Abstract
The article considers an investment strategy based on observing the behavior of a certain organized group of investors belonging to the oanda.com platform. This platform provides data on the distribution of open positions between long and short for many different financial instruments. A relatively simple and quite effective investment strategy was developed, which was tested for various time ranges and various currency pairs. This data was generated artificially trying to keep statistical similarity to data published by Oanda. The basic observed variable was the share of long positions in the total number of open positions. The basic input variable of the strategy was the first derivative of the number of these open long positions. The investment risk was controlled by means of mechanisms typical of the brokerage platform. The tests were carried out on the selected fixed data set both in the Matlab environment and using the MetaTrader platform tester.
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Wilinski, A., Matuszak, P. (2019). An Investment Strategy Using Temporary Changes in the Behavior of the Observed Group of Investors. In: Pejaś, J., El Fray, I., Hyla, T., Kacprzyk, J. (eds) Advances in Soft and Hard Computing. ACS 2018. Advances in Intelligent Systems and Computing, vol 889. Springer, Cham. https://doi.org/10.1007/978-3-030-03314-9_9
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DOI: https://doi.org/10.1007/978-3-030-03314-9_9
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