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The information content of implied volatility in developed versus developing FX markets

机译:发达和发展中外汇市场隐含波动率的信息内容

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This article predicts the daily movement of monthly foreign exchange (FX) rate volatility using a linear combination of a time-series model and implied volatilities from options. The focus is on analysing the FX volatilities in three developing economies (the Brazilian real (BRL), the Indian rupee (INR) and the Russian ruble (RUB)) against the US dollar (USD). The empirical exercise utilizes two time-series models, mixed data sampling (MIDAS) and GARCH. The analysis indicates that for both developed and developing economies the predictive power of MIDAS and that of GARCH is comparable. Further on in this article, we will ascertain whether the relationship between realized and implied volatility is fundamentally different in the case of developing economies from that among developed economies. Thus, we compare the pairs USD/BRL, USD/INR and USD/RUB against EURO/USD and USD/Japanese yen to determine the information content and predictive power of implied volatilities. Plots of the MIDAS coefficients show that the volatility is more persistent in developing economies than in developed economies.
机译:本文使用时间序列模型和期权的隐含波动率的线性组合来预测每月外汇(FX)汇率波动的每日运动。重点是分析三个发展中经济体(巴西雷亚尔(BRL),印度卢比(INR)和俄罗斯卢布(RUB))对美元(USD)的外汇波动率。实证研究利用了两个时间序列模型,即混合数据采样(MIDAS)和GARCH。分析表明,对于发达经济体和发展中经济体,MIDAS和GARCH的预测能力都是可比的。在本文的进一步内容中,我们将确定在发展中经济体与发达经济体之间,实际波动率和隐含波动率之间的关系是否根本不同。因此,我们将USD / BRL,USD / INR和USD / RUB对与EURO / USD和USD /日元进行比较,以确定隐含波动率的信息内容和预测能力。 MIDAS系数图显示,与发达经济体相比,发展中经济体的波动性更为持久。

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