Volume 5, Issue 17 (10-2014)                   jemr 2014, 5(17): 87-122 | Back to browse issues page

XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Asgharpur H, Fallahi F, Sanoubar N, Rezazadeh A. Stock Optimal Portfolio Selection in a VaR Framework: Comparison the MS-GARCH and Bootstrapping Methods. jemr 2014; 5 (17) :87-122
URL: http://jemr.khu.ac.ir/article-1-858-en.html
1- University of Tabriz , asgharpurh@gmail.com
2- University of Tabriz
Abstract:   (9401 Views)
The main goal of this research is to calculate VaR index with parametric Markov-Switching GARCH approach for accepted companies in Tehran Stock Exchange and also selecting the optimal portfolio of their stocks. To calculate the index, data and information of weekly stock price of 10 representative firms during the period 2008-2014 has been used which account for 332 working weeks.
The results from estimation of VaR and determination of optimal stock portfolio in the non-linear programming framework showed that optimal portfolio of food-industry companies stock, in the context of VaR has higher returns and risk in the first regime (Boom period) compared to the second regime ( recession period). On the other hand, it has had lower weight in both stock portfolios that had lower average returns compared to the rest of the stocks and compared to the stocks which had lower VaR relative to other stocks that has higher weights.
The Kupiec and Lopez back testing using 10 future week data, showed that both of approaches is valid but the parametric approach has better rank. Therefore the optimal portfolios of stocks under parametric VaR will be accepted as final optimal portfolio.
Full-Text [PDF 449 kb]   (4966 Downloads)    
Type of Study: Applicable | Subject: پولی و مالی
Received: 2013/10/19 | Accepted: 2014/09/8 | Published: 2014/12/6

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Journal of Economic Modeling Research

Designed & Developed by : Yektaweb