MSc Financial Economics

Year of entry: 2024

Course unit details:
Financial Economics I

Course unit fact file
Unit code ECON60401
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 1
Available as a free choice unit? Yes

Overview

The main focus of the course Financial Economics I is on topics related to Mathematical Finance. The course will introduce students to fundamental ideas and tools developed in this field. A central goal is to demonstrate the use of these tools in contexts where they are indispensable and widely exploited. A remarkable feature of Mathematical Finance is that its theoretical highlights (such as the Black-Scholes formula) turned out to be extremely important in practice. They have created new markets essentially based on concepts developed by academics. The course will expose students to quantitative techniques and theory that will be useful to any actor in the financial industry - a portfolio manager, a risk management consultant, or a financial analyst.

Aims

The main focus of the course Financial Economics I is on topics related to Mathematical Finance. The course will introduce students to fundamental ideas and tools developed in this field. A central goal is to demonstrate the use of these tools in contexts where they are indispensable and widely exploited. A remarkable feature of Mathematical Finance is that its theoretical highlights (such as the Black-Scholes formula) turned out to be extremely important in practice. They have created new markets essentially based on concepts developed by academics. The course will expose students to quantitative techniques and theory that will be useful to any actor in the financial industry - a portfolio manager, a risk management consultant, or a financial analyst.

 

Learning outcomes

At the end of this course students should be able to:

(i) understand and apply the basic theory, tools, and terminology of Mathematical Finance;

(ii) formalise real world situations by using models and techniques suggested by the theory;

(iii) solve numerically typical problems related to asset pricing and risk management.

Syllabus

Topics will include the following:

1. The Markowitz mean-variance portfolio theory.

2. Capital Asset Pricing Model (CAPM).

3. Factor models: Ross-Huberman arbitrage pricing theory (APT).

4. One-period and multiperiod discrete-time models of securities markets.

5. Hedging strategies and pricing by no-arbitrage.

6. Fundamental Theorem of Asset Pricing.

7. Pricing European and American options in binomial models.

8. The Black-Scholes formula (via binomial approximation).

9. Growth-optimal investments and the Kelly rule.

Teaching and learning methods

Lectures, exercice classes and tutorials.

Assessment methods

Method Weight
Other 10%
Written exam 90%

Final exam 90%.

2 take home tests weighted at 5% each.

Recommended reading

1. I. Evstigneev, T. Hens and K.R. Schenk-Hoppé, Mathematical Financial Economics, Springer, 2015.

2. H. H. Panjer (Editor), Financial Economics, The Actuarial Foundation of the USA, 1998.

3. D. Luenberger, Investment Science, Oxford University Press, 1998.

4. S. Ross, An introduction to Mathematical Finance, Cambridge University Press, 1999.

5. S. R. Pliska, Introduction to Mathematical Finance: Discrete Time Models, Blackwell Publ., 1997.

6. H. Follmer and A. Schied, Stochastic Finance: An Introduction in Discrete Time, Walter de Gruyter, 2002.

 

This reading is supplementary to the lectures and is optional. The course is self-contained, and no external texts or resources are required to fulfill its objectives. Electronic pdf copies of all course materials (lecture notes/slides, exercises and answers) will be posted to the web during the semester.

 

Those who wish to study the subject more deeply are referred to the textbook [1]. This is the only text in the literature that combines mathematical rigour with the use of only elementary mathematical techniques suitable for Economics students. Other books in the above list require knowledge of advanced mathematics.

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Study hours

Scheduled activity hours
Lectures 14
Practical classes & workshops 2
Tutorials 4
Independent study hours
Independent study 130

Teaching staff

Staff member Role
Igor Evstigneev Unit coordinator

Additional notes

 

 

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