集成专家意见的在线投资组合策略设计及竞争性能分析

项目名称： 集成专家意见的在线投资组合策略设计及竞争性能分析

项目编号： No.71501049

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 管理科学

项目作者： 张永

作者单位： 广东工业大学

项目金额： 17.4万元

中文摘要： 投资组合选择理论是现代金融理论的重要组成部分，受到了国内外学者的广泛关注。已有的投资组合模型往往假设证券价格服从某个随机过程。然而，在以我国为代表的新兴金融市场中，证券价格波动剧烈，难以找到合适的随机过程来刻画。这就需要修改模型中对证券价格的概率假设。本项目在不对证券价格作任何概率假设的前提下，应用弱集成算法研究集成专家意见的在线投资组合策略。首先，构造代表投资策略的静态专家意见和动态专家意见，应用弱集成算法分别集成这些专家意见，设计在线投资组合策略。其次，考虑利用固定期数的证券价格历史数据计算专家权重、交易费用因素及在线获得的边信息，设计更贴近实际投资决策的在线投资组合策略。最后，基于弱集成算法的竞争性理论分析在线投资组合策略的竞争性能，并用实际证券价格数据进行实证分析，检验策略的有效性。研究成果一方面可以完善在线投资组合选择理论，另一方面可以为我国证券市场中的投资决策活动提供理论依据。

中文关键词： 在线投资组合决策；在线算法；竞争性能分析；弱集成算法；专家意见

英文摘要： Portfolio selection theory is an important component part of modern financial theory, and is widely concerned by scholars at home and aboard. Existing portfolio selection models usually assume security prices obey some stochastic processes. However, in the emerging financial market with China as the representative, the security prices fluctuate dramatically and it is difficult to find suitable stochastic processes to describe them. Thus this requires us to modify the probability hypothesis about the security price in the model. Making no probability hypothesis about the security price, this project applies the weak aggregating algorithm to study online portfolio selection strategy by aggregating expert advices. Firstly, we construct static and dynamic expert advices representing investment strategies, and aggregate these expert advices using weak aggregating algorithm to design online portfolio selection strategy, respectively. Secondly, we consider using recent historical security price data of fixed number of periods to compute the weights of experts, and the transaction cost factor, and the side information obtained online to design online portfolio selection strategies which are closer to real investment decision-making. Finally, we analyze the competitive performance of our designed strategies based on the competitive theory of weak aggregating algorithm, and carry out empirical analysis using real security price data to illustrate the effectiveness of the strategies. On one hand, the research findings from this project will perfect the online portfolio selection theory; on the other hand, they can provide theoretical evidence for investment decision-making activities in Chinese security market.

英文关键词： Decision-making for online portfolio;Online algorithm;Competitive performance analysis;Weak aggregating algorithm;Expert advice