论文标题
半度投资组合优化：一种新算法减少同时资产冲击
Semi-metric portfolio optimization: a new algorithm reducing simultaneous asset shocks
论文作者
论文摘要
本文提出了一种基于减少资产集合的同时资产冲击的新方法来优化财务组合。这可以理解为基于新数学数量的投资组合中风险降低的替代方法。首先，我们在有限集之间应用了最近引入的半量表，以确定时间序列的结构断裂之间的距离。然后，我们建立在Markowitz的经典投资组合优化理论的基础上，并将资产结构中断之间的这种距离用于我们的惩罚函数，而不是投资组合差异。我们的实验是有希望的：在综合数据上，我们表明我们所提出的方法确实在具有高度相似的结构断裂的时间序列之间多样化，并且比集合之间的现有指标具有优势。在实际数据上，实验表明，我们提出的优化方法相对于其他九种常用选项的性能很好，产生了第二高的回报，最低的波动率和第二低的下降。该方法在投资组合管理中的主要影响是在高度相似的结构性突破（例如市场危机）期间减少同时的资产冲击和潜在的急剧关联下降。我们的方法增加了计量经济学中投资组合优化技术的大量文献，并可以通过投资组合平均来补充这些技术。
This paper proposes a new method for financial portfolio optimization based on reducing simultaneous asset shocks across a collection of assets. This may be understood as an alternative approach to risk reduction in a portfolio based on a new mathematical quantity. First, we apply recently introduced semi-metrics between finite sets to determine the distance between time series' structural breaks. Then, we build on the classical portfolio optimization theory of Markowitz and use this distance between asset structural breaks for our penalty function, rather than portfolio variance. Our experiments are promising: on synthetic data, we show that our proposed method does indeed diversify among time series with highly similar structural breaks and enjoys advantages over existing metrics between sets. On real data, experiments illustrate that our proposed optimization method performs well relative to nine other commonly used options, producing the second-highest returns, the lowest volatility, and second-lowest drawdown. The main implication for this method in portfolio management is reducing simultaneous asset shocks and potentially sharp associated drawdowns during periods of highly similar structural breaks, such as a market crisis. Our method adds to a considerable literature of portfolio optimization techniques in econometrics and could complement these via portfolio averaging.
