退出时间和对资产绩效评估的影响
Mohammad Ghasemi Doudkanlou1, Prokash Chandro2, Shokoofeh Banihashemi3
1Department of Economics and Statistics, University of Siena, 53100 Siena, Italy.
Entropy (Basel, Switzerland)
|September 28, 2023
概括
本研究介绍了一种新的投资模型,该模型包含退出时间和香农,以更好地评估资产绩效. 增强方法通过平衡风险和回报来优化投资组合,以实现短期和长期目标.
科学领域:
- 量化金融 量化金融
- 投资管理 投资管理
- 风险测量 风险测量 风险测量
背景情况:
- 传统的风险测量往往忽略了关键因素,如退出时间.
- 香农提供了对投资组合多样化和风险的独特视角.
- 整合这些要素对于使投资与具体财务目标保持一致至关重要.
研究的目的:
- 通过将退出时间和香农度纳入风险测量来评估资产绩效.
- 为短期和长期投资目标制定投资组合优化策略.
- 将一个新的DEA模型与传统的平均CVaR方法进行比较.
主要方法:
- 使用数据包装分析 (DEA),将风险衡量作为输入,平均回报作为输出.
- 开发并应用了停止点概率-CVaR (SPP-CVaR) 来考虑退出时间.
- 在DEA框架内集成平均回报率和SPP-CVaR,处理负数据.
主要成果:
- 拟议的模型整合了平均回报率和SPP-CVaR,证明了资产选择能力的提高.
- 与平均CVaR模型的比较显示,当考虑出口时间和香农时,性能优越.
- 经验分析证实了对短期和长期投资的增强资产选择.
结论:
- 香农和退出时间的联合使用显著提高了对不同投资时间的资产选择.
- 拟议的DEA模型为投资组合优化提供了一个强大的框架.
- 这种方法引导投资者做出更明智的决策,与他们的财务目标保持一致.
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