Asymmetric interdependence between currency markets' volatilities across frequencies and time scales

Abstract

We investigate the dynamics of interdependence between realized variances and realized semivariances of six major currencies across frequencies and time scales. The empirical results are derived, first, through constructing daily measures of realized variance and semivariance from a high frequency 5‐min interval data, and second, by fitting wavelet squared coherence and wavelet cohesion measure with time‐varying weights. The realized volatilities of the currencies and their cross‐currency influences are found to increase during the global financial crisis. The realized volatilities of the Euro, Swiss Franc, and British Pound are closely synchronized over the short‐term horizon. However, over the long‐run, the Euro, Swiss Franc, and Japanese Yen lead the realized volatilities of the British Pound, Australian Dollar, and Canadian Dollar. The synchronization structure of positive and negative realized volatilities indicates asymmetric dependence among the currencies across time horizons. We further observe strong positive (negative) cohesion among the realized volatilities over the medium‐ and long‐term horizons. Finally, significant counter cyclical comovements among the currencies are observed over the medium‐ and long‐term horizons. These findings have important implications for foreign exchange portfolio managers.

Do birds of a feather flock together? Evidence from time-varying herding behaviour of bitcoin and foreign exchange majors during Covid-19

“…We posit that, not only is herding within the foreign exchange majors time-varying, but it is also horizon-dependent, as the time-varying herding is only observed based on the daily frequency but not at the hourly frequency. Specifically, our hourly and daily time-varying herding results provide some support to Choi et al (2021), who document that herding intensity varies, being more pronounced over longer than shorter time intervals, and Shahzad et al (2021) , who uncover a strong positive relationship between foreign exchange’s volatilities over the medium and long horizons.…”

“…Using a monthly dataset from 1995 to 2014 for 67 forecasters, anti-herding was reported over different monthly horizons: foreign exchange forecasters tend to differentiate themselves from each other, mainly when dealing with short-term forecasts. Meanwhile, using five-minute data, Shahzad et al (2021) scrutinise the interdependence between foreign exchange pairs and observe a strong positive relationship between the volatilities of pairs over the medium and long term.…”

In search of light in the darkness: What can we learn from ethical, sustainable and green investments?

“…For instance, all the EESG assets exhibit a significant increase in spillover and systemic risk with the declaration of the COVID‐19 pandemic. These findings are consistent with the literature that describes the increase on spillover among assets during periods of turmoil (Aloui et al, 2013; Charfeddine & Benlagha, 2016; Jawadi et al, 2014; Shahzad et al, 2021; Yahya et al, 2020).…”

“…Earlier studies are constrained from evaluating connectedness dynamics over short‐run horizon. However, the literature shows that the investment horizon tends to depend on the preferences of the market participants (Barunik & Vacha, 2018; Bekiros & Marcellino, 2013; Berger, 2015; Shahzad et al, 2021; Yahya et al, 2019). Therefore, in this study, we will provide a comprehensive overview of the variation in symmetric and asymmetric connectedness and spillovers among the underlying assets over various investment time horizons (Al‐Yahyaee et al, 2020).…”

Spillover effects of RMB exchange rate among RCEP member countries: Empirical evidence from time-frequency domain approach

“…The literature on exchange rate markets connectedness is quite extensive, encompassing the interlinkages among currencies of developed countries [22][23][24][25][26], spillover effects of developed country currencies to emerging market currencies [5,27,28], and the interdependence between currencies and other categories of assets, as stocks [29,30], oil [31,32], other commodities [31,33,34], and cryptocurrencies [35]. As China's influence in the International Monetary System (IMS) continues to grow, there is an increasing body of literature that examines the interlinkages between the RMB and other currencies.…”