An enhanced absorbing Markov chain model for predicting TAIEX Index Futures

Wen-Tso Huang and Cheng-Chang Lu

Communications in Statistics - Theory and Methods, 2018, vol. 47, issue 1, 133-146

Abstract: This study introduces an enhanced absorbing Markov chain model for predicting Taiwan Stock Exchange Capitalization Weighted Stock Index Futures (TAIEX Futures) trends. Data were gathered from the U.S. TAIEX Futures Yahoo portal site and converted into a regular Markov chain model. A regular Markov chain enables long-term behavioral predictions to be made with regard to the probability of TAIEX Futures. This paper also demonstrates an artificial variable technique for establishing an enhanced absorbing Markov chain model for determining how long TAIEX Futures will increase before prices begin to fall. The results show that the TAIEX Futures absorbing Markov chain can warn investors about the least number of days on average that a particular TAIEX Futures that increased or decreased that day will increase before its price begins to fall.

Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2017.1300281 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:47:y:2018:i:1:p:133-146

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2017.1300281

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().