A hybrid alpha-stable model development for high frequency trading markets
José Climent Hernández (),
Luis Fernando Hoyos-Reyes and
Marissa R. Martínez-Preece
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Luis Fernando Hoyos-Reyes: Universidad Autónoma Metropolitana, México
Marissa R. Martínez-Preece: Universidad Autónoma Metropolitana, México
Contaduría y Administración, 2018, vol. 63, issue 4, 31-32
Business activities require to obtain, organize and manage information from large amounts of data. In hedge funds, short selling trade and derivatives valuation, agents change their strategies to improve profits, and therefore to increase their possibilities to remain in the market, as a result of finding more accurate methods to process ever larger volume of information, considering that the information is not evenly distributed among markets participants. In this paper, a hybrid three stage model is formulated consisting of: a high frequency market model through a non-stationary Compound Poisson Process, a multilayer perceptron trained by backpropagation and, finally, estimators based on alpha-stable distributions, as an initial overview to develop a high frequency trading market operating system.
Keywords: a-stable processes; non-stationary compound Poisson processes; multilayer Perceptron; High frequency markets; Big Data. (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:nax:conyad:v:63:y:2018:i:4:p:31-32
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