Third Financial Mathematics Festival 22 — 24 March 2001 Dirac Science Library, 4th Floor Department of Mathematics The Florida State University

This our biggest event of the year for the Financial Mathematics program! We appreciate the continuing support to our students from the participating departments - Computer Science, Economics, Finance, Risk Management, and Statistics. Now we are happy to invite their faculty and graduate students to join Mathematics as three speakers from the financial sector bring very different experiences to us. We want to especially welcome Angun Zhou, who is new to Tallahassee but has been told good things about us by our own PhD and first annual Festival speaker, Edward Qian (Hunter, 1993). Our other two speakers have direct FSU connections: Steve Perfect was an Associate Professor of Finance before going to Sonat and subsequently El Paso Energy, then FPL; Ray Song's PhD is from our department (Quine, 1993) and he has worked in several aspects of the banking.

SCHEDULE OF EVENTS March 22—26

Thursday, 22 March 2001: 3:30 p.m.

For this Thursday talk only, space is limited; others than the Financial Mathematics second year students who wish to attend the Thursday talk should notify case@math.fsu.edu.

      3:30 p.m., 200 Love Building

Implied Forward Yield Curve Calculation

Ray Song, Vice President, Systems and Quantitative Analysis, Branch Banking and Trust

The yield curve, often referred to as the term structure of interest rates, is a graph of the relationship between the yields on Treasury securities or some other homogeneous groups of fixed-income securities and the time-to-maturity. The shape of the yield curve reflects the market's expectation about future interest rate moves, inflation outlook, and market conditions. The forward rate computed from (that is, implied by) the successive zero-coupon (spot) rates is the rate of interest specific to the security between two future dates. More importantly the implied forward rate is considered to be arbitrage-free. It is widely used as a pricing vehicle for forward trading contracts. In this note we will be focusing on the concepts and calculations of par, spot, and forward rates.

Friday, 23 March 2001: 3:30-6:00 p.m.

      3:30 p.m., Dirac Science Library, 4th Floor

Applications of VaR and EaR in Power Portfolio Risk Management

Steve Perfect, Director of Risk Analytics, Florida Power and Light

     In the presence of deregulation and market change, the typical utility's view of risk has evolved from one which examines operational risk alone to one which now incorporates risk arising from exposure to traded markets. Corporate decision-making now mandates use of quantitative methods such as value at risk (VaR) and earnings at risk (EaR) to measure and manage this exposure.
     Essentially VaR is a way of measuring the possible loss to the portfolio over a measured period of time for a specific confidence interval. VaR for a given portfolio is intended to be larger than all but a certain fraction of trading outcomes. Due to the recent popularity of VaR in corporate decision-making, many variations of VaR have come into being including daily VaR (DVaR), delta VaR, cash at risk (CaR), and credit-at-risk (CVaR), and earnings at risk (EaR). The scope of this discussion will be the application of VaR and Ear in power portfolio risk management. In practice, VaR requires that the decision-maker first set limits for the maximum permissible VaR. Specified VaR limits may then be achieved by adding measures to reduce risk. Hedge positions may be set up to reduce the exposure inherent in contracts for the forward sale of generating output against an asset. Further reduction of VaR may be achieved through the introduction of appropriate uncorrelated assets to the portfolio. An obvious example of this is the combination of wind and fossil assets in the same market area.
     EaR analysis leads to an efficient frontier view for asset portfolios whereby earnings may be optimized over a continuum of risk tolerance levels. Assuming you know what your risk tolerance is, an optimal portfolio of assets and contracts may be established based on EaR analysis.

Reception

Modeling Liquidity Risk

Angun Zhou, Principal, Advanced Research Center, State Street Global Advisors

The kernel regression method has recently become popular in financial studies. It is especially useful in the early stage of exploring the relationship among variables. An application is demonstrated to model the volatility of forward rates, whose relationship with the potential factors is unclear. It is shown that the forward rate and forward spread play different roles for the time series with different maturities.

Saturday, 24 March 2001      

      10:30 a.m., Dirac Science Library, 4th Floor

Bagels and Coffee

Opportunities, Resources and Skill Sets for Financial Engineering

Ray Song, Vice President, Systems and Quantitative Analysis, Branch Banking and Trust

Recent advances in information technologies have created the new economy. The rapidly changing business environment and global competition force companies to better manage the way they do business by adopting new technologies and using accurate and current information to make decisions. This evolution creates great opportunities for employment classified Quantitative Analyst or Financial Engineer for those who have a solid background in mathematics, statistics and finance, understand the nature of business and economics, have practical computer skills, and hence can quickly turn information into smart business decisions. In this discussion, I will briefly talk about my own experience, and then describe some of the areas and skill sets that different financial sector employers look for. After Dr. Song's comments, he is joined by Dr. Zhou and Dr. Perfect; they will each recount their own job paths, and then the three visitors will answer audience questions.

Panel Discussion and Audience Questions

Jobs!

Dr. Zhou, Dr. Perfect, Dr. Song

Cooperating Departments are: Economics, Finance, Mathematics, Risk Management and Statistics.

Graduate study in Financial Mathematics and a listing of the faculty is described in the Guide to Financial Mathematics at Florida State University

The Steering Committee is composed of Professors Paul Beaumont, Bettye Anne Case (Chair), David Kopriva, Ian McKeague, Don Nast and Craig Nolder.