Difference between revisions of "FE535 Introduction to Financial Risk Management"

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:1) Functions:
:1) Functions:
:d.Skew(), Kurt(), Average(), Stdev()
::d.Skew(), Kurt(), Average(), Stdev()
:2) Data Analysis Function : Histogram<br />
:2) Data Analysis Function : Histogram<br />

Revision as of 14:15, 5 September 2012

Professor: Dr. Rupak Chatterjee, Citi Global Markets
Office: Babbio 537
Email: Rupak.Chatterjee@stevens.edu
Class Schedule: Tuesdays 6:15 p.m. to 8:45 p.m., Babbio 122
Office Hours: Monday 5:00-7:00

Course Objectives and Description

Risk Control and derivative pricing are major concerns for financial institutions. Yet, as recent events have shown us there is a real need for adequate statistical tools to measure and anticipate the amplitude of the potential moves of the financial market. Many of the standard models seen on Wall Street however are based on simplified assumptions and can lead to systematic (and sometimes dramatic) underestimation of real risks. Starting from a detailed analysis of market data, one can take into account more faithfully the real behavior of financial markets (in particular the ‘rare events’) for asset allocation, derivative pricing and hedging, and risk control. This course will introduce some concepts to better address these issues. As these ideas are not (yet) standard, they are not found in any one book and the course will largely be based on lecture notes. There will also be two sessions in the Hanlon lab learning to use a Bloomberg terminal.

Course topics

  • Financial Instruments: Bloomberg Analysis
  • Statistical Analysis of Financial Data
  • Stochastic Processes
  • Statistical Modeling of Trading Strategies

Some Useful References

  1. Risk Management and Financial Institutions, John Hull, John Wiley & Sons, 2012 (optional)
  2. An Introduction to the Mathematics of Financial Derivatives, 2nd Edition, Salih Neftci, Academic Press, 2000 (optional)
  3. 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:
d.Skew(), Kurt(), Average(), Stdev()
2) Data Analysis Function : Histogram

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.

Week Topic(s) Homework
1 Stochastic Processes
2 Statistical Modeling of Trading Strategies
3 Optimal Hedging Monte Carlo (OHMC) Methods
4 Optimal Hedging Monte Carlo (OHMC) Methods
5 Optimal Hedging Monte Carlo (OHMC) Methods
6 Introduction to Credit Derivatives
7 Introduction to Credit Derivatives
8 Introduction to Credit Derivatives
9 Mid-term Exam
10 Modeling Extreme Moves with Power Laws
11 Modeling Extreme Moves with Power Laws
12 Basel II, Basel III, and CVA
13 Thanksgiving
14 Basel II, Basel III, and CVA
15 Asset Replication
16 Final Exam