In response to the currency crises in the emerging market economies (EMEs) during the 1990s, earlier studies tended to put emphasis on identifying and explaining currency crash, which is an extreme event mostly associated with massive capital reversals. After the 2008 global financial crisis, the focus shifted towards enormous capital inflows which have put a sharp appreciation pressure on domestic currency and inflated a large housing and construction bubble. In this paper, we examine the foreign exchange instabilities of a group of EMEs between 1995Q1 and 2019Q4 using the exchange market pressure (EMP) index by taking into considerations both extreme positive and negative episodes. The identification of tail observations is carried out under the framework of Extreme Value Theory (EVT) to handle asymmetric and heavy-tailed data. A panel multinomial logit model is used to explore whether the predictors differ between extreme positive and negative EMP events. Our findings show that (1) there is asymmetry in the EMP distributions, where the occurrence of currency crises is more frequent than excessive appreciations in most EMEs, (2) portfolio and credit flows are significant predictors to both extreme events, and (3) by distinguishing the residency of capital flows, foreign credit flow is the key factor that contributes to the devaluation pressure in the EMEs.

为了应对1990年代新兴市场经济体（EME）的货币危机，早期的研究倾向于将重点放在识别和解释货币崩盘上，这是一个极端事件，主要与大规模的资本逆转有关。2008年全球金融危机之后，重点转向大量资本流入，这给本币带来了极大的升值压力，并扩大了巨大的住房和建筑泡沫。在本文中，我们通过考虑极端正值和负值事件，使用交换市场压力（EMP）指数研究了1995年第一季度至2019年第四季度的一组新兴市场经济体的外汇不稳定性。尾部观测值的识别是在极值理论（EVT）的框架下进行的，以处理不对称且重尾的数据。面板多项式对数模型用于探索极端正和负EMP事件之间的预测变量是否不同。我们的发现表明（1）EMP分布不对称，大多数EME中货币危机的发生比过度升值更为频繁；（2）投资组合和信贷流量是这两种极端事件的重要预测因子，（3）通过区分资本流动的居民地位，外国信贷流动是导致新兴市场经济体贬值压力的关键因素。