Following the leaders? A study of co-movement and volatility spillover in BRICS currencies

The paper investigates return co-movement and volatility spillover among the currencies of Brazil, Russia, India, China, and South Africa (the BRICS member countries) and four major developed countries from April 2006 to October 2019. Using Bloomberg daily data on exchange rates, the study employs a flexible multivariate generalized autoregressive conditional heteroskedasticity (MGARCH)–dynamic conditional correlation (DCC) model and a vector autoregressive (VAR)–based spillover index, as the empirical strategy. Along with evidence of exchange rate volatility in BRICS currencies, among which the Russian ruble and the Chinese yuan are explosive, the econometric estimation results show the presence of significant return co-movement and volatility spillover among the foreign exchange markets across different countries. The currency markets in developed countries, as leaders, are found to transmit volatility mostly to BRICS currency markets, which are net receivers. The degree of spillover, however, varies across countries, with Brazil and Russia passing on volatility to the developed countries whereas India, China, and South Africa receive volatility from their developed counterparts.     

Region-wide connectedness of Asian equity and currency markets

This study systemically analyzes the dynamics of interdependence between the Asian equity and currency markets. The novelty of our study is that unlike other studies that explore either co-movements among equity markets or co-movements among currency markets, we pay particular attention to the interdependence between the two in terms of both return and volatility connectedness. We find that the contribution of crossspillovers between the Asian equities and currencies is substantial for the region-wide connectedness of both the returns and volatilities. We also find that the short-term spillovers are far more important for the return spillovers, while the long-term spillovers are far more important for the volatility spillovers, presumably reflecting the long-lasting effects of volatility shocks. All the results consistently underline the pivotal role of cross-interdependence between equity and currency markets, both as channels for integrating Asian financial markets and as sources of financial contagion across these markets. Our findings will provide useful guidance for portfolio risk management to adopt better hedging strategies for foreign exchange risks involved in the international investment of Asian equities.     

Impact of the COVID-19 outbreak and its related announcements on the Chinese conventional and Islamic stocks’ connectedness

In this paper, we assess the impacts of the COVID-19 counts (infected cases, deaths and recovered) and related announcements on the Islamic and conventional stocks interplays in the Chinese market. We test whether Islamic stocks are perceived as assets providing diversification benefits in time of COVID-19 pandemic. Doing so, we implement a multivariate GJR-GARCH model under dynamic conditional correlation (DCC) as well as multiple and partial wavelet coherence methods to recent Chinese daily data ranging from 2 December 2019 to 8 May 2020 and COVID-19 related announcement for the period. Our results from multivariate GJR-GARCH models reveal that COVID-19 infected cases and deaths do impact mean DCCs between Islamic and conventional stocks, number of recovered do not have such impact, while none of the above have any significant impact on the DCCs fluctuations. However, when we analyze the impact of COVID-19 related announcement on the variation of conditional correlation between two stocks (i.e. DCC volatility) our findings show that 7 out of 10 such announcements (mainly those with serious health treats or economic implications) do effect those volatilities in Chinese equity market. The empirical findings from partial and multiple wavelet coherences provide robust evidence of instability in the co-movement between Islamic and conventional indexes for different scales and over dissimilar sub-periods. Indeed, the weakening of co-movements is especially notable in the very short and short-run where operating the short-term investors. Our empirical findings offer several key propositions for policy makers and portfolio managers in China with broad implications applicable to other markets.     

Volatility spillovers among the U.S. and Asian stock markets: A comparison between the periods of Asian currency crisis and subprime credit crisis

This paper examines the changing nature of volatility spillovers among the U.S. and eight East Asian stock markets between two financial crises: the Asian currency crisis and the U.S. subprime credit crisis. Our empirical results suggest that volatility is not always spilled over from the directly affected markets to surrounding markets in crisis periods. The East Asian markets who directly suffered from the Asian currency crisis are the ones to which volatility is spilled over from other markets during the Asian currency crisis period, whereas uni-directional volatility spillovers from the U.S. market to other markets are observed during both crisis periods. This difference can be explained by a pre-determined hierarchy in which volatility spillovers tend to start from the U.S. market regardless of the geographical origin of the crisis. Furthermore, our results reveal that the markets in three major Asian financial hubs, i.e., Japan, Hong Kong and Singapore, are the markets to which volatility is spilled over uni-directionally from several other countries during the subprime credit crisis period, but not during the Asian currency crisis period. We attribute this difference to crisis-specific (currency or credit crisis), market-specific (credit derivatives market participation and foreign currency reserves), and time-specific (more integrated global market) factors.     

Can crude oil drive the co-movement in the international stock market? Evidence from partial wavelet coherence analysis

In this paper, we employ partial- and multiple-wavelet coherence analyses to examine co-movement between international stock markets by considering the influence of crude oil in a time domain perspective. Overall, we find that crude oil is a major factor driving co-movement between international stock markets in the median and long term. However, when considering the oil-importing and oil-exporting countries differently, we still find that crude oil is a driver for interdependence between oil-importing and oil-exporting countries. In contrast, the crude oil has relative lower impact on the co-movement in oil-importing or in oil-exporting countries, which indicates its co-movement is caused by other factors. In addition, Gulf Cooperation Council stock market may lead the stock markets of oil-importing countries in the long term. Our empirical results provide meaningful information for investors and policymakers.     

Conditional value-at-risk forecasts of an optimal foreign currency portfolio

This study provides daily conditional value-at-risk (C-VaR) forecasts for a foreign currency portfolio comprising the USD/EUR, USD/JPY, and USD/BRL currencies. To do so, we estimate multivariate stochastic volatility models with time-varying conditional correlations using a Bayesian Markov chain Monte Carlo algorithm. Then, given the model-specific currency return density forecasts, we make the optimal portfolio choice by minimizing the C-VaR through numerical optimization. According to out-of-sample experiment, including emerging markets into the currency basket is essential for downside risk management, and considering model uncertainty as well as the parameter uncertainty can improve the portfolio performance.     

The dynamic relationship between stock,bond and foreign exchange markets

This paper investigates whether the deviation of a currency from its fundamentally determined rate of return affects the relationship between interest rates and stock market yields. A time-varying transition probability, the Markov-switching vector autoregressive (MS-VAR) model, is utilized for this purpose. Wald and likelihood ratio tests are computed and used as model adequacy measures. In order to analyze the link between the variables, impulse–response functions are employed. A sticky price exchange rate model is used to show the fundamentally determined rate of return of currencies. States are defined as either overvalued or undervalued, depending on the position of the observed exchange rate compared to its fundamentally determined rate. The model is applied to four major currencies: the Australian Dollar, the Canadian Dollar, the Japanese Yen, and the British Pound. Transition between the states is linked to the risk-adjusted excess return (the Sharpe ratio) of the debt and equity markets of the respective currencies in order to understand whether over- and undervaluation is connected to the returns in these markets. The results provide evidence that the relationship between economic fundamentals and nominal exchange rates are subject to change depending on the over- or undervaluation of the currencies relative to their fundamentally determined rate of return. An extension of this result shows that the Sharpe ratios of debt and equity investments in the currencies influence the evolution of the transitional dynamics of the exchange rates’ deviation from their fundamental values.     

The transition of the global financial markets' connectedness during the COVID-19 pandemic

This study contributes to the literature on financial research under the presence of the COVID-19 pandemic. Fresh evidence emerges from using two novel approaches, namely network analysis and wavelet coherence, to examine the connectedness and comovement of financial markets consisting of stock, commodity, gold, real estate investment trust, US exchange, oil, and Cryptocurrency before and during the COVID-19 onset. Moreover, unlike the previous studies, we seek to fill a gap in the literature regarding the ex-post detection of COVID-19 crises and propose the Markov-switching autoregressive model to detect structural breaks in financial market returns. The first result shows that most financial markets entered the downtrend after January 30, 2020, coinciding with the date the World Health Organization (WHO) declared the COVID-19 pandemic as a Public Health Emergency of International Concern. Thus, it is reasonable to use this date as the break date due to COVID-19. The empirical result from network analysis indicates a similar connectedness, or the network structure, in other words, among global financial markets in both the pre-and during COVID-19 pandemic periods. Moreover, we find evidence of market differences as the MSCI stock market plays a central role while Cryptocurrency presents a weak role in the global financial markets. The findings from the wavelet coherence analysis are quite mixed and illustrate that the comovement of the financial markets varies over time across different frequencies. We also find the main and most significant period of coherence and comovement among financial markets to be between December 2019 and August 2020 at the low-frequency scale (>32 days) (middle and long terms). Among all market pairs, the oil and commodity market pair has the strongest comovement in both pre-and during the COVID-19 pandemic phases at all investment horizons.     

Modelling Currency Crises in Emerging Markets: A Dynamic Probit Model with Unobserved Heterogeneity and Autocorrelated Errors*

The paper investigates the causes of currency crises in emerging markets. We estimate the probability of a currency crisis by applying maximum smoothly simulated likelihood to a dynamic LDV model. This approach allows us to take explicit account of the existence of intertemporal links between crises. The results show that currency crises are influenced by real, monetary, debt and global variables. Past banking crises are significant determinants of the probability of currency crises. Moreover, countries that sharply devalued in the past are less prone to experience another currency crisis. We find evidence of unobserved heterogeneity, which may reflect differences in the countries’ institutional/historical background. Finally, the determinants of currency crises differ by type of exchange rate regime.     

The impact of COVID-19 on the G7 stock markets: A time-frequency analysis

We examine the co-movement of the G7 stock returns with the numbers of confirmed COVID-19 cases and causalities based on daily data from December 31, 2019 to November 13, 2020. We employ the wavelet coherence approach to measure the impact of the numbers of confirmed cases and deaths on the G7 stock markets. Our findings reveal that both the number of confirmed COVID-19 cases and the number of deaths exhibit strong coherence with the G7 equity markets, although we find heterogeneous results for the Canadian and Japanese equity markets, in which the numbers of COVID-19 cases and the deaths exhibit only a weak relationship. This evidence is more pronounced in the long-term horizon rather than the short-term horizon. Moreover, the lead-lag relationship entails a mix of lead-lag relations across different countries. We present the implications of these findings for both policymakers and the international investment community.     

Continuous wavelet analysis of Chinese renminbi: Co-movement and lead-lag relationship between onshore and offshore exchange rates

This study examines the interdependence between the onshore (CNY) and offshore (CNH) Chinese renminbi exchange rates by employing continuous wavelet analysis. We pay particular attention to the effect of CNY exchange rate reform in 2015. We find that the interdependence between the CNY and CNH exchange rates has increased significantly following the 2015 reform. In addition, we find higher coherence for the lower frequencies than for the higher ones, suggesting that the interdependence between the two renminbi exchange rates is stronger over longer time horizons. Our evidence also indicates that, after the 2015 reform, the CNH tends to lead the CNY across almost all frequencies, except at the lowest frequency where the CNY leads the CNH.     

Nonlinear causality testing with stepwise multivariate filtering: Evidence from stock and currency markets

We examine the spillovers of the US subprime crisis to Asian and European economies and in particular to what extent currency and stock markets have been affected by the crisis. Linear and nonlinear dependencies are detected after pairwise and system-wise causality analysis. A new stepwise multivariate filtering approach is implemented after controlling for conditional heteroskedasticity in the raw data and in VAR/VECM residuals using multivariate GARCH models. Significant nonlinear causal linkages persisted even after the application of GARCH-BEKK, CCC-GARCH and DCC-GARCH modelling. This indicates that volatility effects might partly induce nonlinear causality. Perhaps new short-term asset-pricing models could be developed to explain this stylized fact. These results might also have important implications for hedging, trading strategies and financial market regulation.     

Spillovers of currency carry trade returns,market risk sentiment,and U.S. market returns

This paper examines the link between spillovers of currency carry trade returns and U.S. market returns. Following Tse and Zhao (2012), this paper hypothesizes that the magnitude of spillovers of currency carry trade returns is positively correlated with market risk sentiment and, therefore, has an impact on market returns. Using the G10 currencies and S&P 500 index futures, the empirical results present a high magnitude of spillover effects of currency carry trade markets. The empirical findings also show a significantly positive relationship between spillovers of currency carry trade returns and subsequent market returns. Furthermore, the results indicate that this relationship is stronger in bear markets than in bull markets. Finally, our findings show that spillovers of currency carry trade returns significantly affect the subsequent transition probabilities of market returns.     

Implied volatility term structure and exchange rate predictability

This paper provides empirical evidence of the predictive power of the currency implied volatility term structure (IVTS) for the behavior of the exchange rate from both cross-sectional and time series perspectives. Intriguingly, the direction of the prediction is not the same for developed and emerging markets. For developed markets, a high slope means low future returns, while for emerging markets it means high future returns. We analyze predictability from a cross-sectional perspective by building portfolios based on the slope of the term structure, and thus present a new currency trading strategy. For developed (emerging) currencies, we buy (sell) the two currencies with the lowest slopes and sell (buy) the two with the highest slopes. The proposed strategy performs better than common currency strategies – carry trade, risk reversal, and volatility risk premium (VRP) – based on the Sharpe ratio, considering only currency returns, which supports the exchange rate predictability of the IVTS from a cross-sectional perspective.     

The Yen as an International Currency

Japanese policy-makers have spent many years attempting to increase the role of the Yen as a regional and international currency. In this article Francis Breedon and Geoffrey Williams look at its role both before and after the Asian currency crisis. Pre-crisis they find that the Yen was of less regional importance than economic theory would suggest, so that its rapid depreciation from 1995 to 1997 did not influence regional currencies as much as it perhaps should have. Since the Asian crisis they find that its regional role has increased markedly, largely at the expense of the Dollar. This suggests that Yen volatility, which remains considerable, is likely to have more impact on regional Dollar exchange rates and thus less impact on real activity than before.     

On the predictability of the distribution of excess returns in currency markets

This paper investigates the predictability of foreign exchange (FX) volatility and liquidity risk factors on returns to the carry trade, an investment strategy that borrows in currencies with low interest rates and invests in currencies with high interest rates. Previous studies have suggested that this predictability could have been spuriously accounted for due to the persistence of the predictors. The analysis uses a predictive quantile regression model developed by Lee (2016) that allows for persistent predictors. We find that predictability changes remarkably across the entire distribution of currency excess returns. Predictability weakens substantially in the left tail once persistence is accounted for, implying a moderate negative predictive relation between FX volatility risk and carry trade returns. By contrast, it becomes stronger in the right tail. Furthermore, we provide evidence that FX volatility risk still dominates liquidity risk after controlling for persistence. These findings suggest that the persistence of the predictors needs to be taken into account when one measures predictability in currency markets. Finally, out-of-sample forecast performance is also presented.     

Time-frequency co-movement and network connectedness between green bond and financial asset markets: Evidence from multiscale TVP-VAR analysis

This study examines the time-frequency co-movement and network connectedness between green bonds and other financial assets in China. We propose wavelet coherence and multiscale TVP-VAR to explore the time-frequency co-movement and spillover connectedness. The empirical results are as follows. First, green bonds positively co-move with conventional bonds across time scales and negatively co-move with stocks and commodities. Second, there is a significant network connectedness of green bonds with conventional bonds in the short term, and the connectedness with stocks and commodities gradually strengthens with the increase in time scales. Third, the dynamic spillover between green bonds and other assets is much greater in the long and medium terms than in the short term. Finally, under crisis shocks, the spillovers spike temporarily in the short term, while they are persistent and at a high level in the long term. Overall, some practical implications are proposed for investors and policymakers.     

Are the stock and real estate markets integrated in China?

This paper examines the dynamic short-run and long-run co-movement between the real estate and stock markets in China by employing a continuous wavelet method. We use gross domestic product and M2 (broad money supply) as control variables to eliminate the common factors of the two markets and to identify the real nexus between them. The empirical results show that the co-movement between real estate and stock prices is weak in the short run, except during the financial crisis period. Since the stock market is highly volatile, while real estate prices are relatively stable, the two markets are less correlated in the short run. The results also show that real estate prices affect stock prices in the long run, which supports the existence of a credit-price effect in China. Real estate prices remained very high in most time periods. Enterprises and individuals can obtain funds from bank loans to invest in the stock market, thus raising stock prices. These findings indicate that the two markets are generally segmented in the short run but are integrated in the long run. The stabilization of the real estate market is critical for stability in the stock market, but not vice versa. Additionally, investments in the two markets may not provide a high level of risk dispersion in the long run in China.

     

A multivariate GARCH in mean approach to testing uncovered interest parity: evidence from Asia-Pacific foreign exchange markets

The existence of time-varying risk premia in deviations from uncovered interest parity (UIP) is investigated based on a conditional capital asset pricing model (CAPM) using data from four Asia-Pacific foreign exchange markets. A parsimonious multivariate generalized autoregressive conditional heteroskedasticity in mean (GARCH-M) parameterization is employed to model the conditional covariance matrix of excess returns. The empirical results indicate that when each currency is estimated separately with an univariate GARCH-M parameterization, no evidence of time-varying risk premia is found except Malaysian ringgit. However, when all currencies are estimated simultaneously with the multivariate GARCH-M parameterization, strong evidence of time-varying risk premia is detected. As a result, the evidence supports the idea that deviations from UIP are due to a risk premium and not to irrationality among market participants. In addition, the empirical evidence found in this study points out that simply modeling the conditional second moments is not sufficient enough to explain the dynamics of the risk premia. A time-varying price of risk is still needed in addition to the conditional volatility. Finally, significant asymmetric world market volatility shocks are found in Asia-Pacific foreign exchange markets.     

Dynamic connectedness of China’s green bonds and asset classes

This paper quantifies the co-movement and time-varying integration between China's green bonds and other asset classes across different time domains using the wavelet coherence and time-frequency connectedness model based on the time-varying parameter VAR (TVP-VAR). First, we predominantly detect a strong positive co-movement of green and conventional bonds, especially in the medium and long term. Second, strong bidirectional spillovers exist between green bonds and treasury, corporate, and financial bonds regardless of the time horizon. Lastly, cross-market spillovers between the green bonds and the stock, energy, low-carbon stock market were quite limited in the short-run but strengthened towards the long-term except during the 2015 China stock market crash and the COVID-19 recession when short-term integration rose sharply. The results document some practical enlightenment for investors and policymakers with various time horizons.