# FE 635 Financial Enterprise Risk Engineering: Modern Financial Engineering

## Contents |

## Instructor Information

Professor: Dr. Rupak Chatterjee

Office: Babbio 5^{th} Floor

Email: Rupak.Chatterjee@stevens.edu

Class Schedule: Wednesdays 6:15 p.m. to 8:45 p.m., McLean 105

Hanlon Lab: Aug 30th, Sept 6th, Sept 13th Friday 5:00 p.m. – 7:00 p.m (Bloomberg Training)(Plus additional sessions for credit derivatives TBA)

Office Hours: Wednesday 3:00 p.m. to 5:00 p.m.

## Overview

This course is largely a continuation of FE 535. After a review of stochastic processes, a Statistical Arbitrage Strategy is studied in detail. The Optimal Hedging Monte Carlo methodology for derivative pricing is introduced. Potential research topics on OHMC at the Master’s/PhD level will be discussed. Credit Derivatives will be introduced along with the pricing mechanisms using Hazard rates and Copulus. The study of Fat-tailed distributions such as Pareto and those coming from Extreme Value theory will follow. Finally, modern regulatory theory using Basel II, Basel III, and CVA as a starting point will be analyzed. Similar to FE535, the course will largely be based on lecture notes.

Prerequisites: FE 535 or Solid Knowledge of Statistics/Probability Theory and some familiarity of financial instruments

## Course topics

- Statistical Arbitrage
- Optimal Hedging Monte Carlo
- Credit Derivatives
- Extreme Value Theory
- Basel II, Basel III, and CVA
- Asset Replication

## Textbook (uploaded to Moodle)

- Modern Methods of Financial Engineering and Risk Management, Rupak Chatterjee, Apress-Springer, to be published, 2014.

## Some Useful References

- Risk Management and Financial Institutions, John Hull, John Wiley & Sons, 2012 (optional)
- An Introduction to the Mathematics of Financial Derivatives, 2nd Edition, Salih Neftci, Academic Press, 2000 (optional)
- Monte Carlo Methods in Financial Engineering, Paul Glasserman, Springer-Verlag, 2004 (optional)

## IT Requirements

All the homeworks require the use of Excel with the following properties:

- 1) Functions:
- a.Offset()
- b.Rand()
- c.Norminv()
- d.Skew(), Kurt(), Average(), Stdev()
- e.Gammaln()

- 2) Data Analysis Function : Histogram

- 3) Some knowledge of VBA will be useful

**Attention Apple Users:** Even though you may have Excel, the above functionality does not come with all Apple versions of Excel so you better check to see what your Excel provides.

## Syllabus

Chapters from Lecture notes: Modern Methods of Financial Engineering and Risk Management:

4 Stochastic Processes 93

5 Optimal Hedging Monte Carlo (OHMC) Methods 129

6 Introduction to Credit Derivatives 153

7 Modeling Extreme Moves with Power Laws 191

8 Basel II, Basel III, and CVA 203

Week | Topic(s) | Homework |
---|---|---|

1 | Stochastic Processes | |

2 | Statistical Modeling of Trading Strategies | HWK 4.3: GARCH(1,1) Calibration |

3 | Statistical Modeling of Trading Strategies | HWK 4.4: GARCH(1,1) Simulation |

4 | Statistical Modeling of Trading Strategies | HWK 4.5: Pairs Trading |

5 | Optimal Hedging Monte Carlo (OHMC) Methods | |

6 | Optimal Hedging Monte Carlo (OHMC) Methods | |

7 | Optimal Hedging Monte Carlo Methods | |

8 | Midterm | |

9 | Introduction to Credit Derivatives | HWK 6.4.1 |

10 | Introduction to Credit Derivatives | |

11 | Introduction to Credit Derivatives | |

12 | Basel II, Basel III, and CVA | |

13 | Basel II, Basel III, and CVA | |

14 | Modeling Extreme Moves with Power Laws | HWK 7.1.2 |

15 | Final Exam |