Pricing Assets with Higher Co-moments and Value-at-Risk by Quantile Regression Approach: Evidence from Vietnam Stock Market

  • Toan Luu Duc Huynh
  • Sang Phu Nguyen
  • Duy Duong
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 760)


This paper examines the role of higher co-moments of the shape of return distribution in capturing secondary data for 274 non-financial firms listed in the Vietnam Index, considered as one of the emerging stock markets, during the period from July 2006 to June 2016. We employ Fama-French model combined with higher co-moments, particularly co-skewness and co-kurtosis, and value-at-risk (VaR) to explain the return-generating process. Quantile regression is also used in descending order with the two methods of equally weighted and value-weighted portfolios. The findings show that investors could maximize their portfolio return by holding more stocks with the positive co-skewness and restricting the large co-kurtosis ones. It implies that in addition to co-momentum effects other determinants such as size, value and maximal value of losses also have a strong influence on stock return.


Co-skewness Co-kurtosis Fama and French factors Value-at-Risk Vietnam 


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Toan Luu Duc Huynh
    • 1
  • Sang Phu Nguyen
    • 1
  • Duy Duong
    • 1
  1. 1.Faculty of FinanceBanking University of Ho Chi Minh CityHo Chi Minh CityVietnam

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