外汇市场上一个世纪的套利和灾难风险定价

G. Corsetti, Emile Alexandre Marin
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引用次数: 4

摘要

在国际金融中,一个长期存在的难题是,正的利率差异系统地预测了汇率的升值——未发现的利率平价(UIP)难题。因此,通过借入低收益货币融资而持有高收益货币债券的套息交易组合有望产生正利润。然而,在金融危机之后,这个谜的迹象发生了变化——正的利差预示着过度贬值——在2007-2008年投资者遭受巨大损失后,套利交易已经萎缩。在本文中,我们使用了长达一个世纪的英镑/美元汇率时间序列来表明,标志转换既不是新的,也不是一个新的难题。首先,这在数据中并不新鲜——凭借一个不频繁、不重叠的货币崩溃的长样本,我们证明,在20世纪30年代的大萧条和20世纪90年代的汇率动荡等危机中,汇率转换系统地发生了。然而,对于短期和中期投资组合来说,UIP偏差在任何一个方向上都很明显,但对于长期投资组合来说,UIP偏差仍然很小,几乎可以忽略不计。其次,我们认为,我们长达一个世纪的证据与具有灾难或“比索事件”随时间变化概率的模型是一致的,这些模型是为了解释危机时期和非常规时期UIP偏差的差异,以及平均表征数据的套息交易回报期限结构的下降。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Century of Arbitrage and Disaster Risk Pricing in the Foreign Exchange Market
A long-standing puzzle in international finance is that a positive interest rate differen- tial systematically forecasts an exchange rate appreciation-the Uncovered Interest Parity (UIP) puzzle. Hence, a carry trade portfolio long in high yield currency bonds funded by borrowing in low yield currencies can be expected to yield positive profits. Following the Great Financial Crisis, however, the sign of the puzzle has changed-positive differentials forecast excessive depreciation-and carry trade has withered after the large losses suffered by investors in 2007-2008. In this paper, we use a century-long time series for the GBP/USD exchange rate to show that a sign switch is neither new, nor, arguably, a new puzzle. First, it is not new in the data-by virtue of a long sample featuring infrequent, non-overlapping currency crashes, we document that switches systematically occur in crises such as the Great Depression in the 1930s and the exchange rate turmoil of the 1990s. However, UIP devi- ations, sharp in either direction for short- to medium-horizon portfolios, remain small to almost negligible for long-horizon investment portfolios. Second, we argue that our century- long evidence is consistent with models featuring a time-varying probability of disasters or 'Peso events,' specified so to account for the difference in UIP deviations in crisis and nor- mal times, as well as for a decreasing term structure of carry trade returns that on average characterize the data.
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