This module is not currently running in 2024 to 2025.
This module will examine how Excel can be used for financial data analysis. Students will already be familiar with the financial concepts from earlier modules. A brief revision of each financial concept will be presented during the lectures while students will apply the financial techniques in Excel during the lab hours. The syllabus will typically cover:
Introduction to Excel:
• Basic functions, mathematical expressions
Data Analysis with Excel:
• Data analysis, charts, solver, goal seek, pivot tables and pivot charts
Financial Valuation:
• Applications of time value of money
• Applications of capital budgeting techniques in Excel (IRR, NPV, Scenario Analysis, Monte Carlo simulation)
• Company Valuation Models
Portfolio Analysis and Security Pricing:
• Portfolio models, calculations of efficient portfolios, variance-covariance matrix
• Beta coefficient estimations and security market line
• Bond Valuations
• Technical Analysis
• Binomial option pricing, Black-Scholes model.
This module employs lectures, labs, and private study.
Total Contact Hours: 31
Private Study Hours: 119.
Main assessment methods
Individual quantitative report – 1000 Words: 30%
Excel Based Project – 2500 Words: 70%
Reassessment methods
Reassessment will be on a like-for-like basis.
Core Reading
Benninga, S. (2014) Financial Modelling, 4th edition. Cambridge, Mass.: MIT Press.
Recommended Reading
Holden, C.W. (2015) Excel Modelling in Investments. 5th edition, London: Pearson.
Fairhurst, D.S. (2015) Using Excel for Business Analysis: A Guide to Financial Modelling Fundamentals, Edition Revised for Excel 2013, Chichester: Wiley.
The intended subject specific learning outcomes.
On successfully completing the module students will be able to:
- Demonstrate systematic understanding of key aspects of the use of Excel to solve financial problems.
- Demonstrate their ability in calculation and manipulation and capability to deploy accurately established approaches to analyse and solve problems in the following financial areas: Basic financial calculations, Monte Carlo simulation, Bond valuation, Derivative modelling and portfolio analysis.
- Apply key aspects of Excel for finance in well-defined contexts, showing judgement in the selection and application of tools and techniques.
- Demonstrate conceptual understanding of the advantages and disadvantages of financial approaches in project and asset valuation and in portfolio analysis.
The intended generic learning outcomes.
On successfully completing the module students will be able to:
- Manage their own learning and make use of appropriate resources and demonstrate the acquisition of the study skills needed for continuing professional development.
- Understand and critically evaluate logical arguments, identifying the assumptions made and the conclusions drawn.
- Communicate complex arguments and conclusions reasonably accurately and clearly.
- Apply advanced IT skills to analyse and solve complex problems.
University of Kent makes every effort to ensure that module information is accurate for the relevant academic session and to provide educational services as described. However, courses, services and other matters may be subject to change. Please read our full disclaimer.
