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Kernel price pattern trading

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Abstract

A new approach to algorithmic trading system development is presented. This approach, Kernel Price Pattern Trading (KPPT P ), allows the practitioner to link the performance of a learned classifier (that predicts the occurrence of the price pattern P) to the profitability of the system. A positive definite kernel based distance that tries to capture the drivers of the process of price patterns formation and some results about the profitability of the system are also presented.

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Authors and Affiliations

  1. Algorithmic Trading Team, Innovating Finances S.A., Valparaíso, Chile

    Alejandro Cañete

  2. Informatics Department, Santa Maria University, Valparaíso, Chile

    Alejandro Cañete, Jorge Constanzo & Luis Salinas

Authors
  1. Alejandro Cañete
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  2. Jorge Constanzo
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  3. Luis Salinas
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Correspondence to Alejandro Cañete.

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Cañete, A., Constanzo, J. & Salinas, L. Kernel price pattern trading. Appl Intell 29, 152–156 (2008). https://doi.org/10.1007/s10489-007-0054-2

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  • DOI: https://doi.org/10.1007/s10489-007-0054-2

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