The Fourth Annual 2008 MLSP competition

Kenneth E. Hild, Vince Daniel Calhoun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

For the Fourth Annual 2008 Machine Learning for Signal Processing competition entrants were asked to develop a machine learning algorithm that maximizes the rate of return by trading (buying, selling, shorting, or covering) stocks over a six-month time period. Each entrant began with a (fictional) $100,000 USD. Both the training and the test set include the daily price and volume for a total of 2929 stocks that are traded in American stock markets and a total of 41 monthly indices. Stock valuations are based on real (historical) stock prices. This year there were 5 algorithms submitted. The highest annual rate of return of an astonishing 150% was obtained by Peng and Ji of the Rensselaer Polytechnic Institute/Shanghai Maritime University team.

Original languageEnglish (US)
Title of host publicationProceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008
Pages38-42
Number of pages5
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008 - Cancun, Mexico
Duration: Oct 16 2008Oct 19 2008

Other

Other2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008
CountryMexico
CityCancun
Period10/16/0810/19/08

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ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Electrical and Electronic Engineering

Cite this

Hild, K. E., & Calhoun, V. D. (2008). The Fourth Annual 2008 MLSP competition. In Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008 (pp. 38-42). [4685452] https://doi.org/10.1109/MLSP.2008.4685452