A study on the effectiveness of investment strategy based on the concept of pivot points levels using Matthews criterion

• Autorzy: Wiliński A. , Nyczaj T. , Bera A. , Błaszyński P.
• Języki publikacji: EN

Abstrakty

EN

In this work, the possibility of assessing traditional investment strategy based on the pivot points for using with other than the commonly used criterion is examined. The authors attempted to apply the Matthews Correlation Coefficient (further reffered as MCC) criterion based on a confusion matrix when assessing the strategy to include more factors than the traditional criteria (such as profit, profit vs. Risk, Sharpe ratio, Calmar ratio) and to express these factors by one number. The criterion based on a confusion matrix is, in authors beliefs, unique in this application and gives a fairly valuable estimation of trading strategy. An example of several strategies tested on EURUSD 1h time series in selected intervals in the years 2012-2013 is considered. Among these strategies there is a simple strategy based on the concept of pivot points levels and more complex derivative strategies, based on the vector of optimized values of certain parameters. These strategies are evaluated using both traditional criteria and modification of MCC proposed by the authors.

Słowa kluczowe

EN

algorithmic trading; machine learning; investment strategies; confusion matrix

• Wydawca: Komisja Informatyki Polskiej Akademii Nauk, Oddział w Gdańsku
• Czasopismo: Journal of Theoretical and Applied Computer Science
• Rocznik: 2013
• Tom: Vol. 7, nr 4
• Strony: 42--55
• Opis fizyczny: Bibliogr. 15 poz., rys., tab.

Twórcy

autor

Wiliński A.

• Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Szczecin, Poland

autor

Nyczaj T.

• Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Szczecin, Poland

autor

Bera A.

• Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Szczecin, Poland

autor

Błaszyński P.

• Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Szczecin, Poland

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