Financial Time Series Forecasting using Rough Sets with Time-Weighted Rule Voting

Mariusz Podsiadlo , Henryk Rybiński

Abstract

In the paper we investigate experimentally the feasibility of Rough Sets in building profitable trend prediction models for financial time series. In order to improve the decision process for long time series, a novel time-weighted rule voting method, which accounts for information aging, is proposed. The experiments have been performed using market data of multiple stock market indices. The classification efficiency and financial performance of the proposed Rough Sets models was verified and compared with that of Support Vector Machines models and reference financial indices. The results showed that the Rough Sets approach with time weighted rule voting outperforms the classical Rough Sets and Support Vector Machines decision systems and is profitable as compared to the buy and hold strategy. In addition, with the use of Variable Precision Rough Sets, the effectiveness of generated trading signals was further improved.
Author Mariusz Podsiadlo II
Mariusz Podsiadlo,,
- The Institute of Computer Science
, Henryk Rybiński II
Henryk Rybiński,,
- The Institute of Computer Science
Journal seriesExpert Systems With Applications, ISSN 0957-4174
Issue year2016
Vol66
Pages219-233
Publication size in sheets1.65
Keywords in EnglishDecision systems; Rough Sets; Financial time series prediction
DOIDOI:10.1016/j.eswa.2016.08.066
URL http://dx.doi.org/10.1016/j.eswa.2016.08.066
projectDevelopment of new algorithms in the areas of software and computer architecture, artificial intelligence and information systems and computer graphics . Project leader: Rybiński Henryk, , Phone: +48 22 234 7731, start date 18-05-2015, end date 30-11-2016, II/2015/DS/1, Completed
WEiTI Działalność statutowa
Languageen angielski
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Podsiadło_Rybiński-Financial Time Series.pdf (file archived - login or check accessibility on faculty) Podsiadło_Rybiński-Financial Time Series.pdf 7.58 MB
Score (nominal)35
ScoreMinisterial score = 35.0, 27-03-2017, ArticleFromJournal
Ministerial score (2013-2016) = 35.0, 27-03-2017, ArticleFromJournal
Publication indicators WoS Impact Factor: 2016 = 3.928 (2) - 2016=3.526 (5)
Citation count*3 (2018-02-13)
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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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