Wolf Ketter's Publications

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A Computational Approach to Predicting Economic Regimes in Automated Exchanges

Wolfgang Ketter, John Collins, Maria Gini, Alok Gupta, and Paul Schrater. A Computational Approach to Predicting Economic Regimes in Automated Exchanges. In Proc. of the Fifteenth Annual Workshop on Information Technologies and Systems, pp. 147–152, Las Vegas, Nevada, USA, December 2005.

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Abstract

We present a computational approach to identify dominant market conditions, such as over-supply or scarcity, and to predict market changes in automated exchange environments. Intelligent agents can learn the characteristics of prevailing economic conditions, or regimes, from historical data. Agents can then use real-time observable information to identify the current market regime and forecast upcoming market changes. We show that different market regimes can be effectively identified using our methodology. We also present preliminary work on a method to predict regime transitions. We experimentally validate our approach with data from the Trading Agent Competition for Supply Chain Management.

@InProceedings{Ketter05wits,
  author =       "Wolfgang Ketter and John Collins and Maria Gini and Alok Gupta and Paul Schrater",
  title =        "A Computational Approach to Predicting  Economic Regimes in Automated Exchanges",
  booktitle =    WITS05,
  pages =        {147--152},
  year =         "2005",
  abstract = "We present a computational approach to identify dominant market
conditions, such as over-supply or scarcity, and to predict market
changes in automated exchange environments. Intelligent agents can
learn the characteristics of prevailing economic conditions, or
regimes, from historical data. Agents can then use
real-time observable information to identify the current market regime
and forecast upcoming market changes. We show that different
market regimes can be effectively identified using our
methodology. We also present preliminary work on a method to predict
regime transitions. We
experimentally validate our approach with data from the Trading
Agent Competition for Supply Chain Management."
  address =      {Las Vegas, Nevada, USA},
  month =        {December},
  bib2html_pubtype = {Refereed Conference},
  bib2html_rescat = {Trading Agents: Supply-Chain Management},
}

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