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Mathematical and Statistical Methods for Actuarial Sciences and Finance pp 253–261Cite as

A pattern recognition algorithm for optimal profits in currency trading

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Abstract

A key issue in technical analysis is to obtain good and possibly stable profits. Various trading rules for financial markets do exist for this task. This paper describes a pattern recognition algorithm to optimally match training and trading periods for technical analysis rules. Among the filter techniques, we use the Dual Moving Average Crossover (DMAC) rule. This technique is applied to hourly observations of Euro-Dollar exchange rates. The matching method is accomplished using ten chart patterns very popular in technical analysis. Moreover, in order for the results to have a statistical sense, we use the bootstrap technique. The results show that the algorithm proposed is a good starting point to obtain positive and stable profits.

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Author information

Authors and Affiliations

  1. Dipartimento di Scienze della Comunicazione, University of Teramo, Teramo, Italy

    Danilo Pelusi

Authors
  1. Danilo Pelusi
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Editor information

Editors and Affiliations

  1. Department of Applied Mathematics, University Ca’ Foscari Venice, Venice, Italy

    Marco Corazza

  2. Department of Statistics, University Ca’ Foscari Venice, Venice, Italy

    Claudio Pizzi

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Pelusi, D. (2010). A pattern recognition algorithm for optimal profits in currency trading. In: Corazza, M., Pizzi, C. (eds) Mathematical and Statistical Methods for Actuarial Sciences and Finance. Springer, Milano. https://doi.org/10.1007/978-88-470-1481-7_26

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