As the amount of financial information proliferates without limit, investors face increasing difficulties in assimilating appropriate inputs for intelligent investment decisions. Limited attention and memory resources force investors to focus on vanishingly small proportions of the available financial information. In collaboration a student with experience in the financial industry, I have developed computational models that capture biological attention, memory, and social learning to provide investors with tools to enhance success in financial decision making. In particular, I have introduced three new families of machine learning algorithms that are sensitive to context [17, 18] and time  to filter financial information and provide actionable intelligence, and I have studied the impact of social learning  in a simulated trader population, how individual investors are influenced by other traders, and how centralized market intervention may alter market trends.
- Wong, C., and Versace, M. (2012) CARTMAP: a neural network method for automated feature selection in financial time series forecasting. Neural Computing and Applications, DOI 10.1007/s00521-012-0830-8
- Wong, C., and Versace, M. (2011) Context Sensitivity with Neural Models in Financial Decision Processes.Global Journal of Business Research. Vol. 5, No. 5, pp. 27-43.
- Versace, M., Bhatt, R., Hinds, O., and Shiffer, M. (2004) Predicting the exchange traded fund DIA with a combination of Genetic Algorithms and Neural Networks. Expert Systems with Applications.27, 417–425.
Abstracts & Conference papers
- Wong, C., and Versace, M. (2011) Re-thinking financial neural network studies: Seven cardinal confounds. Global Conference on Business and Finance, Las Vegas, Nevada.
- Wong, C., and Versace, M. (2011) Echo ARTMAP: Context sensitivity with neural networks in financial decision-making. Global Conference on Business and Finance, Las Vegas, Nevada.
- Versace, M., Bhatt, R., Hinds, O. and Shiffer, M. (2004) Optimizing financial applications through biologically-inspired methods. Proceedings of the International Conference on Financial Engineering and Application, Cambridge, MA, USA.
- Wong, C., and Versace, M. (2010) Putting the Dollars and Sense Back into Financial Forecasting with Neural Networks. ICCNS 2010, Boston, MA, USA.