EconPapers    
Economics at your fingertips  
 

Incorporating a leading indicator into the trading rule through the Markov-switching vector autoregression model

Tzu-Pu Chang and Jin-Li Hu ()

Applied Economics Letters, 2009, vol. 16, issue 12, 1255-1259

Abstract: This article examines the profitability of trading rules based on the smoothed probability of Markov-switching models and executes two models in Taiwan's case. The results present that both proposed models can earn excess returns over the buy-and-hold strategy and support that both can be used to trade. However, the univariate Markov-switching model, which only uses daily returns series does not successfully capture the trend in the stock market, especially during a bull market. This implies that high-frequency returns series contain lots of noises. In order to overcome this problem, the Markov-switching vector autoregression model that combines a leading indicator and returns is performed in this study. The results indicate a better trading pattern. We conclude that the leading indicator chosen from open interest in the future market increases useful information and reduces noises to improve model estimation, which can well identify the position of bull and bear markets.

Date: 2009
References: Add references at CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
http://www.informaworld.com/openurl?genre=article& ... 40C6AD35DC6213A474B5 (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:apeclt:v:16:y:2009:i:12:p:1255-1259

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEL20

Access Statistics for this article

Applied Economics Letters is currently edited by Anita Phillips

More articles in Applied Economics Letters from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2019-11-26
Handle: RePEc:taf:apeclt:v:16:y:2009:i:12:p:1255-1259