The Fourth Annual 2008 MLSP competition

Kenneth E. Hild, Vince D. 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
StatePublished - Dec 1 2008
Externally publishedYes
Event2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008 - Cancun, Mexico
Duration: Oct 16 2008Oct 19 2008

Publication series

NameProceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008

Other

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

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Electrical and Electronic Engineering

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