Wolf Ketter's Publications

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Detecting and Forecasting Economic Regimes in Automated Exchanges

Wolfgang Ketter, John Collins, Maria Gini, Alok Gupta, and Paul Schrater. Detecting and Forecasting Economic Regimes in Automated Exchanges. Technical Report 07-008, University of Minnesota, Dept of Computer Science and Engineering, 2007.

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Abstract

We present basic building blocks of an agent that can use observable market conditions to characterize the microeconomic conditions of the market and predict future market trends. The agent can use this information to make both tactical decisions such as pricing and strategic decisions such as product mix and production planning. We develop methods that can learn dominant market conditions, such as over-supply or scarcity, from historical data using computational methods to construct price density functions. We discuss how this knowledge can be used, together with real-time observable information, to identify the current dominant market condition and to forecast market changes over a planning horizon. We validate our methods by presenting experimental results in a case study, the Trading Agent Competition for Supply Chain Management.

@TechReport{Ketter07tr,
  author =       "Wolfgang Ketter and John Collins and Maria Gini and Alok Gupta and Paul Schrater",
  title =        "Detecting and Forecasting Economic Regimes
                  in Automated Exchanges",
  year =         "2007",
  abstract = "We present basic building blocks of an agent that can
use observable
market conditions to characterize the microeconomic conditions of the
market and predict future market trends.  The agent can use this
information to make both tactical decisions such as pricing and
strategic decisions such as product mix and production planning.  We
develop methods that can learn dominant market conditions, such as
over-supply or scarcity, from historical data using computational
methods to construct price density functions. We discuss how this
knowledge can be used, together with real-time observable information,
to identify the current dominant market condition and to forecast
market changes over a planning horizon.  We validate our methods by
presenting experimental results in a case study, the Trading Agent
Competition for Supply Chain Management.",
  institution =  "University of Minnesota, Dept of Computer Science
        and Engineering",
  number =       "07-008",
  address =      "Minneapolis, MN",
  bib2html_pubtype = {Unrefereed},
  bib2html_rescat = {Trading Agents: Supply-Chain Management},
}

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