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ADDITIONAL IT TRAINING
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ADDITIONAL IT TRAINING
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Academic year 2016/2017
- Course ID
- SEM0046
- Teacher
- Andrea Romeo (Esercitatore)
- Degree course
- Finance
Insurance and Statistics - Year
- 1° anno
- Type
- Altre attività
- Credits/Recognition
- 3
- Course disciplinary sector (SSD)
- SECS-S/01 - statistica
SECS-S/06 - metodi matematici dell'economia e delle scienze att. e finanz. - Delivery
- Tradizionale
- Language
- Inglese
- Attendance
- Obbligatoria
- Type of examination
- Orale
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Sommario del corso
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Course objectives
The course aims at presenting the main numerical techniques used in financial applications. It covers both programming introduction and financial applications.
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Results of learning outcomes
Ability to handle numerical techniques suitable for financial problems in Matlab.
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Course delivery
The course is articulated in 24 hours of formal in‐class lecture time, and in hours of at‐home work.
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Learning assessment methods
The final exam consists in a group project.
Projects must be chosen among a list that I will provide you by the end of the course.
Groups should be composed of max 3-4 people.
The discussion of the project will consist in a short presentation of
the project.
The group is also expected to deliver a short report in
pdf format, containing:
- a description of the financial and mathematical problem;
- a description of the solution of the problem;
- the explanation of the numerical algorithms adopted;
- MATLAB code scripts and user-defined functions;
- discussion of the results.
As a general rule, try to write the code in the most efficient possible way, trying
to avoid for loops when possible by vectorizing the calculations.
I will supervise the projects and assist the groups in the making of the code.
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Support activities
Office hours.
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Program
- Introduction to Matlab and basics: arrays and matrices, plotting.
- Programming in Matlab: scripts, functions, control flow and operators, data
handling.
- Statistical and mathematical tools in Matlab: statistical functions, regressions, (un) constrained optimization, interpolation, numerical integration,
random variables generation.
- Sampling paths of continuous diffusions and jump processes;
- Pricing Derivatives via Monte Carlo Simulation;
- Variance Reduction Techniques;
- Lattice methods and binomial pricing.
Suggested readings and bibliography
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P. Glasserman, 2003, Monte Carlo Methods in Financial Engineering, Spinger.
J. Kienitz and D. Wetterau, 2012, Financial Modelling: Theory, Implementation and Practice with MATLAB Source, Wiley.
P. Brandimarte, 2006, Numerical methods in finance and economics: a MATLAB-based introduction, Wiley.
W. Schoutens, 2003, Lévy Processes in Finance, Wiley.Cox, John C., Stephen A. Ross, and Mark Rubinstein. "Option pricing: A simplified approach." Journal of financial Economics 7.3 (1979): 229-263.Black, Fischer, and Myron Scholes. "The pricing of options and corporate liabilities." Journal of political economy 81.3 (1973): 637-654.Cont, Rama. "Empirical properties of asset returns: stylized facts and statistical issues." Quantitative Finance 1 (2001): 223-236.Wetterstrand, William H. "Parametric models for life insurance mortality data: Gompertz’s law over time." Transactions of the Society of Actuaries 33 (1981): 159-175.- Oggetto:
Note
Starting from 6th March, 2016 the class will be held on Monday and Tuesday, always from 17.30 to 19.30.
On Tuesday, 21st of March 2017 there will be no class.
Last class will be held on Tuesday 4th April 2017 from 17.30 to 19.30.
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