Final Project
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Final Project
1 Basic Requirements
You can select any suggested topic provided in the next page. The submission contains one PDF report and MATLAB/Python code.
You will be graded both on mathematical content, quality of code and presentation.
2 The Report
The PDF report should have the following structure:
Title and Author
Introduction Give a general overview of your task. State the problem and the methods. Summarize your results in one or two sentences.
Methods Describe the methods and the mathematical formulas used. All mathematical preparations should be done here.
Results Present your results here. For example, you may tabulate outputs for an array of different
parameters.
Discussions Provide some observations and analysis on the results.
Code Provide the command how to execute the code in the out-of-box run. If you run in an IDE (Integrated Development Environment), state which IDE you use. Specify how (commands or pa- rameters) you generate your results. Specify where your results are shown - in the IDE console, or in the screen of a separate window, or output files?
3 The Code
The folder code contains the code and input configuration files. The following behaviors are expected from your code:
It must be runnable out of box, which produces maybe the simplest case of the results in the report.
The user can edit the input configuration file or a code file to change the configuration parameters
to some reasonable values. The user should be able to run your script to produce results. The submissions from two groups with similar code will result zero marks for both.
4 Sample Project Problems
1. Pricing Asian and Barrier options on a basket of two stocls. using Monte Carlo, Finite difference methods, Tree methods, and close form approximation. Calculation of Greeks.
2. Pricing callable bonds using one-factor Hull-White model.
3. Portfolio optimization. Assessment of the impact of sampling errors on mean-variance portfolios.
4. Estimating the Risk-Neutral Density.
5. Pricing American-style options using Monte Carlo simulation.
6. Calibration of Heston stochastic volatility model to a set of market prices of options.
7. Quasi-Monte Carlo simulation.
8. Pricing Lookback options.
9. Modeling of copulas for risk management
10. Spherical and Elliptical distributions. Modeling for risk management.
2021-12-08