Advanced Topics in Financial Economics - EC824

Location Term Level Credits (ECTS) Current Convenor 2019-20
(version 5)
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7 15 (7.5)







The aim of this module is to offer an in-depth theoretical treatment of advanced topics in financial economics, such as derivative pricing and real options. Simultaneously the module discusses the theoretical basis for computational approaches to asset pricing. The module consists of three main parts. In the first part we review selected elements of probability theory and stochastic calculus. We then discuss two prominent solution ideas for the derivative pricing. One is based on the Girsanov theorem and properties of martingale processes. The other is related to the Feynman-Kac's stochastic representation. In both cases, the well-known Black-Scholes-Merton formula is solved as a special case. In the second part we study a couple of important stochastic processes such as Vasicek process, which is widely used to characterize the dynamics of short-term interest rate. In the third part we deal with real option problems. The latter are workhorse models for irreversible decisions under uncertainty. Combined, the three parts form a broad theoretical perspective of advanced analytical methods in the contemporary financial economics practice.


This module appears in:

Contact hours

30 hours of academic teaching in the form of lectures and seminars

Method of assessment

10% In-Course Test 1 (45 minutes)
10% In-Course Test 2 (45 minutes)
80% Examination (2 hours)

Indicative reading

• Björk, Thomas. Arbitrage theory in continuous time. 3rd Edition. Oxford University Press, 2009
• Dixit, Avinash, and Robert Pindyck. Investment under Uncertainty, Princeton University Press, 1994
• Baxter, Martin, and Andrew Rennie. Financial Calculus: An introduction to derivative pricing. 17th Edition. Cambridge University Press, 1996
• Cochrane, John. Asset Pricing. (Revised Edition). Princeton University Press, 2009
• Wilmott, Paul, Howison, Sam and Jeff Dewynne. The mathematics of financial derivatives: a student introduction. Cambridge University Press, 1995

See the library reading list for this module (Canterbury)

Learning outcomes

On successfully completing the module students will be able to:

• critically understand and flexibly apply stochastic calculus and basic probability theory
• comprehensively understand martingale measure theory and its key elements
• comprehensively understand dynamic programming and the mechanics of the optimal choice of investor
• understand real options and their applications
• demonstrate strong analytical skills to evaluate unpredictable risks in financial markets
• profoundly understand the option value of irreversible decision under uncertainty
• solve complex quantitative problems independently

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