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带交易费用的动态投资组合管理

Dynamic Portfolio Management with Transaction Costs
课程网址: http://videolectures.net/amlcf09_suarez_dpmtc/  
主讲教师: Alberto Suárez
开课单位: 马德里自治大学
开课时间: 信息不详。欢迎您在右侧留言补充。
课程语种: 英语
中文简介:
我们开发了一个循环强化学习(RRL)系统,该系统直接从资产价格和指标的时间序列中归纳出投资组合管理策略,同时考虑交易成本。RRL方法学习了从指标序列到投资组合权重的直接映射,绕过了明确建模价格回报时间序列的需要。所产生的策略动态地优化了投资组合夏普比率,同时考虑了不断变化的条件和交易成本。包括马科维茨在内的许多投资组合优化方法的关键问题是发现角落解决方案。权重集中在少数资产上。在动态环境中,朴素的投资组合算法可以表现出交换行为,尤其是在忽略交易成本的情况下。在这项工作中,我们扩展了RRL方法,以产生更好的多样化投资组合和更平稳的资产配置。我们建议的解决方案包括现实的交易成本,并将投资组合的权重缩小到先前的投资组合。这些方法是根据一个由太平洋、北美和欧洲MSCI国际股指构成的全球资产配置问题进行评估的。
课程简介: We develop a recurrent reinforcement learning (RRL) system that directly induces portfolio management policies from time series of asset prices and indicators, while accounting for transaction costs. The RRL approach learns a direct mapping from indicator series to portfolio weights, bypassing the need to explicitly model the time series of price returns. The resulting policies dynamically optimize the portfolio Sharpe ratio, while incorporating changing conditions and transaction costs. A key problem with many portfolio optimization methods, including Markowitz, is discovering ”corner solutions” with weight concentrated on just a few assets. In a dynamic context, naive portfolio algorithms can exhibit switching behavior, particularly when transaction costs are ignored. In this work, we extend the RRL approach to produce better diversified portfolios and smoother asset allocations over time. The solutions we propose are to include realistic transaction costs and to shrink portfolio weights toward the prior portfolio. The methods are assessed on a global asset allocation problem consisting of the Pacific, North America and Europe MSCI International Equity Indices.
关 键 词: 交易费用; 动态投资组合; 管理
课程来源: 视频讲座网
最后编审: 2019-10-30:cwx
阅读次数: 64