Stock Selection via Nonlinear Multi-Factor Models
–Neural Information Processing Systems
This paper discusses the use of multilayer feedforward neural networks forpredicting a stock's excess return based on its exposure to various technical and fundamental factors. To demonstrate the effectiveness of the approach a hedged portfolio which consists of equally capitalized long and short positions is constructed and its historical returns are benchmarked against T-bill returns and the S&P500 index. 1 Introduction
Neural Information Processing Systems
Dec-31-1996
- Country:
- North America > United States > California > San Francisco County > San Francisco (0.14)
- Genre:
- Research Report (0.34)
- Industry:
- Banking & Finance > Trading (0.47)
- Technology: