My general research interest are in the areas of financial risk management, quantitative and computational finance,
financial engineering, enterprise risk management, investment and trading, and intelligent systems. Most of this
research involves forecasting equity, option, and commodity prices, modeling volatility, and managing credit, market,
and operational risk. Additional interests include hedge fund replication, optimizing option-based spreading strategies,
and assisting the TU student investment fund. Much of his quantitative research involves the use of intelligent
mathematical and computer models, including neural networks, fuzzy logic, evolutionary systems, agent-based systems,
artificial life, data mining, and simulation.
Current Research Focus Areas
I am currently working in the following areas either independently
or with other students and faculty:
- Stock price forecasting using computational models
with either fundamental or technical indicators provided as inputs.
- Hedge fund replication.
- Using neural networks to estimate implied volatility and forecast option prices.
- Optimizing option-based spreading strategies.
- Using intelligent agents for understanding the behavior of stock market investors and
general market dynamics.
Past Research Projects Past funded
and non-funded research projects with which I have been involved
include the following (current research is focused in the area of financial risk management and computational finance):
- Using real options and game theory for placing a valuation on transmission capital investment.
- Developing economic loss estimation methodologies for predicting
the economic impact of an earthquake hazard.
- Stock price forecasting using fuzzy logic to account for
the heuristic uncertainty found in trading decisions guided
by technical analysis indicators.
- Stock price forecasting using genetic and evolutionary
algorithms for optimizing the trading signals provided to
neural networks.
- Electricity price forecasting using neural networks and traditional
mathematical models.
- Studying the effects of electricity deregulation across
the country in terms of market structure and the market dynamics
of electricity price and transmission investment.
- Researching the types of electricity deregulation configurations
most likely to develop in Missouri.
- Developing an expert system for integrating the ISO 9001 quality system guidelines
and an evaluation approach based on the Malcolm Baldrige National Quality Award (MBNQA) criteria .
- Intelligent electric load forecasting using neural networks,
knowledge-based systems, and applied statistics.
- Optimization of electronic part placement machines using
heuristic programming.
- Maintenance analysis of a web-driven diagnostic tool using
a knowledge-based system.
- Group technology machine-part family formation using neural
networks and parallel computing.
- Image processing and inspection algorithms for artificial
vision systems using neural networks.
- Word recognition within a document using neural networks.
- Speaker identification using neural networks.
- Expert system development for managing safety requirements
using a knowledge-based system.
- Biological modeling of the primate retina, LGN, primary
visual cortex, and pulvinar nucleus using connectionist networks.
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