Postgraduate Course: Stochastic Analysis in Finance (MATH11154)
Course Outline
| School | School of Mathematics | 
College | College of Science and Engineering | 
 
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) | 
Availability | Not available to visiting students | 
 
| SCQF Credits | 20 | 
ECTS Credits | 10 | 
 
 
| Summary | This course aims to provide a good and rigorous understanding of the mathematics used in derivative pricing and to enable students to understand where the assumptions in the models break down. | 
 
| Course description | 
    
    Continuous time processes: basic ideas, filtration, conditional expectation, stopping times.  
 
Continuous-time martingales, sub- and super-martingales, martingale inequalities, optional sampling.  
 
Wiener process and Wiener martingale, stochastic integral, Itô calculus and some applications.  
 
Multi-dimensional Wiener process, multi-dimensional Itô's formula.  
 
Stochastic differential equations, Ornstein-Uhlenbeck processes, Black-Scholes SDE, Bessel processes and CIR equations.  
 
Change of measure, Girsanov's theorem, equivalent martingale measures and arbitrage.  
 
Representation of martingales.  
 
The Black-Scholes model, self-financing strategies, pricing and hedging options, European and American options.  
 
Option pricing and partial differential equations; Kolmogorov equations.  
 
Further topics: dividends, reflection principle, exotic options, options involving more than one risky asset.
    
    
 | 
 
 
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites | 
 | 
Co-requisites |  | 
 
| Prohibited Combinations |  | 
Other requirements |  None | 
 
 
Course Delivery Information
 |  
| Academic year 2023/24, Not available to visiting students (SS1) 
  
 | 
Quota:  None | 
 
| Course Start | 
Semester 1 | 
 
Timetable  | 
	
Timetable | 
| Learning and Teaching activities (Further Info) | 
 
 Total Hours:
200
(
 Lecture Hours 36,
 Seminar/Tutorial Hours 8,
 Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
152 )
 | 
 
| Assessment (Further Info) | 
 
  Written Exam
90 %,
Coursework
10 %,
Practical Exam
0 %
 | 
 
 
| Additional Information (Assessment) | 
Two assignments will be marked out of 50 each, and the best two will be counted towards the final result.   
 
Examination 90% 
Coursework 10% | 
 
| Feedback | 
Not entered | 
 
| Exam Information | 
 
    | Exam Diet | 
    Paper Name | 
    Hours & Minutes | 
    
	 | 
  
| Main Exam Diet S2 (April/May) | Stochastic Analysis in Finance (MATH11154) | 3:00 |  |  
 
Learning Outcomes 
    On completion of this course, the student will be able to:
    
        - model the evolution of random phenomena using continuous-time stochastic processes
 - understand the Weiner process, stochastic calculus, Itô integral, and Itô's formula, and apply Ito calculus
 - apply stochastic calculus to option pricing problems
 - understand the martingale representation theorem, its role in financial applications, and the role of martingales in fincancial mathematics generally and the theory of derivative pricing in particular
 - understand stochastic differential equations and be able to use them in modelling generally and in finance in particular
 
     
 | 
 
 
Reading List 
(1) M. Baxter, A. Rennie: Financial Calculus: an introduction to derivative pricing, ,Cambridge University Press, 1997.  
 
( Lib. Number: HG6024.A3 Bax.)  
(2) N. H. Bingham: Risk-neutral valuation : pricing and hedging of financial derivatives,Springer, 1998.  ( Lib. Number: HG4515.2 Bin.)  
(3) D. Lamberton and B. Lapeyre: Introduction to stochastic calculus applied to finance,Chapman & Hall, 1996.   
(4) T. Bj ¿ork: Interest rate theory. Financial mathematics (Bressanone, 1996), 53¿122,Lecture Notes in Math., 1656, Springer, Berlin, 1997.  
(5) J. C. Hull: Options, futures, and other derivatives, 4th ed. Prentice-Hall International,2000.  
( Lib. Number: HG6024.A3 Hul.)  
(6) T. Bj ¿ork: A geometric view of interest rate theory. Option pricing, interest ratesand risk management, 241¿277, Handb. Math. Finance, Cambridge Univ. Press,Cambridge, 2001.  
(7) N. V. Krylov: Introduction to the theory of random processes. Graduate studies inmathematics ; v. 43, American Mathematical Society, Providence, RI, 2002.  
(8) B. Oksendal: Stochastic differential equations : an introduction with applications, 5thed. Springer, 1998.  
( Lib. Number: QA274.23 Oks.)  
(9) T. Mikosch: Elementary stochastic calculus with finance in view. Advanced series on statistical science & applied probability ; vol. 6, World Scientific, Singapore, London,1998.  
(10) R. J. Williams: Introduction to the Mathematics of Finance, Graduate Studies in Mathematics V. 72, American Mathematical Society, Providence, RI, 2006.  
(11) S. E. Shreve: Stochastic Calculus for Finance I: The Binomial Asset Pricing Model:Binomial Asset Pricing Model v. 1, Springer 2004.  
(12) S. E. Shreve: Stochastic C |   
 
Additional Information
| Graduate Attributes and Skills | 
Not entered | 
 
| Special Arrangements | 
MSc Financial Mathematics, MSc Financial Modelling and Optimization and MSc Computational Mathematical Finance students only. | 
 
| Keywords | SAF | 
 
 
Contacts 
| Course organiser | Prof Istvan Gyongy 
Tel: (0131 6)50 5945 
Email:  | 
Course secretary | Miss Gemma Aitchison 
Tel: (0131 6)50 9268 
Email:  | 
   
 
 |    
 
  
  
  
  
 |