标题： 基于金融危机指标的赢利投资策略 显示英文标题

标题： Winning Investment Strategies Based on Financial Crisis Indicators

摘要： 本工作的目的是基于市场动态的谱特性，构建几种金融危机指标的系统交易策略。 在我们框架和数据的限制范围内，我们将证明我们的系统交易策略能够盈利，这并非纯粹的运气，而是通过可重复的方式，并避免过拟合的陷阱，这是由于操作员的技能以及他们对金融市场的理解和知识。 为了以高效的方式计算所有谱，我们使用奇异值分解（SVD）技术，构建了两种具有明显预测能力的金融危机指标。 首先，有一些指标在每个日期将协方差或相关矩阵的特征值分布与代表平静或动荡市场的参考分布进行比较。 其次，我们有一些指标仅在每个日期计算协方差或相关矩阵的选定谱属性（迹、谱半径或Frobenius范数）。 为了最小化误报错误，我们将所有指标提供的信号进行聚合，然后基于一组离散规则构建系统交易策略，这些规则决定了投资者的投资决策。 最后，我们将我们的主动策略与被动参考策略以及随机策略进行比较，以证明我们方法的有用性以及由我们系统交易策略所基于的金融危机指标的样本外预测能力所带来的附加价值。 显示英文摘要

摘要： The aim of this work is to create systematic trading strategies built upon several financial crisis indicators based on the spectral properties of market dynamics. Within the limitations of our framework and data, we will demonstrate that our systematic trading strategies are able to make money, not as a result of pure luck but, in a reproducible way and while avoiding the pitfall of over fitting, as a result of the skill of the operators and their understanding and knowledge of the financial market. Using singular value decomposition (SVD) techniques in order to compute all spectra in an efficient way, we have built two kinds of financial crisis indicators with a demonstrable power of prediction. Firstly, there are those that compare at every date the distribution of the eigenvalues of a covariance or correlation matrix to a distribution of reference representing either a calm or agitated market reference. Secondly, we have those that merely compute at every date a chosen spectral property (trace, spectral radius or Frobenius norm) of a covariance or correlation matrix. Aggregating the signals provided by all the indicators in order to minimize false positive errors, we then build systematic trading strategies based on a discrete set of rules governing the investment decisions of the investor. Finally, we compare our active strategies to a passive reference as well as to random strategies in order to prove the usefulness of our approach and the added value provided by the out-of-sample predictive power of the financial crisis indicators upon which our systematic trading strategies are built.