Các tham số bậc cao và lợi nhuận tài sản: bằng chứng từ các thị trường cổ phiếu mới nổi

Springer Science and Business Media LLC - Tập 297 - Trang 323-340 - 2020
Xuan Vinh Vo1, Thi Tuan Anh Tran2
1Institute of Business Research and CFVG Ho Chi Minh City, University of Economics Ho Chi Minh City, Ho Chi Minh City, Vietnam
2University of Economics Ho Chi Minh City, Ho Chi Minh City, Vietnam

Tóm tắt

Bài báo này xem xét vai trò của đồng độ lệch (co-skewness) và đồng độ nhọn (co-kurtosis) trong việc giải thích lợi nhuận vượt trội của danh mục đầu tư, sử dụng các phương pháp hồi quy chuỗi thời gian và hồi quy chéo Fama–Macbeth trong bối cảnh của một thị trường mới nổi. Mẫu nghiên cứu bao gồm các công ty niêm yết trên thị trường chứng khoán Việt Nam trong giai đoạn từ tháng 9 năm 2011 đến tháng 12 năm 2016. Bài viết cho thấy đồng độ lệch và đồng độ nhọn không quan trọng trong việc giải thích lợi nhuận cổ phiếu trên thị trường chứng khoán Việt Nam. Quan trọng hơn, chúng tôi nhận thấy rằng thị phần rủi ro (market risk premium) là yếu tố quan trọng nhất, trong khi các yếu tố phổ biến khác như SMB, HML và UMD có tác động nhỏ đến lợi nhuận cổ phiếu. Phát hiện này là rất quan trọng trong việc xác định các yếu tố ảnh hưởng đáng kể đến lợi nhuận cổ phiếu trên các thị trường cổ phiếu mới nổi. Bài báo cũng hỗ trợ giả thuyết rằng các phát hiện từ các thị trường phát triển có thể không thể được tổng quát hóa vào bối cảnh của các thị trường mới nổi. Phát hiện này có những ảnh hưởng trực tiếp đến phân tích danh mục đầu tư và quản lý rủi ro.

Từ khóa

#đồng độ lệch #đồng độ nhọn #lợi nhuận cổ phiếu #thị trường chứng khoán mới nổi #quản lý rủi ro

Tài liệu tham khảo

Andersen, T. G., Bollerslev, T., Diebold, F. X., & Ebens, H. (2001). The distribution of realized stock return volatility. Journal of Financial Economics, 61(1), 43–76. Batten, J. A., & Vo, X. V. (2014). Liquidity and return relationships in an emerging market. Emerging Markets Finance and Trade, 50(1), 5–21. Batten, J. A., & Vo, X. V. (2015). Foreign ownership in emerging stock markets. Journal of Multinational Financial Management, 32, 15–24. Berk, J. B., & Van Binsbergen, J. H. (2016). Assessing asset pricing models using revealed preference. Journal of Financial Economics, 119(1), 1–23. Buckle, M., Chen, J., & Williams, J. M. (2016). Realised higher moments: Theory and practice. The European Journal of Finance, 22(13), 1272–1291. Bui, T. M. H., Vo, X. V., & Bui, D. T. (2018). Gender inequality and FDI: Empirical evidence from developing Asia–Pacific countries. Eurasian Economic Review, 8(3), 393–416. https://doi.org/10.1007/s40822-018-0097-1. Cakici, N., Fabozzi, F. J., & Tan, S. (2013). Size, value, and momentum in emerging market stock returns. Emerging Markets Review, 16, 46–65. Choi, P., & Nam, K. (2008). Asymmetric and leptokurtic distribution for heteroscedastic asset returns: The SU-normal distribution. Journal of Empirical Finance, 15(1), 41–63. Cvitanić, J., Polimenis, V., & Zapatero, F. (2008). Optimal portfolio allocation with higher moments. Annals of Finance, 4(1), 1–28. de Athayde, G. M., & Flôres, R. G. (2004). Finding a maximum skewness portfolio—A general solution to three-moments portfolio choice. Journal of Economic Dynamics and Control, 28(7), 1335–1352. Do, H. X., Brooks, R., Treepongkaruna, S., & Wu, E. (2016). Stock and currency market linkages: New evidence from realized spillovers in higher moments. International Review of Economics & Finance, 42, 167–185. Fama, E. (1965). The behavior of stock market prices. Journal of Business, 38, 34–105. Fama, E. F., & French, K. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3–56. Fama, E. F., & French, K. R. (1992). The cross-section of expected stock returns. The Journal of Finance, 47(2), 427–465. Fama, E. F., & French, K. R. (2017). International tests of a five-factor asset pricing model. Journal of Financial Economics, 123(3), 441–463. Fama, E. F., & MacBeth, J. D. (1973). Risk, return, and equilibrium: Empirical tests. The Journal of Political Economy, 81(3), 607–636. Fernández, C., & Steel, M. F. (1998). On Bayesian modeling of fat tails and skewness. Journal of the American Statistical Association, 93(441), 359–371. Friend, I., & Westerfield, R. (1980). Co-skewness and capital asset pricing. The Journal of Finance, 35, 897–914. Grigoletto, M., & Lisi, F. (2011). Practical implications of higher moments in risk management. Statistical Methods and Applications, 20(4), 487–506. Günay, S. (2017). Value at risk (VaR) analysis for fat tails and long memory in returns. Eurasian Economic Review, 7(2), 215–230. https://doi.org/10.1007/s40822-017-0067-z. Hansan, Z., & Kamil, A. (2014). Contribution of co-skewness and co-kurtosis of the higher moment CAPM for finding the technical efficiency. Economics Research International. https://doi.org/10.1155/2014/253527. Harvey, C. R., Liechty, J. C., Liechty, M. W., & Müller, P. (2010). Portfolio selection with higher moments. Quantitative Finance, 10(5), 469–485. He, T. T., Li, W. X., & Tang, G. Y. (2019). Foreign institutional investors and stock price synchronicity of Chinese listed firms: Further evidence. Eurasian Economic Review, 9(1), 107–120. Jondeau, E., & Rockinger, M. (2003). Conditional volatility, skewness, and kurtosis: Existence, persistence, and comovements. Journal of Economic dynamics and Control, 27(10), 1699–1737. Jondeau, E., & Rockinger, M. (2006). Optimal portfolio allocation under higher moments. European Financial Management, 12(1), 29–55. Kelly, B., & Jiang, H. (2014). Tail risk and asset prices. The Review of Financial Studies, 27(10), 2841–2871. Kostakis, A., Muhammad, K., & Siganos, A. (2012). Higher co-moments and asset pricing on London stock exchange. Journal of Banking & Finance, 36, 913–922. Kraus, A., & Litzenberger, R. (1976). Skewness preference and the valuation of risk assets. The Journal of Finance, 31, 1085–1100. Lambert, M., & Hubner, G. (2013). Comoment risk and stock returns. Journal of Empirical Finance, 23, 191–205. Lim, K. (1989). A new test of the three-moment capital asset pricing model. Journal of Financial and Quantitative Analysis, 24, 205–216. Linden, M. (2001). A model for stock return distribution. International Journal of Finance & Economics, 6(2), 159–169. Ling, X. (2017). Normality of stock returns with event time clocks. Accounting & Finance, 57(S1), 277–298. Lintner, J. (1965). The valuation of risk assets and the selection of risky investment in stock portfolios and capital budgets. Review of Economics and Statistics, 47, 13–37. Mandelbrot, B., & Taylor, H. (1967). On the distribution of stock price differences. Operations Research, 15(6), 1057–1062. Martellini, L., & Ziemann, V. (2009). Improved estimates of higher-order comoments and implications for portfolio selection. The Review of Financial Studies, 23(4), 1467–1502. McLean, R. D., & Pontiff, J. (2016). Does academic research destroy stock return predictability? The Journal of Finance, 71(1), 5–32. Mencía, J., & Sentana, E. (2009). Multivariate location–scale mixtures of normals and mean–variance–skewness portfolio allocation. Journal of Econometrics, 153(2), 105–121. Mossin, J. (1966). Equilibrium in a capital asset market. Econometrica: Journal of the econometric society, 34, 768–783. Officer, R. (1972). The distribution of stock returns. Journal of the American Statistical Association, 67, 807–812. Perez-Quiros, G., & Timmermann, A. (2001). Business cycle asymmetries in stock returns: Evidence from higher order moments and conditional densities. Journal of Econometrics, 103(1), 259–306. Pettengill, G., Sundaram, S., & Mathur, I. (1995). The conditional relation between beta and returns. Journal of Financial and Quantitative Analysis, 30, 101–116. Pradhan, R. P. (2018). Development of stock market and economic growth: The G-20 evidence. Eurasian Economic Review, 8(2), 161–181. https://doi.org/10.1007/s40822-018-0094-4. Richardson, M., & Smith, T. (1993). A test for multivariate normality in stock returns. Journal of Business, 66, 295–321. Rouwenhorst, K. G. (1999). Local return factors and turnover in emerging stock markets. The Journal of Finance, 54(4), 1439–1464. Rubinstein, M. (1973). The fundamental theorem of parameter preference and security valuation. Journal of Financial and Quantitative Analysis, 8, 61–69. Scott, R. C., & Horvath, P. A. (1980). On the direction of preference for moments of higher order than the variance. The Journal of Finance, 35(4), 915–919. Sharpe, W. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. The Journal of Finance, 19, 425–442. Taussig, R. D., Tobi, D., & Zwilling, M. (2019). The importance of timing in estimating beta. Eurasian Economic Review, 9(1), 61–70. Teplova, T., & Shutova, E. (2011). A higher moment downside framework for conditional and unconditional CAPM in the Russian stock market. Eurasian Economic Review, 1(2), 157–178. Vo, X. V. (2016a). Does institutional ownership increase stock return volatility? Evidence from Vietnam. International Review of Financial Analysis, 45, 54–61. Vo, X. V. (2016b). Finance in Vietnam: An overview. Afro-Asian Journal of Finance and Accounting, 6(3), 202–209. Vo, X. V. (2016c). Foreign investors and corporate risk taking behavior in an emerging market. Finance Research Letters, 18, 273–277. Vo, X. V. (2017). Do foreign investors improve stock price informativeness in emerging equity markets? Evidence from Vietnam. Research in International Business and Finance, 42, 986–991. Vo, X. V. (forthcoming). Foreign investors and stock price crash risk: Evidence from Vietnam. International Review of Finance. https://doi.org/10.1111/irfi.12248. Young, B., Christoffersen, P., & Jacobs, K. (2010). Market skewness risk and the cross-section of stock returns. Montreal: McGill University. Zaremba, A. (2016). Is there a low-risk anomaly across countries? Eurasian Economic Review, 6(1), 45–65.