorials, you will learn to solve statistics exercises based on the relevant theory; and in the practicals, you will be applying the theory with real data using computer software. The use of computer packages and IT will allow you to access, retrieve, interpret, communicate and present technical financial information effectively. Moreover, you will develop key employability skills through the practical experiences associated with the formative and summative assessments. Finally, you will be exposed to the importance of academic rigour in terms of sourcing relevant information, structuring this information to support your own work, and communicating this effectively through a written report.

Supporting equality and diversity: The module content is broad and applicable to an international context. Mature, part-time and international students will be able to contribute to class exercise and discussion sessions. Disabled students will have appropriate adjustments made to enable them to participate fully in the module. Exercise data is drawn from major world markets. The expected number of international students present in the module will enrich the understanding of all students as they collaborate and support each other in terms of their own learning.

Formative Assessment:
The formative assessment of this module includes solving tutorial exercises and practical application of statistics methods using computer software solved on a weekly basis in class. Through close contact with the module leader and the tutor, you will learn to solve statistics exercises as well as how to apply statistical techniques to solve modern data-based problems. You will be sourcing economic and financial data, analysing it with rigorous methods and reaching valid conclusions.

Summative Assessment:
The summative assessment of this module consists of two equally weighted coursework reports. In the first report, you are required to present a robust critical analysis of the methods, data analysis and the ways in which the authors interpret the results in a journal article of your choice. You are required to present the article’s conclusions clearly and explain how they are achieved.

In the second report, you are required to conduct your own statistical analysis using financial data. Indicatively, you may conduct a rigorous risk assessment of a company’s stock or of a portfolio of assets.

Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)
Online Lecture 24
Face To Face Tutorial 12
Face To Face Practical classes and workshops 12
Independent Learning Guided independent study 152
Total Study Hours200
Expected Total Study Hours for Module200

Type of Assessment Weighting % LOs covered Week due Length in Hours/Words
Report 50 1, 2, 4, 5 9 HOURS= 00.00, WORDS= 2500
Report 50 1, 2, 3, 5 13 HOURS= 00.00, WORDS= 2500
Component 1 subtotal: 50
Component 2 subtotal: 50
Module subtotal: 100

Indicative References and Reading List - URL:
FIN11101 Statistics, Probability and Risk