Risk Courses

 

 

 

 

 

 

 

 

 

Risk Management Courses

Risk Seminar

ECON 217/STAT 278B

The Risk Seminar is cross-listed as Econ 217 and a section of STAT 278B. It focuses on the statistical and economic measurement and management of risk, and includes presentations by participants on a broad range of topics related to risk, such as the determination of portfolio returns, performance attribution, pricing anomalies, counterparty risk, and asset returns containaing jumps.

The seminar will be led by Lisa R. Goldberg and Robert M. Anderson. In fall 2014, the seminar meets Tuesdays from 11 to 1 in 639 Evans.

The course is open to Ph.D. students only, and requires permission of the Instructors. Please email Robert Anderson to request permission.

Quantitative Risk Management I: Modeling and Measuring Financial Risk--This Course is not offered in 2014-2015.

 

Economics 296/ Statistics 260

Syllabus

 

 

The global financial crisis that began in 2007 resulted in trillions of lost dollars, millions of lost jobs and unquantifiable human suffering.  However, the impact of the crisis on the practice of risk management is more difficult to assess.  Have Dodd-Frank and Basel III made financial markets safer?  Is risk management an art?  a science?  a sham? Is the familiar analogy between financial markets and gambling casinos valid?  To what extent can quantitative methods borrowed from physical sciences, mathematics and statistics be used to measure and to manage financial risk?

 

This provocative course explores the current state-of-the art in financial risk management and provides an historical perspective on its evolution.  Risk analysis became part of finance in 1952 when Harry Markowitz formulated an investment decision as a tradeoff between portfolio expected return and variance.  In this setting, portfolio variance is the quantitative embodiment of risk. Markowitz's formulation launched six decades of vigorous, probabilistic research into the nature of financial risk.  A short list of important topics includes techniques for measuring risk, competing notions of diversification, portfolio construction and optimization, asset allocation, statistical evaluation of investment strategies, the econometrics of financial time series and the properties of financial derivatives.  We study these topics in the context of data limitations, regulatory constraints, market frictions and other practical considerations faced every day by financial practitioners.