scholarly journals Risk Return Relationship in the Portfolio Selection Models

2018 ◽  
Vol 08 (03) ◽  
pp. 358-366
Author(s):  
Ken Hung ◽  
C. W. Yang ◽  
Yifan Zhao ◽  
Kuo-Hao Lee
Keyword(s):  
Portfolio Selection ◽  
Selection Models ◽  
Risk Return

Portfolio Selection Models and Their Discrimination

2011 ◽  
Vol 2 (2) ◽  
pp. 65-91 ◽  
Author(s):  
Satadal Ghosh ◽  
Sujit Kumar Majumdar
Keyword(s):  
Portfolio Selection ◽  
Portfolio Management ◽  
Stock Return ◽  
Signal To Noise Ratio ◽  
Selection Models ◽  
Markowitz Model ◽  
Risk Return ◽  
Future Return ◽  
Possibility Distributions ◽  
Portfolio Selection Model

The stochastic nature of financial markets is a barrier for successful portfolio management. Besides traditional Markowitz’s model, many other portfolio selection models in Bayesian and Non-Bayesian frameworks have been developed. Starting with the basic Markowitz model, several cardinal models are used to find optimum portfolios with select stock set. Having developed the regression model of the return of each stock with the market return, the unsystematic part of the uncertainty was used to find the optimum portfolio and efficient risk–return frontier within each portfolio selection model. The average stock return as estimated from its historical data and the forecasted stock return were used for maximizing return with quadratic programming formulation in Markowitz model. In the models involving Fuzzy probability and possibility distributions, the future return was estimated using the similarity grade of past returns. In the interval coefficient models, future return was estimated as interval variable. The optimum portfolios of different models were widely divergent and DEA was used to identify the model giving the best portfolio with higher appraisal, both overall and by peers, and least Maverick behavior. Use of Signal to Noise ratio proved equally efficient for model discrimination and yielded identical results.

Portfolio Selection Models and Their Discrimination

2013 ◽  
pp. 170-195
Author(s):  
Satadal Ghosh ◽  
Sujit Kumar Majumdar
Keyword(s):  
Portfolio Selection ◽  
Portfolio Management ◽  
Stock Return ◽  
Signal To Noise Ratio ◽  
Selection Models ◽  
Markowitz Model ◽  
Risk Return ◽  
Future Return ◽  
Possibility Distributions ◽  
Portfolio Selection Model

The stochastic nature of financial markets is a barrier for successful portfolio management. Besides traditional Markowitz’s model, many other portfolio selection models in Bayesian and Non-Bayesian frameworks have been developed. Starting with the basic Markowitz model, several cardinal models are used to find optimum portfolios with select stock set. Having developed the regression model of the return of each stock with the market return, the unsystematic part of the uncertainty was used to find the optimum portfolio and efficient risk–return frontier within each portfolio selection model. The average stock return as estimated from its historical data and the forecasted stock return were used for maximizing return with quadratic programming formulation in Markowitz model. In the models involving Fuzzy probability and possibility distributions, the future return was estimated using the similarity grade of past returns. In the interval coefficient models, future return was estimated as interval variable. The optimum portfolios of different models were widely divergent and DEA was used to identify the model giving the best portfolio with higher appraisal, both overall and by peers, and least Maverick behavior. Use of Signal to Noise ratio proved equally efficient for model discrimination and yielded identical results.

Joint tails impact in stochastic volatility portfolio selection models

2020 ◽  
Vol 292 (2) ◽  
pp. 833-848
Author(s):  
Marco Bonomelli ◽  
Rosella Giacometti ◽  
Sergio Ortobelli Lozza
Keyword(s):  
Stochastic Volatility ◽  
Portfolio Selection ◽  
Selection Models

scholarly journals On Imposing ESG Constraints of Portfolio Selection for Sustainable Investment and Comparing the Efficient Frontiers in the Weight Space

SAGE Open ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 215824402097507
Author(s):  
Yue Qi ◽  
Xiaolin Li
Keyword(s):  
Portfolio Selection ◽  
Efficient Frontier ◽  
Weight Space ◽  
Efficient Frontiers ◽  
Risk Return ◽  
Screening Strategies ◽  
Dow Jones Industrial Average ◽  
Sustainable Investment ◽  
Selection For ◽  
Portfolio Selection Model

Sustainable investment is typically fulfilled by screening of environmental, social, and governance (ESG); the screening strategies are practical and expedite sustainable-investment development. However, the strategies typically build portfolios by a list of good stocks and ignore portfolio completeness. Moreover, there has been limited literature to study the portfolio weights of sustainable investment in the weight space. In such an area, this article contributes to the literature as follows: We extend a conventional portfolio-selection model and impose ESG constraints. We analytically solve our model by computing the efficient frontier and prove that the frontier’s portfolio weights all lie on a ray (half line). By the ray structure, we prove that portfolio selection for sustainable investment and conventional portfolio selection fundamentally possess highly different portfolio weights. Overall, our aim is comparing the portfolio weights of sustainable portfolio selection and of conventional portfolio selection; the comparison result has been unknown until now. The result is important for sustainable investment because portfolio weights are the foundation of portfolio selection and investments. We sample the component stocks of Dow Jones Industrial Average Index from 2004 to 2013 and find that our efficient frontier and the conventional efficient frontier are quite similar. Therefore, in plain financial language, investors can still obtain risk-return performance similar to conventional portfolio selection after imposing strong ESG requirements, although the portfolio weights can be totally different. The result is both an endorsement and a reminder for sustainable investment.

Problems in the application of portfolio selection models

Omega ◽  
1976 ◽  
Vol 4 (6) ◽  
pp. 699-709 ◽  
Author(s):  
Stewart D Hodges
Keyword(s):  
Portfolio Selection ◽  
Selection Models

scholarly journals Maximization of utility and portfolio selection models

2017 ◽  
Vol 0 (11) ◽  
Author(s):  
João Francisco Neves ◽  
Patrícia Nunes da Silva ◽  
Carlos Frederico Fragoso de Barros e Vasconcellos
Keyword(s):  
Portfolio Selection ◽  
Selection Models
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