Bridging minds and machines


Aug 11, 2021
Bridging minds and machinesBy Shawn Hutchins

Research at Rice University’s Center for Computational Finance and Economic Systems (CoFES), which is supported by a gift from alumnus Mike Reed (B.S. ’87), bridges the use of artificial intelligence and machine learning to improve market risk assessment and options pricing.

The statistical and quantitative research includes two interdisciplinary teams of researchers who are building layers of time-series forecasting models that detect interdependencies and patterns in equity options from unstructured or nonlinear market data.

Statistics doctoral student Mike Jackson, and Alexander Gallegos, a junior double majoring in statistics and economics, and Cole Rabson, a sophomore in computer science, are creating an R package for the nonlinear autoregressive neural network with exogenous variables (NARX). They are also testing a trading algorithm that uses the (NARX) by performing a manual grid search on the parameters found in the NARX version available in Matlab, a commonly used programming and numeric computing platform.

Shiyuan Wang, a professional master in statistics student, and Samuel (Jae Hyun) Hong, a senior majoring in mathematical economic analysis, are working with Katherine Ensor, the Noah G. Harding Professor of Statistics, to develop models and teaching materials that use machine learning approaches to produce quicker and more accurate options pricing.  

Since its founding in 2002, CoFES has collaborated with departments at Rice University’s George R. Brown School of Engineering, School of Social Sciences, and the Jones School of Business to offer interdisciplinary training programs and courses. The knowledge gained from both research groups will be incorporated into the statistics and CoFES curriculum this fall.