用张量分析全球固定收益市场
Analysing Global Fixed Income Markets with Tensors
摘要：
全球固定收益回报跨越多个到期日和经济体，也就是说，它们自然存在于称为张量的多维数据结构中。与标准的“平面视图”多变量模型，不可知的数据结构，只描述线性成对关系，我们引入了一个张量值的方法来模拟多个利率曲线共享的全球风险。通过这种方式，估计的风险因素可以通过分析分解为成熟度域和国家域成分，这使得投资者能够针对每个风险域设计严格且易于处理的全球投资组合管理和对冲策略。实证分析证实了八个发达经济体共有的全球风险因素的存在，并表明它们有能力对全球宏观经济环境进行比较准确的描述。
英文摘要：
Global fixed income returns span across multiple maturities and economies, that is, they naturally reside on multi-dimensional data structures referred to as tensors. In contrast to standard "flat-view" multivariate models that are agnostic to data structure and only describe linear pairwise relationships, we introduce a tensor-valued approach to model the global risks shared by multiple interest rate curves. In this way, the estimated risk factors can be analytically decomposed into maturity-domain and country-domain constituents, which allows the investor to devise rigorous and tractable global portfolio management and hedging strategies tailored to each risk domain. An empirical analysis confirms the existence of global risk factors shared by eight developed economies, and demonstrates their ability to compactly describe the global macroeconomic environment.
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