FE 635 Financial Enterprise Risk Engineering: Modern Financial Engineering

From Hanlon Financial Systems Lab Web Encyclopedia
(Difference between revisions)
Jump to: navigation, search
(Created page with "Professor: Dr. Rupak Chatterjee<br /> Office: Babbio 5<sup>th</sup> Floor<br /> Email: Rupak.Chatterjee@stevens.edu<br /> Class Schedule: Thursdays 6:15 p.m. to 8:45 p.m., Bab...")
 
Line 5: Line 5:
 
Hanlon Lab: Jan18, 25, Feb 1, Friday 5:00 p.m. – 7:00 p.m. (Bloomberg Training)<br />
 
Hanlon Lab: Jan18, 25, Feb 1, Friday 5:00 p.m. – 7:00 p.m. (Bloomberg Training)<br />
 
Office Hours: Wednesday 3:00 p.m. to 5:00 p.m.<br />
 
Office Hours: Wednesday 3:00 p.m. to 5:00 p.m.<br />
 +
 +
== Course Objectives and Description ==
 +
This course is largely a continuation of FE 535. After a review of stochastic processes, a <big>Statistical Arbitrage Strategy</big> is studied in detail. The <big>Optimal Hedging Monte Carlo</big> methodology for derivative pricing is introduced. Potential research topics on OHMC at the Master’s/PhD level will be discussed. <big>Credit Derivatives</big> will be introduced along with the pricing mechanisms using Hazard rates and Copulus. The study of Fat-tailed distributions such as <big>Pareto</big> and those coming from <big>Extreme Value theory</big> will follow. Finally, modern regulatory theory using <big>Basel II, Basel III, and CVA</big> as a starting point will be analyzed. Similar to FE535, the course will largely be based on lecture notes.<br />
 +
<big>Prerequisites: FE 535 or Solid Knowledge of Statistics/Probability Theory and some familiarity of financial instruments</big>
 +
== Course topics ==
 +
* Statistical Arbitrage
 +
* Optimal Hedging Monte Carlo
 +
* Credit Derivatives
 +
* Extreme Value Theory
 +
* Basel II, Basel III, and CVA
 +
* Asset Replication
 +
== 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)
 +
=== Syllabus ===
 +
Chapters from Lecture notes: Modern Methods of Financial Engineering and Risk Management:<br />
 +
4 Stochastic Processes 93<br />
 +
5 Optimal Hedging Monte Carlo (OHMC) Methods 129<br />
 +
6 Introduction to Credit Derivatives 153<br />
 +
7 Modeling Extreme Moves with Power Laws 191<br />
 +
8 Basel II, Basel III, and CVA 203<br />
 +
 +
== IT Requirements ==
 +
All the homeworks require the use of Excel with the following properties:<br />
 +
 +
:1) Functions:
 +
::a.Offset()
 +
::b.Rand()
 +
::c.Norminv()
 +
::d.Skew(), Kurt(), Average(), Stdev()
 +
::e.Gammaln()
 +
:2) Data Analysis Function : Histogram<br />
 +
: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.
 +
 +
{| class="wikitable"
 +
|-
 +
! Week !! Topic(s) !!Homework
 +
|-
 +
| 1 || Stochastic Processes||
 +
|-
 +
| 2 || Stochastic Processes||
 +
|-
 +
| 3 || Statistical Modeling of Trading Strategies||
 +
|-
 +
| 4 || Statistical Modeling of Trading Strategies ||
 +
|-
 +
| 5 || Optimal Hedging Monte Carlo (OHMC) Methods||
 +
|-
 +
| 6 || Optimal Hedging Monte Carlo (OHMC) Methods||
 +
|-
 +
| 7 || Introduction to Credit Derivatives||
 +
|-
 +
| 8 || <big>Midterm</big>||
 +
|-
 +
| 9 || <big>Spring Recess (Study!)</big> ||
 +
|-
 +
| 10 || Introduction to Credit Derivatives||
 +
|-
 +
| 11 || Introduction to Credit Derivatives||
 +
|-
 +
| 12 || Modeling Extreme Moves with Power Laws||
 +
|-
 +
| 13 || Modeling Extreme Moves with Power Laws||
 +
|-
 +
| 14 || Basel II, Basel III, and CVA||
 +
|-
 +
| 15 || Basel II, Basel III, and CVA||
 +
|- 
 +
| 16 || <big>Final Exam</big> ||
 +
|}

Revision as of 10:45, 22 January 2013

Professor: Dr. Rupak Chatterjee
Office: Babbio 5th Floor
Email: Rupak.Chatterjee@stevens.edu
Class Schedule: Thursdays 6:15 p.m. to 8:45 p.m., Babbio 122
Hanlon Lab: Jan18, 25, Feb 1, Friday 5:00 p.m. – 7:00 p.m. (Bloomberg Training)
Office Hours: Wednesday 3:00 p.m. to 5:00 p.m.

Contents

Course Objectives and Description

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

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)

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

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.

Week Topic(s) Homework
1 Stochastic Processes
2 Stochastic Processes
3 Statistical Modeling of Trading Strategies
4 Statistical Modeling of Trading Strategies
5 Optimal Hedging Monte Carlo (OHMC) Methods
6 Optimal Hedging Monte Carlo (OHMC) Methods
7 Introduction to Credit Derivatives
8 Midterm
9 Spring Recess (Study!)
10 Introduction to Credit Derivatives
11 Introduction to Credit Derivatives
12 Modeling Extreme Moves with Power Laws
13 Modeling Extreme Moves with Power Laws
14 Basel II, Basel III, and CVA
15 Basel II, Basel III, and CVA
16 Final Exam
Personal tools
Namespaces

Variants
Actions
Navigation
Toolbox
SUPPORT