Stock Trading with Random Forests, Trend Detection Tests and Force Index Volume Indicators

Piotr Ładyżyński , Przemysław Grzegorzewski , Kamil Piotr Żbikowski

Abstract

The goal of this paper is to investigate if the strong machine learning technique is able to retrieve information from past prices and predict price movements and future trends. The architecture of the system with the on-line adaptation ability to non-stationary two dimensional mixed Black-Scholes Markov time series model is presented. The methodology of investment strategies performance verification is also proposed.
Author Piotr Ładyżyński (FMIS)
Piotr Ładyżyński,,
- Faculty of Mathematics and Information Science
, Przemysław Grzegorzewski (FMIS / DSPFM)
Przemysław Grzegorzewski,,
- Department of Stochastic Processes and Financial Mathematics
, Kamil Piotr Żbikowski (FEIT / IN)
Kamil Piotr Żbikowski,,
- The Institute of Computer Science
Pages441-452
Publication size in sheets0.55
Book Rutkowski Leszek, Korytkowski Marcin, Scherer Rafal, Tadeusiewicz Ryszard, Zadeh Lotfi A., Zurada Jacek (eds.): Artificial Intelligence and Soft Computing. Part II, Lecture Notes in Artificial Intelligence, vol. 7895, 2013, Heidelberg New York Dordrecht London, Springer, ISBN 978-3-642-38609-1, [978-3-642-38610-7], 637 p., DOI:10.1007/978-3-642-38610-7
front-mater.pdf / 365.21 KB / No licence information
Abstract in PolishW pracy zaproponowano nowy system wspomagający inwestowanie na giełdzie, wykorzystujący zaawansowane metody uczenia maszynowego. System ów wykazuje dobre własności adaptacyjne do niestacjonarnych szeregów czasowych.
DOIDOI:10.1007/978-3-642-38610-7_41
URL http://link.springer.com/chapter/10.1007%2F978-3-642-38610-7_41
ProjectDevelopment of new methods and algorithms in the following areas: computer graphics, artificial intelligence, and information systems, and distributed systems . Project leader: Rybiński Henryk, , Phone: +48 22 234 7731, start date 29-05-2012, planned end date 31-12-2012, end date 30-11-2013, II/2012/DS/1, Completed
WEiTI Działalność statutowa
Languageen angielski
Score (nominal)15
Score sourceconferenceIndex
ScoreMinisterial score = 10.0, 14-06-2020, BookChapterSeriesAndMatConfByConferenceseries
Ministerial score (2013-2016) = 15.0, 14-06-2020, BookChapterSeriesAndMatConfByConferenceseries
Publication indicators WoS Citations = 6; Scopus Citations = 11; GS Citations = 7.0
Citation count*7 (2015-08-19)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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