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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Barber, B.M., Lee, Y.T., Liu, Y.J., Odean, T.: Just how much do individual investors lose by trading? Rev. Financ. Stud. 22(2), 609–632 (2008)
Barber, B.M., Odean, T.: Online investors: do the slow die first? Rev. Financ. Stud. 15(2), 455–488 (2002)
Barberis, N., Huang M.: Mental accounting, loss aversion, and individual stock returns. J. Finance 56(4), 1247–1292 (2001)
Fama, E.F.: Market efficiency, long-term returns, and behavioral finance. J. Financ. Econ. 49(3), 283–306 (1998)
Kahneman, D.: Maps of bounded rationality: Psychology for behavioral economics. Am. Econ. Rev. 93(5), 1449–1475 (2003)
Krutsinger, J.: Trading Systems: Secrets of the Masters, p. 242. McGraw-Hill, New York (1997)
Pasche, R.: How Many Pips Should We Target Per Day? DailyFX, 8 July 2014. www.dailyfx.com. Accessed Aug 2017
Ricciardi, V., Simon, H.K.: What is behavioral finance? Bus. Educ. Technol. J. 2(2), 1–9, Fall 2000 (2000)
Shiller, R.J.: From efficient markets theory to behavioral finance. J. Econ. Perspect. 17(1), 83–104 (2003)
Shiller, R.J.: Human behavior and the efficiency of the financial system. Handb. macroecon. 1, 1305–1340 (1999)
Thaler, R.H. (Ed.).:  Advances in Behavioral Finance, vol. 2. Princeton University Press (2005)
Thaler, R.H.: Misbehaving: The Making of Behavioral Economics. WW Norton & Company (2015)
Young, W.T.: Calmar Ratio: A Smoother Tool, Futures (magazine), October 1991
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Wilinski, A., Matuszak, P. (2019). An Investment Strategy Using Temporary Changes in the Behavior of the Observed Group of Investors. In: PejaÅ›, 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
Download citation
DOI: https://doi.org/10.1007/978-3-030-03314-9_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-03313-2
Online ISBN: 978-3-030-03314-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)