CIS 9556 – Sample Course Syllabus

Title Risk Management Systems
Description

The students will gain an understanding of how institutional financial risks can be quantified and managed using information technology. This course discusses issues in aggregating and rationalizing real-time data from multiple trading sources in designing and implementing firmwide risk systems. The course discusses the business and IT issues, regulatory requirements, and techniques to measure and report risk across a major financial organization and examines several cases of major risk failures. It further addresses market, credit, operational, model, and liquidity risks and the Basel II recommendations regarding risk management in financial institutions. As a part of the course, the students will experience vendor systems and risk applications at the Subotnick Financial Services Center. Students will learn to compute Value at Risk (VaR), perform a Monte Carlo simulation using spreadsheet software, and have an understanding of best practices as well as the underlying assumptions and limitations of widely used models in risk management practice.

 

Soc Gen Trader loses billions due to a “rogue trader”.  Citibank, ML, UBS, lose billions in CDO’s, Bear Stearns “saved” by JP Morgan Chase, AIG saved by the US government to avoid a global crisis in credit derivatives, Amaranth hedge fund losses $7B in one week and Lehman Brothers goes bankrupt.   These are not new stories but recurring crises going back many years.  How did so many smart people lose so much money???  This course will explain what happened, examine a number of notorious cases, review what regulators are doing about it, (the now famous Basel II and III Accord), calculate Value at Risk and what you need to know to read and understand risk management reports, or architect and build or buy a risk management system.

In today’s world of rapid information flows, rising volatility, regulatory concerns and oversight, prudent management increasingly requires understanding and measuring risk.  Merged or individual banks, securities dealers, insurance companies and industrial firms with significant financing operations, all require enterprise-wide risk management that may span many operations across currencies and locations in real time.  Risk management establishes standards for aggregating disparate information, gathering market data, calculating risk measures and creating timely reporting tools for management market, credit, and operational risks.  This course is directed toward students interested in understanding how large-scale complex risk can be quantified, needs to be managed and architected.  We identify the business and technical issues, regulatory requirements and techniques to measure and report risk across a major organization.

Prerequisites Prerequisite: STA 9708; FIN 9770 or CIS 9555; or permission of the instructor
Learning Goals  
Grades
  • Midterm  45%
  • Final 45%
  • Class Participation and Homework 10%
Textbooks and other material
  • Jorion, Phillippe, Value at Risk: The New Benchmark for Managing Financial Risk, 3rd edition, McGraw-Hill, 2007 (The 2nd edition is not a substitute).
  • Roger Lowenstein, When Genius Failed, Random House, 2000

Other Reading Material & Cases will be supplied in class:

 

Topics Introduction to the course

The course – syllabus, grading, readings, etc.

Review of Modern Portfolio Theory, (EMH) and Behavioral finance

Review of probability and statistics (if needed)

Intro to risk management

Types of risk – market, credit, liquidity, operational, etc.

Examples of financial disasters

Review and discuss Barings case

Value at Risk –VaR

Risk measures for various asset classes

Historical VaR

Parametric VaR

Time scaling

Portfolio VaR

VaR Tools – Marginal, Component VaR, etc.

RAROC

Barings revisited

Calculating VaR of single equity using Excel and publicly available data

Homework #1 on calculating single instrument VAR and HW #2 on 2 asset VaR

VaR II

Monte Carlo Simulation

Choice of Quantitative Measures

Measurement Errors

GARCH Volatility Models

Model Risk

Back Testing

Stress Testing

Fat Tails

Extreme Value Theory (EVT and CVaR)

Review and discuss Orange County case

Liquidity Risk

Liquidity Risk and Leverage

Hedge Fund Risk Measures

First Exam Part I

First Exam Part II

When Genius Failed – LTCM case

Regulatory Environment

25 years of risk related regulations

BIS, Basel and Dodd Frank

Multifactor models

Discussion of multifactor analysis and Barra software

Barra system test cases

Credit Risk

Systems addressing Credit Risk

Empirical, Accounting and Financial

Altman Z Score, Merton Model and Jarrow Models

Credit Metrics, etc. Credit Rating Systems

2008 Crisis

Credit Default Swaps (CDS)

CDO’s, CMO’s and other structured finance

Tranching of Sub-prime CDOs

What happened to AIG?

SIVs and off balance sheet financing and lessons on credit risk management

Operational Risk and its Basel II requirements

Defining and organizing operational risk

CSAs, KRI’s

Measuring Op Risk for VaR

Six Sigma and Balanced Scorecards for process improvement

Second Exam