ML Anthology

Stock Selection via Nonlinear Multi-Factor Models

Asriel E. Levin
NeurIPS 1995 pp. 966-972
/neurips/1995/levin1995neurips-stock/

Abstract

This paper discusses the use of multilayer feed forward neural net(cid:173) works for predicting 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.

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Text

Levin. "Stock Selection via Nonlinear Multi-Factor Models." Neural Information Processing Systems, 1995.

Markdown

[Levin. "Stock Selection via Nonlinear Multi-Factor Models." Neural Information Processing Systems, 1995.](https://mlanthology.org/neurips/1995/levin1995neurips-stock/)

BibTeX

@inproceedings{levin1995neurips-stock,
  title     = {{Stock Selection via Nonlinear Multi-Factor Models}},
  author    = {Levin, Asriel E.},
  booktitle = {Neural Information Processing Systems},
  year      = {1995},
  pages     = {966-972},
  url       = {https://mlanthology.org/neurips/1995/levin1995neurips-stock/}
}