基于前景云的不确定语言多准则国际股指投资群决策
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摘要
针对投资决策过程中语言评价值具有随机性及模糊性,以及投资者的决策容易受到其情绪的影响且不同投资者受到的影响程度不同,本文提出基于前景云的不确定语言多准则投资群决策方法,并将其运用在国际股指投资中。其中,前景理论模型用来刻画投资者情绪对决策的影响,而云模型用来刻画语言评价值模糊性和随机性之间的关联。更具体来说,论文首先解决传统文献云生成方法中云期望值超过论域或者无法区分语言评价标度等级等问题,然后构建了前景云模型并将该模型应用于多个专家共同进行的国际股指投资群决策。实证结果显示,该模型得出的决策结果比传统决策方法下的结果更直观、可靠,表现为决策依据不仅考虑方案的期望值大小及变动风险,而且还考虑了投资者情绪对决策的影响。由此可得出,本文所提出的模型更符合现实情景,也更能有效实现对投资群决策。
In view of the randomness and ambiguity of linguistic information in the process of investment decision,and the behavior of investors are easily affected by their sentiment at different degrees,this paper puts forward an uncertain-linguistic multi-criteria group investment decision based on the prospect-cloud model for international stock indices. In the method of decision,the prospect theory model can describe the influence of investment sentiment,while the cloud one can capture the association of ambiguity and randomness in linguistic evaluations.More specifically,after solving the problems that the cloud expectation exceeds the universe and the linguistic scale that cannot be distinguished in the existing cloud-generation methods,this paper proposes a prospect-cloud model and applies it to the empirical analysis for international stock-index investment decisions by group experts.The empirical result shows that the investment decision making based on the prospect-cloud model is more intuitive and reliable than the existing one. Since the former not only confers to the expectation,but also the risk of investment as well as investment sentiment. Thus,it can be concluded that our proposed model performs better in practice and is more effective to group decision of investment.
In view of the randomness and ambiguity of linguistic information in the process of investment decision,and the behavior of investors are easily affected by their sentiment at different degrees,this paper puts forward an uncertain-linguistic multi-criteria group investment decision based on the prospect-cloud model for international stock indices. In the method of decision,the prospect theory model can describe the influence of investment sentiment,while the cloud one can capture the association of ambiguity and randomness in linguistic evaluations.More specifically,after solving the problems that the cloud expectation exceeds the universe and the linguistic scale that cannot be distinguished in the existing cloud-generation methods,this paper proposes a prospect-cloud model and applies it to the empirical analysis for international stock-index investment decisions by group experts.The empirical result shows that the investment decision making based on the prospect-cloud model is more intuitive and reliable than the existing one. Since the former not only confers to the expectation,but also the risk of investment as well as investment sentiment. Thus,it can be concluded that our proposed model performs better in practice and is more effective to group decision of investment.
引文
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[18] Pang J F,Liang J Y,Song P. An adaptive consensus method for multi-attribute group decision making under uncertain linguistic environment[J]. Applied Soft Computing,2017,58:339-353.
[19] Peng H G,Zhang H Y,Wang J Q. Cloud decision support model for selecting hotels on Trip Advisor. com with probabilistic linguistic information[J]. International Journal of Hospitality Management, 2018, 68:124-138.
[20]文杏梓,罗新星,欧阳军林.基于决策者信任度的风险型混合多属性群决策方法[J].控制与决策,2014,29(03):481-486.
[21]糜万俊,戴跃伟.基于前景理论的风险型混合模糊多准则群决策[J].控制与决策,2017,32(07):1279-1285.
[22] Li D,Cheung D,Shi X M,Ng V. Uncertainty reasoning based on cloud models in controllers[J]. Computers&Mathematics with Applications, 1998, 35(3):99-123.
[23] Yang X,Yan L,Zeng L. How to handle uncertainties in AHP:the cloud delphi hierarchical analysis[J].Information Sciences,2013,222:384-404.
[24] Xu Z S. Uncertain linguistic aggregation operators based approach to multiple attribute group decision making under uncertain linguistic environment[J]. Information Sciences,2004,168(1-4):171-184.
[25] Herrera F,Martínez L. A 2-tuple fuzzy linguistic representation model for computing with words[J]. IEEE Trans on Fuzzy Systems,2000,8(6):746-752.
[26] Yager R R. OWA aggregation over a continuous interval argument with applications to decision making[J].IEEE Transactions on Systems,Man and Cybernetics,Part B(Cybernetics),2004,34(5):1952-1963.
[27] Opricovic S,Tzeng G H. Compromise solution by MCDM methods:a comparative analysis of VIKOR and TOPSIS[J]. European Journal of Operational Research,2004,(156):445-455.
[28]阎岩,唐振民,刘家银.基于不确定性分析的自主导航轨迹评测方法[J].机器人,2013,35(02):194-199.
[29]赵坤,高建伟,祁之强.基于前景理论及云模型风险型多准则决策方法[J].控制与决策,2015,30(03):395-402.
[30]邸凯昌,李德毅,李德仁.云理论及其在空间数据发掘和知识发现中的应用[J].中国图象图形学报,1999,4(11):32-37.
[31] Tversky A,Kahneman D. Advances in prospect theory:cumulative representation of uncertainty[J]. Journal of Risk and Uncertainty,1992,(5):297-323.
[32]鲍新中,肖明.基于粗糙集理论的证券投资决策[J].系统管理学报,2010,19(05):526-533.
[33] Weng Y, Gong P. Modeling spatial and temporal dependencies among global stock markets[J]. Expert Systems with Applications,2016,43:175-185.
[34]杨国亮.对外投资合作中的政治风险:现有研究的综述及其扩展[J].经济管理,2012,34(10):192-199.
[35]缪胜光,陈国宏,李美娟.基于云理论的福建省区域创新能力动态评价[J].中国管理科学,2011,19(SI):808-814.
[36]李晓广,张岩贵.我国股票市场与国际市场的联动性研究———对次贷危机时期样本的分析[J].国际金融研究,2008,(11):75-80.
[37]张兵,范致镇,李心丹.中美股票市场的联动性研究[J].经济研究,2010,(11):141-151.
[38] Fernández-Avilés G,Montero J,Orlov A G. Spatial modeling of stock market comovements[J]. Finance Research Letters,2012,9(4):202-212.
[39] Sun L,Najand M,Shen J. Stock return predictability and investor sentiment:a high-frequency perspective[J]. Journal of Banking&Finance, 2016, 73:147-164.
[40] Liang W. Sensitivity to investor sentiment and stock performance of open market share repurchases[J].Journal of Banking&Finance,2016,71:75-94.
[2]刘文革,周方召,肖园园.不完全契约与国际贸易:一个评述[J].经济研究,2016,(11):166-179.
[3] Chen G,Cheung W,Chu S,Xu L. Transshipment hub selection from a shipper’s and freight forwarder’s perspective[J]. Expert Systems with Applications,2017,83:396-404.
[4]黄世席.欧盟国际投资仲裁法庭制度的缘起与因应[J].法商研究,2016,(04):162-172.
[5]王威.论构建中国—东盟自贸区区域经济融合的国际投资问题[J].改革与战略,2015,31(01):105-110.
[6]翁东玲.国际货币体系变革与人民币的国际化[J].经济学家,2016,(12):45-51.
[7]余湄,谢海滨,高茜.国际投资中的汇率风险对冲问题研究[J].系统工程理论与实践,2014,(S1):67-74.
[8] Chatsanga N,Parkes A J. International portfolio optimisation with integrated currency overlay costs and constraints[J]. Expert Systems with Applications,2017,83:333-349.
[9]王坚强,刘淘.基于综合云的不确定语言多准则群决策方法[J].控制与决策,2012,27(08):1185-1190.
[10]王坚强,吴建文.基于区间灰色不确定语言的多准则决策方法[J].中国管理科学,2010,18(03):107-111.
[11] Yunusoglu M G,Selim H. A fuzzy rule based expert system for stock evaluation and portfolio construction:an application to istanbul stock exchange[J]. Expert Systems with Applications,2013,40(3):908-920.
[12] Meng F Y,Chen X H. The symmetrical interval intuitionistic uncertain linguistic operators and their application to decision making[J]. Computers&Industrial Engineering,2016,98:531-542.
[13] Zhang H Y,Peng H G,Wang J,Wang J Q. An extended outranking approach for multi-criteria decisionmaking problems with linguistic intuitionistic fuzzy numbers[J]. Applied Soft Computing,2017,59:462-474.
[14] Liu P D,Chu Y,Li Y. The multi-attribute group decision-making method based on the interval grey uncertain linguistic generalized hybrid averaging operator[J].Neural Computing and Applications,2015,26(6):1395-1405.
[15]彭勃,叶春明.基于不确定纯语言混合调和平均算子的多属性群决策方法[J].中国管理科学,2015,23(02):131-138.
[16]李海涛,罗党,韦保磊.不确定语言评价信息下大群体决策的MC-EMD方法[J].中国管理科学,2017,25(04):164-173.
[17] Jin F F,Ni Z W,Pei L D,et al. Approaches to group decision making with linguistic preference relations based on multiplicative consistency[J]. Computers&Industrial Engineering,2017,114:69-79.
[18] Pang J F,Liang J Y,Song P. An adaptive consensus method for multi-attribute group decision making under uncertain linguistic environment[J]. Applied Soft Computing,2017,58:339-353.
[19] Peng H G,Zhang H Y,Wang J Q. Cloud decision support model for selecting hotels on Trip Advisor. com with probabilistic linguistic information[J]. International Journal of Hospitality Management, 2018, 68:124-138.
[20]文杏梓,罗新星,欧阳军林.基于决策者信任度的风险型混合多属性群决策方法[J].控制与决策,2014,29(03):481-486.
[21]糜万俊,戴跃伟.基于前景理论的风险型混合模糊多准则群决策[J].控制与决策,2017,32(07):1279-1285.
[22] Li D,Cheung D,Shi X M,Ng V. Uncertainty reasoning based on cloud models in controllers[J]. Computers&Mathematics with Applications, 1998, 35(3):99-123.
[23] Yang X,Yan L,Zeng L. How to handle uncertainties in AHP:the cloud delphi hierarchical analysis[J].Information Sciences,2013,222:384-404.
[24] Xu Z S. Uncertain linguistic aggregation operators based approach to multiple attribute group decision making under uncertain linguistic environment[J]. Information Sciences,2004,168(1-4):171-184.
[25] Herrera F,Martínez L. A 2-tuple fuzzy linguistic representation model for computing with words[J]. IEEE Trans on Fuzzy Systems,2000,8(6):746-752.
[26] Yager R R. OWA aggregation over a continuous interval argument with applications to decision making[J].IEEE Transactions on Systems,Man and Cybernetics,Part B(Cybernetics),2004,34(5):1952-1963.
[27] Opricovic S,Tzeng G H. Compromise solution by MCDM methods:a comparative analysis of VIKOR and TOPSIS[J]. European Journal of Operational Research,2004,(156):445-455.
[28]阎岩,唐振民,刘家银.基于不确定性分析的自主导航轨迹评测方法[J].机器人,2013,35(02):194-199.
[29]赵坤,高建伟,祁之强.基于前景理论及云模型风险型多准则决策方法[J].控制与决策,2015,30(03):395-402.
[30]邸凯昌,李德毅,李德仁.云理论及其在空间数据发掘和知识发现中的应用[J].中国图象图形学报,1999,4(11):32-37.
[31] Tversky A,Kahneman D. Advances in prospect theory:cumulative representation of uncertainty[J]. Journal of Risk and Uncertainty,1992,(5):297-323.
[32]鲍新中,肖明.基于粗糙集理论的证券投资决策[J].系统管理学报,2010,19(05):526-533.
[33] Weng Y, Gong P. Modeling spatial and temporal dependencies among global stock markets[J]. Expert Systems with Applications,2016,43:175-185.
[34]杨国亮.对外投资合作中的政治风险:现有研究的综述及其扩展[J].经济管理,2012,34(10):192-199.
[35]缪胜光,陈国宏,李美娟.基于云理论的福建省区域创新能力动态评价[J].中国管理科学,2011,19(SI):808-814.
[36]李晓广,张岩贵.我国股票市场与国际市场的联动性研究———对次贷危机时期样本的分析[J].国际金融研究,2008,(11):75-80.
[37]张兵,范致镇,李心丹.中美股票市场的联动性研究[J].经济研究,2010,(11):141-151.
[38] Fernández-Avilés G,Montero J,Orlov A G. Spatial modeling of stock market comovements[J]. Finance Research Letters,2012,9(4):202-212.
[39] Sun L,Najand M,Shen J. Stock return predictability and investor sentiment:a high-frequency perspective[J]. Journal of Banking&Finance, 2016, 73:147-164.
[40] Liang W. Sensitivity to investor sentiment and stock performance of open market share repurchases[J].Journal of Banking&Finance,2016,71:75-94.