A hybrid grey MCDM approach for asset allocation: evidence from China’s Shanghai Stock Exchange
Abstract
Asset allocation is a critical concern for any investor in the financial market. This paper aims to prioritize five randomly selected firms from the top ten stocks by market capitalization of the Shanghai Stock Exchange (SSE) by opting for adequate financial procedures and practical criteria under uncertain conditions. Decision makers want not only the ranking order of stocks but also capital proportions to be allocated. Therefore, this study uses a hybrid multi-criteria decision-making (MCDM) approach comprising of an integrated analytic network process (ANP) and decision making trial and evaluation laboratory (DEMATEL) in a grey environment for optimal portfolio selection to provide both ranking and weighting information for decision makers. Results indicate that return, financial ratios, dividends, and risk are causal criteria group, which are the most influential determinants for obtaining high benefits with regards to stock portfolio selection in SSE. The free float of stocks is the least influencing criterion among all identified criteria of stock portfolio selection of SSE. The Industrial and Commercial Bank of China Ltd. stocks have the highest allocated proportion with the highest priority shown by investors and can be described as a suitable alternative. The practical implications of this research are that the approach, when applied, highlights how the grey system theory minimizes the uncertainties in all stages of decision-making of portfolio selection.
Keyword : asset allocation, grey MCDM, grey-ANP, grey-DEMATEL, Shanghai Stock Exchange, China
How to Cite
Atta Mills, E. F. E. ., Baafi, M. A. ., Amowine, N. ., & Zeng, K. . (2020). A hybrid grey MCDM approach for asset allocation: evidence from China’s Shanghai Stock Exchange. Journal of Business Economics and Management, 21(2), 446-472. https://doi.org/10.3846/jbem.2020.11967
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Abdel-Basset, M., Manogaran, G., Gamal, A., & Smarandache, F. (2018). A hybrid approach of neutrosophic sets and DEMATEL method for developing supplier selection criteria. Design Automation for Embedded Systems, 22(3), 257–278. https://doi.org/10.1007/s10617-018-9203-6
Ahmed, N., & Bassiouny, A. (2018). The effects of index changes on stock trading: Evidence from the EGX. Review of Economics & Finance, 11, 55–66.
Asan, U., Soyer, A., & Serdarasan, S. (2012) A fuzzy analytic network process approach. In C. Kahraman (Ed.), Computational intelligence systems in industrial engineering. Atlantis Computational Intelligence Systems (Vol. 6, pp. 155–179). Atlantis Press. https://doi.org/10.2991/978-94-91216-77-0_8
Atta Mills, E. F. E., Yan, D., Yu, B., & Wei, X. (2016). Research on regularized mean–variance portfolio selection strategy with modified Roy safety-first principle. SpringerPlus, 5(1), 919. https://doi.org/10.1186/s40064-016-2621-7
Atta Mills, E. F. E., Yu, B., & Yu, J. (2017). Scaled and stable mean-variance-EVaR portfolio selection strategy with proportional transaction costs. Journal of Business Economics and Management, 18(4), 561–584. https://doi.org/10.3846/16111699.2017.1342272
Bai, C., & Sarkis, J. (2011). Evaluating supplier development programs with a grey based rough set methodology. Expert Systems with Applications, 38(11), 13505–13517. https://doi.org/10.1016/j.eswa.2011.02.137
Capelle-Blancard, G. (2017). Curbing the growth of stock trading? Order-to-trade ratios and financial transaction taxes. Journal of International Financial Markets, Institutions and Money, 49, 48–73. https://doi.org/10.1016/j.intfin.2017.02.004
Charouz, J., & Ramík, J. (2010). A multicriteria decision making at portfolio management. E+M Ekonomie a Management, (2), 44–52.
Cui, L., Chan, H. K., Zhou, Y., Dai, J., & Lim, J. J. (2019). Exploring critical factors of green business failure based on Grey-Decision Making Trial and Evaluation Laboratory (DEMATEL). Journal of Business Research, 98, 450–461. https://doi.org/10.1016/j.jbusres.2018.03.031
Cuthbertson, K., & Nitzsche, D. (2013). Performance, stock selection and market timing of the German equity mutual fund industry. Journal of Empirical Finance, 21, 86–101. https://doi.org/10.1016/j.jempfin.2012.12.002
Deng, J. L. (1982). Control problems of grey systems. Systems and Control Letters, 1(5), 288–294. https://doi.org/10.1016/S0167-6911(82)80025-X
Devpura, N., Narayan, P. K., & Sharma, S. S. (2018). Is stock return predictability time-varying? Journal of International Financial Markets, Institutions and Money, 52, 152–172. https://doi.org/10.1016/j.intfin.2017.06.001
Ding, Y., & Lu, Z. (2016). The optimal portfolios based on a modified safety-first rule with risk-free saving. Journal of Industrial & Management Optimization, 12(1), 83–102. https://doi.org/10.3934/jimo.2016.12.83
Dou, Y., Zhu, Q., & Sarkis, J. (2014). Evaluating green supplier development programs with a greyanalytical network process-based methodology. European Journal of Operational Research, 233(2), 420–431. https://doi.org/10.1016/j.ejor.2013.03.004
El-Nader, G. (2018). Stock liquidity and free float: Evidence from the UK. Managerial Finance, 44(10), 1227–1236. https://doi.org/10.1108/MF-12-2017-0494
Firth, M., Gao, J., Shen, J., & Zhang, Y. (2016). Institutional stock ownership and firms’ cash dividend policies: Evidence from China. Journal of Banking & Finance, 65, 91–107. https://doi.org/10.1016/j.jbankfin.2016.01.009
Gabus, A., & Fontela, E. (1972). World problems, an invitation to further thought within the framework of DEMATEL. Battelle Geneva Research Center. Geneva, Switzerland.
Garcia-Lopez, F. J., Batyrshin, I., & Gelbukh, A. (2018). Analysis of relationships between tweets and stock market trends. Journal of Intelligent & Fuzzy Systems, 34(5), 3337–3347. https://doi.org/10.3233/JIFS-169515
Gilbert, T., Scotti, C., Strasser, G., & Vega, C. (2017). Is the intrinsic value of a macroeconomic news announcement related to its asset price impact? Journal of Monetary Economics, 92, 78–95. https://doi.org/10.1016/j.jmoneco.2017.09.008
Gupta, P., Mehlawat, M. K., & Saxena, A. (2013). Hybrid optimization models of portfolio selection involving financial and ethical considerations. Knowledge-Based Systems, 37, 318–337. https://doi.org/10.1016/j.knosys.2012.08.014
Haleem, A., Khan, S., & Khan, M. I. (2019). Traceability implementation in food supply chain: A greyDEMATEL approach. Information Processing in Agriculture, 6(3), 335–348. https://doi.org/10.1016/j.inpa.2019.01.003
He, Z., He, L., & Wen, F. (2019). Risk compensation and market returns: The role of investor sentiment in the stock market. Emerging Markets Finance and Trade, 55(3), 704–718. https://doi.org/10.1080/1540496X.2018.1460724
Ho, W. R. J., Tsai, C. L., Tzeng, G. H., & Fang, S. K. (2011). Combined DEMATEL technique with a novel MCDM model for exploring portfolio selection based on CAPM. Expert Systems with Applications, 38(1), 16–25. https://doi.org/10.1016/j.eswa.2010.05.058
Huang, D., Zhu, S. S., Fabozzi, F. J., & Fukushima, M. (2008). Portfolio selection with uncertain exit time: A robust CVaR approach. Journal of Economic Dynamics and Control, 32(2), 594–623. https://doi.org/10.1016/j.jedc.2007.03.003
Jakob, K., & Whitby, R. (2017). The impact of nominal stock price on ex-dividend price responses. Review of Quantitative Finance and Accounting, 48(4), 939–953. https://doi.org/10.1007/s11156-016-0574-0
Karpavičius, S., & Yu, F. (2018). Dividend premium: Are dividend-paying stocks worth more? International Review of Financial Analysis, 56, 112–126. https://doi.org/10.1016/j.irfa.2018.01.004
Kaur, J., Sidhu, R., Awasthi, A., Chauhan, S., & Goyal, S. (2018). A DEMATEL based approach for investigating barriers in green supply chain management in Canadian manufacturing firms. International Journal of Production Research, 56(1–2), 312–332. https://doi.org/10.1080/00207543.2017.1395522
Kellerer, H., Mansini, R., & Speranza, M. G. (2000). Selecting portfolios with fixed costs and minimum transaction lots. Annals of Operations Research, 99(1–4), 287–304. https://doi.org/10.1023/A:1019279918596
Kelly, B. T., Pruitt, S., & Su, Y. (2019). Characteristics are covariances: A unified model of risk and return. Journal of Financial Economics, 134(3), 501–524. https://doi.org/10.1016/j.jfineco.2019.05.001
Leung, L. C., Hui, Y. V., & Zheng, M. (2003). Analysis of compatibility between interdependent matrices in ANP. Journal of the Operational Research Society, 54(7), 758–768. https://doi.org/10.1057/palgrave.jors.2601569
Li, Y., & Mathiyazhagan, K. (2018). Application of DEMATEL approach to identify the influential indicators towards sustainable supply chain adoption in the auto components manufacturing sector. Journal of Cleaner Production, 172, 2931–2941. https://doi.org/10.1016/j.jclepro.2017.11.120
Lin, R. J. (2013). Using fuzzy DEMATEL to evaluate the green supply chain management practices. Journal of Cleaner Production, 40, 32–39. https://doi.org/10.1016/j.jclepro.2011.06.010
Liu, J., & Qiao, J. Z. (2014). A grey rough set model for evaluation and selection of software cost estimation methods. Grey Systems: Theory and Application, 4(1), 3–12. https://doi.org/10.1108/GS-08-2013-0016
Luthra, S., Govindan, K., Kharb, R. K., & Mangla, S. K. (2016). Evaluating the enablers in solar power developments in the current scenario using fuzzy DEMATEL: An Indian perspective. Renewable and Sustainable Energy Reviews, 63, 379–397. https://doi.org/10.1016/j.rser.2016.04.041
Mandic, K., Delibasic, B., Knezevic, S., & Benkovic, S. (2014). Analysis of the financial parameters of Serbian banks through the application of the fuzzy AHP and TOPSIS methods. Economic Modelling, 43, 30–37. https://doi.org/10.1016/j.econmod.2014.07.036
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77–91. https://doi.org/10.1111/j.1540-6261.1952.tb01525.x
Opricovic, S., & Tzeng, G. H. (2003). Defuzzification within a multicriteria decision model. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 11(05), 635–652. https://doi.org/10.1142/S0218488503002387
Patel, J., Shah, S., Thakkar, P., & Kotecha, K. (2015). Predicting stock and stock price index movement using trend deterministic data preparation and machine learning techniques. Expert Systems with Applications, 42(1), 259–268. https://doi.org/10.1016/j.eswa.2014.07.040
Pourjavad, E., & Shahin, A. (2018). Hybrid performance evaluation of sustainable service and manufacturing supply chain management: An integrated approach of fuzzy dematel and fuzzy inference system. Intelligent Systems in Accounting, Finance and Management, 25(3), 134–147. https://doi.org/10.1002/isaf.1431
Rahimnia, F., Moghadasian, M., & Mashreghi, E. (2011). Application of grey theory approach to evaluation of organizational vision. Grey Systems: Theory and Application, 1(1), 33–46. https://doi.org/10.1108/20439371111106713
Rezaeian, J., & Akbari, F. (2015). Stock portfolio selection using a hybrid fuzzy approach: A case study in Tehran Stock Exchange. International Journal of Operational Research, 22(4), 423–453. https://doi.org/10.1504/IJOR.2015.068560
Roy, A. D. (1952). Safety first and the holding of assets. Econometrica, 20(3), 431–449. https://doi.org/10.2307/1907413
Saaty, T. L. (1990). How to make a decision: the analytic hierarchy process. European Journal of Operational Research, 48(1), 9–26. https://doi.org/10.1016/0377-2217(90)90057-I
Saaty, T. L. (1996). Decision making with dependence and feedback: The Analytic Network Process (Vol. 4922). RWS Publications (accessed 18 December 2018). https://ci.nii.ac.jp/naid/10018484540/
Saaty, T. L. (1980). The analytic hierarchy process: Planning, priority setting, resources allocation. McGraw-Hill.
Seçme, N. Y., Bayrakdaroğlu, A., & Kahraman, C. (2009). Fuzzy performance evaluation in Turkish banking sector using analytic hierarchy process and TOPSIS. Expert Systems with Applications, 36(9), 11699–11709. https://doi.org/10.1016/j.eswa.2009.03.013
Shanghai Stock Exchange. (2019). SSE Monthly Market Statistics. http://english2019.sse.com.cn/indices/publications/monthly/
Simaan, M., Simaan, Y., & Tang, Y. (2018). Estimation error in mean returns and the mean-variance efficient frontier. International Review of Economics & Finance, 56, 109–124. https://doi.org/10.1016/j.iref.2017.10.019
Tian, G., Liu, X., Zhang, M., Yang, Y., Zhang, H., Lin, Y., Ma, F., Wang, X., Qu, T., & Li, Z. (2019). Selection of take-back pattern of vehicle reverse logistics in China via Grey-DEMATEL and FuzzyVIKOR combined method. Journal of Cleaner Production, 220, 1088–1100. https://doi.org/10.1016/j.jclepro.2019.01.086
Vercher, E., Bermúdez, J. D., & Segura, J. V. (2007). Fuzzy portfolio optimization under downside risk measures. Fuzzy Sets and Systems, 158(7), 769–782. https://doi.org/10.1016/j.fss.2006.10.026
Wang, X. T., Li, Z., & Zhuang, L. (2017). Risk preference, option pricing and portfolio hedging with proportional transaction costs. Chaos, Solitons & Fractals, 95, 111–130. https://doi.org/10.1016/j.chaos.2016.12.010
Wu, S. I., & Hung, J. M. (2008). A performance evaluation model of CRM on non-profit organisations. Total Quality Management, 19(4), 321–342. https://doi.org/10.1080/14783360701591978
Xia, X., Govindan, K., & Zhu, Q. (2015). Analyzing internal barriers for automotive parts remanufacturers in China using grey-DEMATEL approach. Journal of Cleaner Production, 87, 811–825. https://doi.org/10.1016/j.jclepro.2014.09.044
Zhu, J. (2017). Optimal financing and dividend distribution with transaction costs in the case of restricted dividend rates. ASTIN Bulletin: The Journal of the IAA, 47(1), 239–268. https://doi.org/10.1017/asb.2016.29
Ahmed, N., & Bassiouny, A. (2018). The effects of index changes on stock trading: Evidence from the EGX. Review of Economics & Finance, 11, 55–66.
Asan, U., Soyer, A., & Serdarasan, S. (2012) A fuzzy analytic network process approach. In C. Kahraman (Ed.), Computational intelligence systems in industrial engineering. Atlantis Computational Intelligence Systems (Vol. 6, pp. 155–179). Atlantis Press. https://doi.org/10.2991/978-94-91216-77-0_8
Atta Mills, E. F. E., Yan, D., Yu, B., & Wei, X. (2016). Research on regularized mean–variance portfolio selection strategy with modified Roy safety-first principle. SpringerPlus, 5(1), 919. https://doi.org/10.1186/s40064-016-2621-7
Atta Mills, E. F. E., Yu, B., & Yu, J. (2017). Scaled and stable mean-variance-EVaR portfolio selection strategy with proportional transaction costs. Journal of Business Economics and Management, 18(4), 561–584. https://doi.org/10.3846/16111699.2017.1342272
Bai, C., & Sarkis, J. (2011). Evaluating supplier development programs with a grey based rough set methodology. Expert Systems with Applications, 38(11), 13505–13517. https://doi.org/10.1016/j.eswa.2011.02.137
Capelle-Blancard, G. (2017). Curbing the growth of stock trading? Order-to-trade ratios and financial transaction taxes. Journal of International Financial Markets, Institutions and Money, 49, 48–73. https://doi.org/10.1016/j.intfin.2017.02.004
Charouz, J., & Ramík, J. (2010). A multicriteria decision making at portfolio management. E+M Ekonomie a Management, (2), 44–52.
Cui, L., Chan, H. K., Zhou, Y., Dai, J., & Lim, J. J. (2019). Exploring critical factors of green business failure based on Grey-Decision Making Trial and Evaluation Laboratory (DEMATEL). Journal of Business Research, 98, 450–461. https://doi.org/10.1016/j.jbusres.2018.03.031
Cuthbertson, K., & Nitzsche, D. (2013). Performance, stock selection and market timing of the German equity mutual fund industry. Journal of Empirical Finance, 21, 86–101. https://doi.org/10.1016/j.jempfin.2012.12.002
Deng, J. L. (1982). Control problems of grey systems. Systems and Control Letters, 1(5), 288–294. https://doi.org/10.1016/S0167-6911(82)80025-X
Devpura, N., Narayan, P. K., & Sharma, S. S. (2018). Is stock return predictability time-varying? Journal of International Financial Markets, Institutions and Money, 52, 152–172. https://doi.org/10.1016/j.intfin.2017.06.001
Ding, Y., & Lu, Z. (2016). The optimal portfolios based on a modified safety-first rule with risk-free saving. Journal of Industrial & Management Optimization, 12(1), 83–102. https://doi.org/10.3934/jimo.2016.12.83
Dou, Y., Zhu, Q., & Sarkis, J. (2014). Evaluating green supplier development programs with a greyanalytical network process-based methodology. European Journal of Operational Research, 233(2), 420–431. https://doi.org/10.1016/j.ejor.2013.03.004
El-Nader, G. (2018). Stock liquidity and free float: Evidence from the UK. Managerial Finance, 44(10), 1227–1236. https://doi.org/10.1108/MF-12-2017-0494
Firth, M., Gao, J., Shen, J., & Zhang, Y. (2016). Institutional stock ownership and firms’ cash dividend policies: Evidence from China. Journal of Banking & Finance, 65, 91–107. https://doi.org/10.1016/j.jbankfin.2016.01.009
Gabus, A., & Fontela, E. (1972). World problems, an invitation to further thought within the framework of DEMATEL. Battelle Geneva Research Center. Geneva, Switzerland.
Garcia-Lopez, F. J., Batyrshin, I., & Gelbukh, A. (2018). Analysis of relationships between tweets and stock market trends. Journal of Intelligent & Fuzzy Systems, 34(5), 3337–3347. https://doi.org/10.3233/JIFS-169515
Gilbert, T., Scotti, C., Strasser, G., & Vega, C. (2017). Is the intrinsic value of a macroeconomic news announcement related to its asset price impact? Journal of Monetary Economics, 92, 78–95. https://doi.org/10.1016/j.jmoneco.2017.09.008
Gupta, P., Mehlawat, M. K., & Saxena, A. (2013). Hybrid optimization models of portfolio selection involving financial and ethical considerations. Knowledge-Based Systems, 37, 318–337. https://doi.org/10.1016/j.knosys.2012.08.014
Haleem, A., Khan, S., & Khan, M. I. (2019). Traceability implementation in food supply chain: A greyDEMATEL approach. Information Processing in Agriculture, 6(3), 335–348. https://doi.org/10.1016/j.inpa.2019.01.003
He, Z., He, L., & Wen, F. (2019). Risk compensation and market returns: The role of investor sentiment in the stock market. Emerging Markets Finance and Trade, 55(3), 704–718. https://doi.org/10.1080/1540496X.2018.1460724
Ho, W. R. J., Tsai, C. L., Tzeng, G. H., & Fang, S. K. (2011). Combined DEMATEL technique with a novel MCDM model for exploring portfolio selection based on CAPM. Expert Systems with Applications, 38(1), 16–25. https://doi.org/10.1016/j.eswa.2010.05.058
Huang, D., Zhu, S. S., Fabozzi, F. J., & Fukushima, M. (2008). Portfolio selection with uncertain exit time: A robust CVaR approach. Journal of Economic Dynamics and Control, 32(2), 594–623. https://doi.org/10.1016/j.jedc.2007.03.003
Jakob, K., & Whitby, R. (2017). The impact of nominal stock price on ex-dividend price responses. Review of Quantitative Finance and Accounting, 48(4), 939–953. https://doi.org/10.1007/s11156-016-0574-0
Karpavičius, S., & Yu, F. (2018). Dividend premium: Are dividend-paying stocks worth more? International Review of Financial Analysis, 56, 112–126. https://doi.org/10.1016/j.irfa.2018.01.004
Kaur, J., Sidhu, R., Awasthi, A., Chauhan, S., & Goyal, S. (2018). A DEMATEL based approach for investigating barriers in green supply chain management in Canadian manufacturing firms. International Journal of Production Research, 56(1–2), 312–332. https://doi.org/10.1080/00207543.2017.1395522
Kellerer, H., Mansini, R., & Speranza, M. G. (2000). Selecting portfolios with fixed costs and minimum transaction lots. Annals of Operations Research, 99(1–4), 287–304. https://doi.org/10.1023/A:1019279918596
Kelly, B. T., Pruitt, S., & Su, Y. (2019). Characteristics are covariances: A unified model of risk and return. Journal of Financial Economics, 134(3), 501–524. https://doi.org/10.1016/j.jfineco.2019.05.001
Leung, L. C., Hui, Y. V., & Zheng, M. (2003). Analysis of compatibility between interdependent matrices in ANP. Journal of the Operational Research Society, 54(7), 758–768. https://doi.org/10.1057/palgrave.jors.2601569
Li, Y., & Mathiyazhagan, K. (2018). Application of DEMATEL approach to identify the influential indicators towards sustainable supply chain adoption in the auto components manufacturing sector. Journal of Cleaner Production, 172, 2931–2941. https://doi.org/10.1016/j.jclepro.2017.11.120
Lin, R. J. (2013). Using fuzzy DEMATEL to evaluate the green supply chain management practices. Journal of Cleaner Production, 40, 32–39. https://doi.org/10.1016/j.jclepro.2011.06.010
Liu, J., & Qiao, J. Z. (2014). A grey rough set model for evaluation and selection of software cost estimation methods. Grey Systems: Theory and Application, 4(1), 3–12. https://doi.org/10.1108/GS-08-2013-0016
Luthra, S., Govindan, K., Kharb, R. K., & Mangla, S. K. (2016). Evaluating the enablers in solar power developments in the current scenario using fuzzy DEMATEL: An Indian perspective. Renewable and Sustainable Energy Reviews, 63, 379–397. https://doi.org/10.1016/j.rser.2016.04.041
Mandic, K., Delibasic, B., Knezevic, S., & Benkovic, S. (2014). Analysis of the financial parameters of Serbian banks through the application of the fuzzy AHP and TOPSIS methods. Economic Modelling, 43, 30–37. https://doi.org/10.1016/j.econmod.2014.07.036
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77–91. https://doi.org/10.1111/j.1540-6261.1952.tb01525.x
Opricovic, S., & Tzeng, G. H. (2003). Defuzzification within a multicriteria decision model. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 11(05), 635–652. https://doi.org/10.1142/S0218488503002387
Patel, J., Shah, S., Thakkar, P., & Kotecha, K. (2015). Predicting stock and stock price index movement using trend deterministic data preparation and machine learning techniques. Expert Systems with Applications, 42(1), 259–268. https://doi.org/10.1016/j.eswa.2014.07.040
Pourjavad, E., & Shahin, A. (2018). Hybrid performance evaluation of sustainable service and manufacturing supply chain management: An integrated approach of fuzzy dematel and fuzzy inference system. Intelligent Systems in Accounting, Finance and Management, 25(3), 134–147. https://doi.org/10.1002/isaf.1431
Rahimnia, F., Moghadasian, M., & Mashreghi, E. (2011). Application of grey theory approach to evaluation of organizational vision. Grey Systems: Theory and Application, 1(1), 33–46. https://doi.org/10.1108/20439371111106713
Rezaeian, J., & Akbari, F. (2015). Stock portfolio selection using a hybrid fuzzy approach: A case study in Tehran Stock Exchange. International Journal of Operational Research, 22(4), 423–453. https://doi.org/10.1504/IJOR.2015.068560
Roy, A. D. (1952). Safety first and the holding of assets. Econometrica, 20(3), 431–449. https://doi.org/10.2307/1907413
Saaty, T. L. (1990). How to make a decision: the analytic hierarchy process. European Journal of Operational Research, 48(1), 9–26. https://doi.org/10.1016/0377-2217(90)90057-I
Saaty, T. L. (1996). Decision making with dependence and feedback: The Analytic Network Process (Vol. 4922). RWS Publications (accessed 18 December 2018). https://ci.nii.ac.jp/naid/10018484540/
Saaty, T. L. (1980). The analytic hierarchy process: Planning, priority setting, resources allocation. McGraw-Hill.
Seçme, N. Y., Bayrakdaroğlu, A., & Kahraman, C. (2009). Fuzzy performance evaluation in Turkish banking sector using analytic hierarchy process and TOPSIS. Expert Systems with Applications, 36(9), 11699–11709. https://doi.org/10.1016/j.eswa.2009.03.013
Shanghai Stock Exchange. (2019). SSE Monthly Market Statistics. http://english2019.sse.com.cn/indices/publications/monthly/
Simaan, M., Simaan, Y., & Tang, Y. (2018). Estimation error in mean returns and the mean-variance efficient frontier. International Review of Economics & Finance, 56, 109–124. https://doi.org/10.1016/j.iref.2017.10.019
Tian, G., Liu, X., Zhang, M., Yang, Y., Zhang, H., Lin, Y., Ma, F., Wang, X., Qu, T., & Li, Z. (2019). Selection of take-back pattern of vehicle reverse logistics in China via Grey-DEMATEL and FuzzyVIKOR combined method. Journal of Cleaner Production, 220, 1088–1100. https://doi.org/10.1016/j.jclepro.2019.01.086
Vercher, E., Bermúdez, J. D., & Segura, J. V. (2007). Fuzzy portfolio optimization under downside risk measures. Fuzzy Sets and Systems, 158(7), 769–782. https://doi.org/10.1016/j.fss.2006.10.026
Wang, X. T., Li, Z., & Zhuang, L. (2017). Risk preference, option pricing and portfolio hedging with proportional transaction costs. Chaos, Solitons & Fractals, 95, 111–130. https://doi.org/10.1016/j.chaos.2016.12.010
Wu, S. I., & Hung, J. M. (2008). A performance evaluation model of CRM on non-profit organisations. Total Quality Management, 19(4), 321–342. https://doi.org/10.1080/14783360701591978
Xia, X., Govindan, K., & Zhu, Q. (2015). Analyzing internal barriers for automotive parts remanufacturers in China using grey-DEMATEL approach. Journal of Cleaner Production, 87, 811–825. https://doi.org/10.1016/j.jclepro.2014.09.044
Zhu, J. (2017). Optimal financing and dividend distribution with transaction costs in the case of restricted dividend rates. ASTIN Bulletin: The Journal of the IAA, 47(1), 239–268. https://doi.org/10.1017/asb.2016.29