The short-term and long-term trade-off between risk and return: chaos vs rationality
Abstract
This paper used the composite construction method proposed by Haugen (1999) and its application by Zhao and Wang (2010) for the Chinese stock market. Utilizing the Shanghai A-share market stocks data, this paper first selected the shares listed on the Shanghai Stock Exchange during January 1, 1997 to December 31, 2017. A portfolio was then built according to the mean variance model of portfolio structure, and simulation results were analysed using the Wilcoxon Signed Rank Test. The relationship between risk and return in the long and short term was explored. Results indicated no significant relationship between the risk and return of the stock portfolio in the short run, which reflects the complexity of the Chinese stock market. However, in the long run, the risk and return of the stock portfolios are positively correlated, which means that high returns are accompanied by high risks, indicating that the stock market will eventually return to rationality. In other words, the A-share stock market will eventually return to be value-driven and the short-term speculators would be outweighed by long-term value investors.
First published online 07 November 2019
Keyword : risk-return relationship, value investors, speculators, long-term rationality, short-term chaos, risk, returns
How to Cite
Liu, C., Shi, H., Wu, L., & Guo, M. (2020). The short-term and long-term trade-off between risk and return: chaos vs rationality. Journal of Business Economics and Management, 21(1), 23-43. https://doi.org/10.3846/jbem.2019.11349
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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ElBannan, M. (2015). The capital asset pricing model: an overview of the theory. International Journal of Economics and Finance, 7(1), 216-228. https://doi.org/10.5539/ijef.v7n1p216
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Hou, K., & Loh, R. (2016). Have we solved the idiosyncratic volatility puzzle. Journal of Financial Economics, 121(1), 167-194. https://doi.org/10.1016/j.jfineco.2016.02.013
Jagannathan, R., & Ma, T., & Zhang, J. (2019). A note on “Risk reduction in large portfolios: Why imposing the wrong constraints helps”. Journal of Finance, 74(5). https://doi.org/10.1111/jofi.12824
Jouini, E., & Napp, C. (2011). Unbiased disagreement in financial markets, waves of pessimism and the risk-return trade-off. Review of Finance, 15(3), 575-601. https://doi.org/10.1093/rof/rfq002
Lundblad, C. (2007). The risk return tradeoff in the long run: 1836–2003. Journal of Financial Economics, 85(1), 123-150. https://doi.org/10.1016/j.jfineco.2006.06.003
Li, B., & Wu, S. (2003). An empirical study of the effectiveness and applicability of CAPM – a test of Shanghai stock market. China Economic Studies, 2, 36-41.
Lins, K. V., Servaes, H., & Tamayo, A. (2017). Social capital, trust, and firm performance: the value of corporate social responsibility during the financial crisis. The Journal of Finance, 72, 1785-1824. https://doi.org/10.1111/jofi.12505
Livingstona, M., Poon, W. P. H., & Zhou, L. (2019). Are Chinese credit ratings relevant? A study of the Chinese bond market and credit rating industry. Journal of Banking & Finance, 87, 216-232. https://doi.org/10.1016/j.jbankfin.2017.09.020
Olivier, D. (2019). The effect of pro-environmental preferences on bond prices: Evidence from green bonds. Journal of Banking & Finance, 98, 39-60. https://doi.org/10.1016/j.jbankfin.2018.10.012
Rickett, L., & Datta, P. (2018). Beauty-contests in the age of financialization: information activism and retail investor behavior. Journal of Information Technology, 33(1), 31-49. https://doi.org/10.1057/s41265-016-0026-2
Saengchote, K. (2017). The low-risk anomaly: evidence from the Thai stock market. Asian Academy of Management Journal of Accounting and Finance, 13(1), 143-158. https://doi.org/10.21315/aamjaf2017.13.1.6
Shen, L. (2006). Empirical research on the relationship among portfolio size, risk and return of Shanghai securities market. Journal of University of Electronic Science and Technology of China, 6, 1-5.
Shi, Y., & Cheng, Y. (2006). Empirical study on risk and return of small and medium sized enterprises stock. Shandong Metallurgy, 28(1), 58-60.
Song, Z., Yang, J. & Li, C. (2004). Empirical study on the risk and return of securities market. China Soft Science, 3, 46-50.
Theodossiou, P., & Savva, CS. (2016). Skewness and the relation between risk and return. Management Science, 62(6), 1598-1609. https://doi.org/10.1287/mnsc.2015.2201
Wang, P. (2011). Study on the relationship between risk premium and volatility in stock market based on SV-M model. Business Review, 23(6), 54-60.
Wei, T. (2001). Further empirical study of risk measurement and portfolio structure. Nankai Economic Studies, 2, 3-6.
Wei, Y. (2009). Research on capital asset pricing model. Journal of Gansu Lianhe University (Natural Science Edition), 23(1), 37-41.
Wu, Ch., Zhao, J., & Wu, G. (2002). Income risk relationship and inertia analysis of China stock market. Journal of Mathematics in Practice and Theory, 32(4), 576-582.
Yadav, P. L., Han, S. H., & Rho, J. J. (2016). Impact of environmental performance on firm value for sustainable investment: evidence from large US firms. Business Strategy and the Environment, 25(6), 402-420. https://doi.org/10.1002/bse.1883
Yang, S. (2007). Mean variance model based on MATLAB and EXCEL. Yinshan Academic Journal, 21(2), 42-45.
Yusaku, N., & Sun, B. X. (2016). Intraday volatility and volume in Chinese stock index cash and futures markets: evidence from high frequency data. Journal of Industrial Engineering and Engineering Management, 30(2), 167-189.
Zhang, S. & Ma, G. (2000). Stock market risk, return and market efficiency: ARMA-ARCH-M model. The Journal of World Economy, 5, 19-28
Zhao, W. & Wang, R. (2010). A new method to study the relationship between stock market risk and income: a combined construction method based on Monte Carlo simulation sampling. Productivity Research, 6, 27-29.
Zhao, S., Yuan, D., & Ren, P. (2018). Volatility spill over effects between our country’s index futures and spot market – based on HAR-CAW model. Operations Research & Management Science, 7(1),153-159.
Zhou, X., & Chen, Y. (2008). The volatility relationship between Shanghai and Shenzhen stock markets. Research on Economics and Management, 8, 77-82.
Zhou, B., Hou, D., & Shao, Z. (2017). Research on the spillover effects between Chinese stock index futures market and stock market. Economic Review, 8, 37-49.
Zaremba, A. (2016). Is there a low-risk anomaly across countries? Eurasian Economic Review, 6(1), 45-65. https://doi.org/10.1007/s40822-015-0036-3
Barberis, B., Greenwood, R., Lawrence, J., & Shleifer, A. (2015). X-CAPM: An extrapolative capital asset pricing model. Journal of Financial Economics, 115(1), 1-24. https://doi.org/10.1016/j.jfineco.2014.08.007
Benlagha, N., & Chargui, S. (2017). Range-based and GARCH volatility estimation: Evidence from the French asset market. Global Finance Journal, 32, 149-165. https://doi.org/10.1016/j.gfj.2016.04.001
Baležentis, T., Štreimikienė, D., Melnikienė, R., & Yu, Z. (2017). Non-parametric analysis of yield risk in Lithuanian crop farming. Journal of Business Economics and Management, 18, 2017(3). https://doi.org/10.3846/16111699.2017.1322633
Butaru, F., Chen, Q., Clark, B., Das, S., Lo, A. W., & Siddiqu, A. (2016). Risk and risk management in the credit card industry. Journal of Banking & Finance, 72, 218-239. https://doi.org/10.1016/j.jbankfin.2016.07.015
Chan, K., Wang, J., & Wei, K. C. J. (2004). Underpricing and long-term performance of IPOs in China. Journal of Corporate Finance, 10(3), 409-430. https://doi.org/10.1016/S0929-1199(03)00023-3
Chen, Q., & Li, Z. (2008). Research of CAPM on liquidity adjustment in China. The Journal of Quantitative & Technical Economics, 25(6), 66-78.
Christensen, B. J., Nielsen, M. O., & Zhu, J. (2010). Long memory in stock market volatility and the volatility-in-mean effect: The FIEGARCH-M model. Journal of Empirical Finance, 17(3), 460-470. https://doi.org/10.1016/j.jempfin.2009.09.008
Ciarreta, A., Muniain, P., & Zarraga, A. (2017). Modeling and forecasting realized volatility in German–Austrian continuous intraday electricity prices. Journal of Forecasting, 36(6). https://doi.org/10.1002/for.2463
Cox, D. R., & Peterson, D. R. (1994). Stock returns following large one‐day declines: Evidence on short‐term reversals and longer‐term performance. Journal of Finance, 49(1), 255-267. https://doi.org/10.1111/j.1540-6261.1994.tb04428.x
Doojin, R. (2017). Comprehensive market microstructure model: considering the inventory holding costs. Journal of Business Economics and Management, 18(2), 183-201. https://doi.org/10.3846/16111699.2017.1286380
ElBannan, M. (2015). The capital asset pricing model: an overview of the theory. International Journal of Economics and Finance, 7(1), 216-228. https://doi.org/10.5539/ijef.v7n1p216
Fama, E. F., & French, K. R. (1992). The cross-section of expected stock returns. The Journal of Finance, 47(2), 427-465. https://doi.org/10.1111/j.1540-6261.1992.tb04398.x
Fan, X., & Du. D. (2017). The Spillover effect between CSI500 index futures market and the spot market: evidence from high frequency data in 2015. China Finance Review International, 7(2), 249-272. https://doi.org/10.1108/CFRI-08-2016-0103
Froot, K. A., Scharfstein, D. S., & Stein, J. C. (1992). Herd on the street: Informational inefficiencies in a market with short‐term speculation. Journal of Finance, 47(4), 1461-1484. https://doi.org/10.1111/j.1540-6261.1992.tb04665.x
Ghysels, E., Santa-Clara, P., & Valkanov, R. (2005). There is a risk-return trade-off after all. Journal of Financial Economics, 76(3), 509-548. https://doi.org/10.1016/j.jfineco.2004.03.008
Guo, C., & Ling, K. (2004). Statistical analysis of the relationship between risk and return in China stock market. Journal of Lanzhou University (Social Sciences), 32(6), 92-94.
Haugen, R. A. (1999). The new finance: the case against efficient markets contemporary issues in finance (pp. 97-103). Prentice Hall.
Hong, M., Ramchander, R., Wang, T., & Yang, D. (2017). Role of index futures on China’s stock markets: Evidence from price discovery and volatility spillover. Pacific-Basin Finance Journal, 44, 13-26. https://doi.org/10.1016/j.pacfin.2017.05.003
Hou, K., & Loh, R. (2016). Have we solved the idiosyncratic volatility puzzle. Journal of Financial Economics, 121(1), 167-194. https://doi.org/10.1016/j.jfineco.2016.02.013
Jagannathan, R., & Ma, T., & Zhang, J. (2019). A note on “Risk reduction in large portfolios: Why imposing the wrong constraints helps”. Journal of Finance, 74(5). https://doi.org/10.1111/jofi.12824
Jouini, E., & Napp, C. (2011). Unbiased disagreement in financial markets, waves of pessimism and the risk-return trade-off. Review of Finance, 15(3), 575-601. https://doi.org/10.1093/rof/rfq002
Lundblad, C. (2007). The risk return tradeoff in the long run: 1836–2003. Journal of Financial Economics, 85(1), 123-150. https://doi.org/10.1016/j.jfineco.2006.06.003
Li, B., & Wu, S. (2003). An empirical study of the effectiveness and applicability of CAPM – a test of Shanghai stock market. China Economic Studies, 2, 36-41.
Lins, K. V., Servaes, H., & Tamayo, A. (2017). Social capital, trust, and firm performance: the value of corporate social responsibility during the financial crisis. The Journal of Finance, 72, 1785-1824. https://doi.org/10.1111/jofi.12505
Livingstona, M., Poon, W. P. H., & Zhou, L. (2019). Are Chinese credit ratings relevant? A study of the Chinese bond market and credit rating industry. Journal of Banking & Finance, 87, 216-232. https://doi.org/10.1016/j.jbankfin.2017.09.020
Olivier, D. (2019). The effect of pro-environmental preferences on bond prices: Evidence from green bonds. Journal of Banking & Finance, 98, 39-60. https://doi.org/10.1016/j.jbankfin.2018.10.012
Rickett, L., & Datta, P. (2018). Beauty-contests in the age of financialization: information activism and retail investor behavior. Journal of Information Technology, 33(1), 31-49. https://doi.org/10.1057/s41265-016-0026-2
Saengchote, K. (2017). The low-risk anomaly: evidence from the Thai stock market. Asian Academy of Management Journal of Accounting and Finance, 13(1), 143-158. https://doi.org/10.21315/aamjaf2017.13.1.6
Shen, L. (2006). Empirical research on the relationship among portfolio size, risk and return of Shanghai securities market. Journal of University of Electronic Science and Technology of China, 6, 1-5.
Shi, Y., & Cheng, Y. (2006). Empirical study on risk and return of small and medium sized enterprises stock. Shandong Metallurgy, 28(1), 58-60.
Song, Z., Yang, J. & Li, C. (2004). Empirical study on the risk and return of securities market. China Soft Science, 3, 46-50.
Theodossiou, P., & Savva, CS. (2016). Skewness and the relation between risk and return. Management Science, 62(6), 1598-1609. https://doi.org/10.1287/mnsc.2015.2201
Wang, P. (2011). Study on the relationship between risk premium and volatility in stock market based on SV-M model. Business Review, 23(6), 54-60.
Wei, T. (2001). Further empirical study of risk measurement and portfolio structure. Nankai Economic Studies, 2, 3-6.
Wei, Y. (2009). Research on capital asset pricing model. Journal of Gansu Lianhe University (Natural Science Edition), 23(1), 37-41.
Wu, Ch., Zhao, J., & Wu, G. (2002). Income risk relationship and inertia analysis of China stock market. Journal of Mathematics in Practice and Theory, 32(4), 576-582.
Yadav, P. L., Han, S. H., & Rho, J. J. (2016). Impact of environmental performance on firm value for sustainable investment: evidence from large US firms. Business Strategy and the Environment, 25(6), 402-420. https://doi.org/10.1002/bse.1883
Yang, S. (2007). Mean variance model based on MATLAB and EXCEL. Yinshan Academic Journal, 21(2), 42-45.
Yusaku, N., & Sun, B. X. (2016). Intraday volatility and volume in Chinese stock index cash and futures markets: evidence from high frequency data. Journal of Industrial Engineering and Engineering Management, 30(2), 167-189.
Zhang, S. & Ma, G. (2000). Stock market risk, return and market efficiency: ARMA-ARCH-M model. The Journal of World Economy, 5, 19-28
Zhao, W. & Wang, R. (2010). A new method to study the relationship between stock market risk and income: a combined construction method based on Monte Carlo simulation sampling. Productivity Research, 6, 27-29.
Zhao, S., Yuan, D., & Ren, P. (2018). Volatility spill over effects between our country’s index futures and spot market – based on HAR-CAW model. Operations Research & Management Science, 7(1),153-159.
Zhou, X., & Chen, Y. (2008). The volatility relationship between Shanghai and Shenzhen stock markets. Research on Economics and Management, 8, 77-82.
Zhou, B., Hou, D., & Shao, Z. (2017). Research on the spillover effects between Chinese stock index futures market and stock market. Economic Review, 8, 37-49.
Zaremba, A. (2016). Is there a low-risk anomaly across countries? Eurasian Economic Review, 6(1), 45-65. https://doi.org/10.1007/s40822-015-0036-3