scholarly journals Analysis of Portfolio Selection Model in Indian Stock Market

2021 ◽  
Vol 8 (2) ◽  
pp. 58-81
Author(s):  
Shubham Sah ◽  
Amit Kundu ◽  
Anil Kumar Goyal
2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Daping Zhao ◽  
Yong Fang ◽  
Chaoliang Zhang ◽  
Zongrun Wang

The traditional portfolio selection model seriously overestimates its theoretic optimal return. Aiming at this problem, two portfolio selection models are proposed to modify the parameters and enhance portfolio performance based on Bayesian theory. Firstly, a Bayesian-GARCH(1,1) model is built. Secondly, Markov Chain is applied to curve the parameters’ state transfer, and a Bayesian Markov regime-Switching-GARCH(1,1) model is constructed. Both the two models can handle the overestimation problem and can obtain self-financing portfolios. In the numerical experiments, both the models are examined with data from China stock market, and their performances are compared and analyzed. The results show that BMS-GARCH(1,1) model is superior to the Bayesian-GARCH(1,1) model.


2010 ◽  
Vol 23 (9) ◽  
pp. 1114-1119 ◽  
Author(s):  
V. Naicker ◽  
J.G. O’Hara ◽  
P.G.L. Leach

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