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International Econometric Conference of Vietnam

ECONVN 2018: Econometrics for Financial Applications pp 953–986Cite as

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

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 760))

Abstract

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.

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Authors and Affiliations

  1. Faculty of Finance, Banking University of Ho Chi Minh City, Ho Chi Minh City, Vietnam

    Toan Luu Duc Huynh, Sang Phu Nguyen & Duy Duong

Authors
  1. Toan Luu Duc Huynh
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  2. Sang Phu Nguyen
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  3. Duy Duong
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Corresponding author

Correspondence to Toan Luu Duc Huynh .

Editor information

Editors and Affiliations

  1. Banking University HCMC, Ho Chi Minh City, Vietnam

    Ly H. Anh

  2. Banking University HCMC, Ho Chi Minh City, Vietnam

    Le Si Dong

  3. Computer Science Department, University of Texas at El Paso, El Paso, Texas, USA

    Vladik Kreinovich

  4. Banking University HCMC, Ho Chi Minh City, Vietnam

    Nguyen Ngoc Thach

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Huynh, T.L.D., Nguyen, S.P., Duong, D. (2018). Pricing Assets with Higher Co-moments and Value-at-Risk by Quantile Regression Approach: Evidence from Vietnam Stock Market. In: Anh, L., Dong, L., Kreinovich, V., Thach, N. (eds) Econometrics for Financial Applications. ECONVN 2018. Studies in Computational Intelligence, vol 760. Springer, Cham. https://doi.org/10.1007/978-3-319-73150-6_70

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  • DOI: https://doi.org/10.1007/978-3-319-73150-6_70

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73149-0

  • Online ISBN: 978-3-319-73150-6

  • eBook Packages: EngineeringEngineering (R0)

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