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多约束的多阶段积极投资组合模型及实证研究

Multi-stage active portfolio management with multiple constraints and its empirical study
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摘要 构建投资组合时需要衡量其风险,除了考虑组合本身的风险暴露,还需考虑其相对基准组合的风险暴露.再者,确定组合权重时需要根据市场的规则加入合适的约束.基于此,为了较为完整地考虑现实投资组合面临的风险及交易约束,将绝对风险(CVaR)和相对风险(跟踪误差)作为风险约束,将交易成本、卖空限制和多元权值作为交易限制约束,构建一个新的多阶段投资组合模型,并利用动态规划和非线性优化方法进行求解.最后,利用上证50成分股中41只股票构建投资组合进行实证研究.实证结果表明构建的多阶段投资组合模型能持续战胜基准组合且优于单阶段投资组合,同时也表明模型考虑多元权值约束具有现实意义. When measuring the risk of the portfolio,the investment manager will consider not only the risk exposed by the portfolio itself,but also the risked exposed compared to a benchmark,i.e.active risk.In addition,the manager will set some constraints according to the rules of the market.Taking account of the risk and the transaction constraints in real market,we consider the absolute risk(CVaR)and the relative risk(Tracking Error)as the risk constraints while we consider the transaction costs,short-sale constraint and the multiple weight constraints as the transaction constraints.Then,we construct a new model of portfolio based on the constraints above and use the nonlinear algorithm and dynamic programming to solve it.Finally,an empirical study is presented based on the benchmark of SSE 50 in empirical study.The result proves the priority of the multi-stage portfolio compared to the single-stage one in terms of the return of the portfolio.Although adding the multiple weight constraints reduces the return of the portfolio in in-sample,we prove that the portfolio can be more efficient by using the multiple weight constraints incorporated by the correct forecast of the investment manager.The portfolio proposed not only conforms to the rules in reality but also shows advantages on the return and risk.
作者 徐维军 庾灿斌 徐中岳 XU Weijun;YU Canbin;XU Zhongyue(School of Business Administration,South China University of Technology,Guangzhou 510641,China)
出处 《运筹学学报》 CSCD 北大核心 2018年第4期57-68,共12页 Operations Research Transactions
基金 国家自然科学基金(Nos.71771091 71720107002) 中央高校基本科研业务费专项资金(No.C2180710) 中国博士后科学基金(No.2016M602476)
关键词 跟踪误差 CVAR 多阶段 动态规划 非线性优化 tracking error CVaR multi-stage dynamic programming nonlinear algorithm
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