This study examines emerging market(EM)local bonds from a portfolio risk perspective and suggests methodologies for risk evaluation,on which the literature is limited.Despite the growth of EM bond funds in recent year...This study examines emerging market(EM)local bonds from a portfolio risk perspective and suggests methodologies for risk evaluation,on which the literature is limited.Despite the growth of EM bond funds in recent years,comprehensive studies regarding this industry have been scarce.In light of this,203 different local bonds of EM countries—Indonesia,Brazil,India,South Africa,Mexico,and Turkey—are elaborated in terms of return,volatility,and cross-correlation features.This study focuses on an untouched field—long memory properties—and the application of fractional models to EM bond portfolios.Based on the outcomes of a dynamic conditional correlation and fractionally integrated generalized autoregressive conditional heteroscedasticity approach and related value at risk analysis,the study finds that fractional models are useful tools for risk management,as they deliver satisfactory empirical results for several static and dynamic versions of EM bond portfolios.展开更多
Correction to:Demirel and Unal Financial Innovation(2020)6:50 https://doi.org/10.1186/s40854-020-00203-3 After publication of this article(Demirel and Unal 2020),it is noticed that Table 7 contained an error.The head...Correction to:Demirel and Unal Financial Innovation(2020)6:50 https://doi.org/10.1186/s40854-020-00203-3 After publication of this article(Demirel and Unal 2020),it is noticed that Table 7 contained an error.The heading‘Long Term Bond Portfolio’should be replaced by two subheadings“MV-Optimal Portfolios Average(Short-Term)”and“MV-Optimal Portfolios Average(Long-Term)”.展开更多
文摘This study examines emerging market(EM)local bonds from a portfolio risk perspective and suggests methodologies for risk evaluation,on which the literature is limited.Despite the growth of EM bond funds in recent years,comprehensive studies regarding this industry have been scarce.In light of this,203 different local bonds of EM countries—Indonesia,Brazil,India,South Africa,Mexico,and Turkey—are elaborated in terms of return,volatility,and cross-correlation features.This study focuses on an untouched field—long memory properties—and the application of fractional models to EM bond portfolios.Based on the outcomes of a dynamic conditional correlation and fractionally integrated generalized autoregressive conditional heteroscedasticity approach and related value at risk analysis,the study finds that fractional models are useful tools for risk management,as they deliver satisfactory empirical results for several static and dynamic versions of EM bond portfolios.
文摘Correction to:Demirel and Unal Financial Innovation(2020)6:50 https://doi.org/10.1186/s40854-020-00203-3 After publication of this article(Demirel and Unal 2020),it is noticed that Table 7 contained an error.The heading‘Long Term Bond Portfolio’should be replaced by two subheadings“MV-Optimal Portfolios Average(Short-Term)”and“MV-Optimal Portfolios Average(Long-Term)”.
