CIFEr'96 Tutorial Information, New York, March 24, 1996

Payman Arabshahi 8834870 (
Fri, 26 Jan 1996 17:18:24 +0100


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IEEE/IAFE Conference on
Computational Intelligence for Financial Engineering

March 24-26, 1996
Crowne Plaza Manhattan - New York City
[next update: February 1]


Sunday, March 24

There are two tracks for the tutorials. Both the Engineering Track and
the Finance Track offer three choices each of 4-hour presentations.
Participants should select one morning tutorial and one afternoon
tutorial, as the tutorial registration fee covers the full day (two
tutorials). Tutorials will be held from 8:30 AM to 5:30 PM on Sunday,
March 24th at the Crowne Plaza Manhattan. Registration is on a
first-come, first-served basis for tutorial selection, so send your
registration form in as soon as possible.


E-1 - Robust Statistical Methods for Analyzing
and Modeling Financial Data

8:30 am-12:30 pm
R. Douglas Martin, Professor
Department of Statistics
University of Washington

The tutorial shows how and why the classical statistical methods
underlying financial analysis and modeling, such as the sample standard
deviation, the sample correlation coefficient and linear regression
methods, are non-robust toward outliers and sometimes give misleading or
useless results. Basic theoretical foundations of robust statistical
methods are outlined, and robust alternatives to the classical methods are
introduced and illustrated in the context of important financial data
applications, such as volatility and risk metric calculations.


E-2 - Data-Driven Methods for Non-Linear Time Series Modeling:
Multivariate Adaptive Regression Splines (MARS) and
Autoregressive Modular (ARM)

1:30-5:30 pm
Bonnie K. Ray, Professor
Department of Mathematics and Center
for Applied Math and Statistics
New Jersey Institute of Technology

This two-part tutorial covers in detail two new classes of computationally
intensive algorithms for modeling nonlinear time series. The first part
covers the application of Multivariate Adaptive Regression Splines (MARS)
to model univariate nonlinear time series having threshold autoregressive
behavior. Extensions will then be presented to Semi-Multivariate Adaptive
Spline Threshold Autoregressive (SMASTAR) models. The second part
presents the class of Autoregressive Modular (ARM) models and will
concentrate on the special case of Transform-Expand-Sample (TES)


E-3 - Neural Networks, Genetic Algorithms and Case-Based Reasoning
for Financial Engineering Applications

1:30-5:30 pm
Dr. Roy S. Freedman
Inductive Solutions, Inc.

This tutorial shows how these quantitative techniques are used in
practice, with topics covered including: 1) Comparing linear, nonlinear,
and time-varying regression to neural networks, 2) Using neural network
techniques to adaptively learn how to price options, 3) Using genetic
algorithms in portfolio optimization problems, 4) Designing derivative
securities with genetic algorithms, 5) The news on news: how case-based
expert systems integrate subjective knowledge into fundamental models.


F-1 - Exotic Options

8:30AM-12:30 pm
Peter Zhang
Vice President
Chemical Bank

This tutorial examines the valuation, use and hedging of second-generation
option products including various types of path-dependent options,
correlation options, compound options, digitals, deferred-start options,
and others. The tutorial illustrates how exotic options are employed to
create structured note products like corridor bonds. Issues like multiple
and exploding greeks are addressed, as well as correlation risk. Hedging
techniques like mirror imaging/ static replication and ramp building are


F-2 - Term Structure Modeling

8:30 am -12:30 pm
Richard H. Stanton
Assistant Professor
Haas School of Business
University of California - Berkeley

This tutorial details the development, parameterization and implementation
of equilibrium and no-arbitrage style term structure models. Single and
multi-factor models are examined. Issues covered include duration and
convexity measurement and the valuation of various forms of interest-rate
derivatives including pure discount bonds, bond options, caps, and the


F-3 - Risk Management

1:30-5:30 pm
Jan W. Dash, Ph.D.
Quantitative Analysis
Global Risk Management
Smith Barney

This tutorial will cover 1) characterization of risks in finance: market
risk (interest rates, FX rates, equity indices, spreads), trading risk,
systems risk (software, hardware, vendors), model risk, and 2)
quantitative measurement of risk: the Greeks (Delta, Gamma, Vega), the
partial Greeks (Ladders), the new Greeks (Exotics), dollars at risk
(n-Sigma analysis), correlations, static scenario analysis, dynamic
scenario analysis, Monte Carlo risk analysis, beginnings of risk
standards, DPG, Risk Metrics, and 3) case study of risk: the Viacom CVR
Options and 4) pricing and hedging for interest rate derivatives.

Payman Arabshahi
Electronic Publicity Chair, CIFEr'96             Tel  : (205) 895-6380
Dept. of Electrical & Computer Eng.              Fax  : (205) 895-6803
University of Alabama in Huntsville    
Huntsville, AL 35899