Downside/upside price spillovers between precious metals: A vine copula approach

We studied downside and upside price spillovers between four precious metals (gold, silver, platinum and palladium), characterizing the multivariate dependence structure using a vine copula model and computing downside and upside value-at-risk and conditional value-at-risk. We found that the dependence structure differed across precious metals, all of which displayed different average and tail dependence features. Gold and silver prices were highly dependent except at the upper tail, whereas silver prices were integrated with those for platinum and palladium except at the upper tail. The gold market was very little integrated with the platinum and palladium markets. We document asymmetric downside and upside price spillover effects that differed in magnitude across precious metals; silver, in particular, had a greater downside and upside price impact on gold. Our results, indicating that precious metals do not behave as a single asset class, have implications for risk management, trading and hedging strategies for portfolios that include precious metals.     

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.     

Extreme risk spillovers between crude palm oil prices and exchange rates

This study is the first attempt to examine the extreme risk spillovers between Malaysian crude palm oil (CPO) and foreign exchange currencies of the three largest CPO importers: India, the European Union and China throughout the global financial crisis. Using daily data of three currencies, CPO spot and futures from 2000 to 2018, our results show: First, before the crisis, the unexpected change in foreign exchange rates is the primary driver of risk spillover to the CPO market. Second, during the crisis, the extreme movement of CPO spot returns is dominant in the Malaysian exchange rates relative to the euro. Third, after the crisis, the spillover flows from the CPO market to the foreign exchange market. Overall, our findings show the importance of CPO pricing dynamics in mitigating foreign exchange risk over the crisis period. This paper contributes to the extant literature by recognizing the effect of risk spillover on the targeted foreign exchange rate for portfolio allocation.     

Hedging local currency risk with precious metals

Precious metals are popular instruments for hedging local currency risk. Most precious metals are priced in US dollars, which is a single-currency numéraire. The numéraire of a precious metal can easily be changed, which allows investors to choose their own local currency as the precious metal’s numéraire and subsequently use it to hedge their own local currency risk. In this paper, we decompose the standard hedge ratio into two parts, namely, a precious-metal hedge ratio and a local-currency hedge ratio. We consider three main precious metals, namely, gold, silver and platinum, from the beginning of 1990 to the end of 2019 to hedge local currency risk for individual G10 currencies. Over the full sample, we find that all standard hedge ratios are negative for all combinations of currencies and precious metals. However, the negativity is driven by the precious metal’s numéraire, rather than the precious metal.     

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.     

Cross-region risk spillover between the stock and stock index futures markets under exogenous shocks

By integrating the stock and futures markets of mainland China and Hong Kong into the same financial system, we explore the cross-region risk spillovers between the stock market and stock index futures market under the impact of exogenous events. We find evidence of significant risk spillovers between the two stock markets, and confirm that exogenous shocks, including the adjustments of regulatory policies of mainland China and 2019 Hong Kong Protest, can significantly affect the volatility spillover across assets and markets. Our findings can potentially help regulators and investors understand the cross-region risk conduction and assess portfolio risk after exogenous event.     

Dynamic spillover and connectedness between oil futures and European bonds

This paper examines the spillovers and connectedness between crude oil futures and European bond markets (EBMs) having different maturities. We also analyze the hedging effectiveness of crude oil futures-bond portfolios in tranquil and turbulent periods. Using the spillovers index of Diebold and Yilmaz (2012, 2014), we show evidence of time-varying spillovers between markets under investigations, which varies between 65% and 83%. Moreover, three-month, six-month, one-year, three-year and thirty-year bonds and crude oil futures are net receivers of risk from other markets, whereas the remaining bonds are net contributors of risk to the other markets. Crude oil futures receive more risk from long-term than short-term bonds. Moreover, the magnitude of risk transmission is low for the pre-crisis and economic recovery periods. Crude oil futures market contributes significantly to the risk of other markets during the oil crisis and Brexit period. A portfolio risk analysis shows that that most investments should be in oil rather than bonds (except the short-term bonds). The hedge ratio is sensitive to market conditions, where the cost of hedging increases during GFC and ESDC period. Finally, a crude oil futures-bond portfolio offers the best hedging effectiveness during the COVID-19 pandemic period.     

Volatility analysis of precious metals returns and oil returns: An ICSS approach

This study examines volatility persistence on precious metals returns taking into account oil returns and the three world major stock equity indices (Dow Jones Industrial, FTSE 100, and Nikkei 225) using daily data over the sample period January 1995 to May 2008; the aim is to analyze market relationships before the global financial crisis. We first determine when large changes in the volatility of each market returns occur by identifying major global events that would increase fluctuations in these markets. The Iterated Cumulative Sums of Squares (ICSS) algorithm was used to identify the existence of structural breaks or sudden changes in the variance of returns. In each market the standardized residuals were obtained through the GARCH(1,1) mean equation. Our main results identify a clear relationship between precious metals returns and oil returns, while the interaction between precious metals and stock returns seems to be an independent one in the case of gold with mixed results for silver and platinum. In relation to volatility persistence, the results show clear evidence of high volatility persistence between these markets, especially during times when markets were affected by excessive volatility due to economic and financial shocks.     

Downside risk management and VaR-based optimal portfolios for precious metals,oil and stocks

Value-at-Risk (VaR) is used to analyze the market downside risk associated with investments in six key individual assets including four precious metals, oil and the S&P 500 index, and three diversified portfolios. Using combinations of these assets, three optimal portfolios and their efficient frontiers within a VaR framework are constructed and the returns and downside risks for these portfolios are also analyzed. One-day-ahead VaR forecasts are computed with nine risk models including calibrated RiskMetrics, asymmetric GARCH type models, the filtered Historical Simulation approach, methodologies from statistics of extremes and a risk management strategy involving combinations of models. These risk models are evaluated and compared based on the unconditional coverage, independence and conditional coverage criteria. The economic importance of the results is also highlighted by assessing the daily capital charges under the Basel Accord rule. The best approaches for estimating the VaR for the individual assets under study and for the three VaR-based optimal portfolios and efficient frontiers are discussed. The VaR-based performance measure ranks the most diversified optimal portfolio (Portfolio #2) as the most efficient and the pure precious metals (Portfolio #1) as the least efficient.     

Long memory and structural breaks in modeling the return and volatility dynamics of precious metals

We investigate the potential of structural changes and long memory (LM) properties in returns and volatility of the four major precious metal commodities traded on the COMEX markets (gold, silver, platinum and palladium). Broadly speaking, a random variable is said to exhibit long memory behavior if its autocorrelation function is not integrable, while structural changes can induce sudden and significant shifts in the time-series behavior of that variable. The results from implementing several parametric and semiparametric methods indicate strong evidence of long range dependence in the daily conditional return and volatility processes for the precious metals. Moreover, for most of the precious metals considered, this dual long memory is found to be adequately captured by an ARFIMA–FIGARCH model, which also provides better out-of-sample forecast accuracy than several popular volatility models. Finally, evidence shows that conditional volatility of precious metals is better explained by long memory than by structural breaks.     

Non-linear volatility dynamics and risk management of precious metals

In this paper, we investigate the value-at-risk predictions of four major precious metals (gold, silver, platinum, and palladium) with non-linear long memory volatility models, namely FIGARCH, FIAPARCH and HYGARCH, under normal and Student-t innovations’ distributions. For these analyses, we consider both long and short trading positions. Overall, our results reveal that long memory volatility models under Student-t distribution perform well in forecasting a one-day-ahead VaR for both long and short positions. In addition, we find that FIAPARCH model with Student-t distribution, which jointly captures long memory and asymmetry, as well as fat-tails, outperforms other models in VaR forecasting. Our results have potential implications for portfolio managers, producers, and policy makers.     

Asymmetric risk spillovers between Shanghai and Hong Kong stock markets under China’s capital account liberalization

In this paper, we investigate the asymmetric risk spillovers between Shanghai and Hong Kong stock markets under the backdrop of China’s capital account liberalization by measuring the Conditional Value-at-Risk (CoVaR) based on adjusted realized volatilities and variational mode decomposition based copula model. The empirical results show that, the asymmetric features of risk spillovers between the two markets are significant and manifest different states before and after the Shanghai-Hong Kong Stock Connect and Shenzhen-Hong Kong Stock Connect schemes. More specifically, first, the downside risk spillovers from Hong Kong to Shanghai are significantly larger than its upside risk spillovers, while the risk spillovers from Shanghai to Hong Kong is on the contrary. Second, the short-run risk spillovers are more drastic than the long-run risk spillovers, except the risk spillovers from Shanghai to Hong Kong after the Shenzhen-Hong Kong Stock Connect scheme. Finally, by comparing the risk spillovers from two directions, the importance of Shanghai stock market gradually rises up with the implementations of Stock Connect schemes.     

Extreme risk transmission channels between the stock index futures and spot markets: Evidence from China

We develop a skewness-dependent multivariate conditional autoregressive value at risk model (SDMV-CAViaR) to detect the extreme risk transmission channels between the Chinese stock index futures and spot markets. The proposed SDMV-CAViaR model improves the forecast performance of extreme risk by introducing the high-frequency realized skewness. Specifically, the realized skewness has a significant impact on the spillovers, but the realized volatility and realized kurtosis do not, which implies that the jump component plays an important role in extreme risk spillovers. The empirical results indicate there are bidirectional extreme risk spillovers between the stock index futures and spot markets, the decline of one market has direct and indirect channels to exacerbate the extreme risk of the other market. Firstly, the market decline will directly increase the extreme risk of related markets by decreasing market returns. Besides, the decline will indirectly increase the extreme risk by increasing the negative realized skewness and extreme risk spillovers.     

Spillovers between sovereign CDS and exchange rate markets: The role of market fear

As important variables in financial market, sovereign credit default swaps (CDS) and exchange rate have correlations and spillovers. And the volatility spillovers between the two markets become further complicated with the effect of market fear caused by extreme events such as global pandemic. This paper attempts to explore the complex interactions within the “sovereign CDS-exchange rate” system by adopting the forecast error variance decomposition method. The results show that there is a relatively close linkage between the two markets and the total spillover index of the system is dynamic. For most of the past, the exchange rate has a higher spillover effect on the sovereign CDS than vice versa. Moreover, after the market fear variables are introduced, the “sovereign CDS-exchange rate” system and market fear variables present bidirectional spillovers. The results of the study have particular significance for maintaining the financial stability and preventing risk contagion between markets.     

Common shocks,common transmission mechanisms and time-varying connectedness among Dow Jones Islamic stock market indices and global risk factors

The purpose of this paper is twofold. First, we examine the importance of permanent versus transitory shocks as well as their domestic and foreign components in explaining the business cycle fluctuations of seven Dow Jones Islamic stock markets (DJIM), namely U.S., U.K., Canada, Europe, Asia-Pacific, Japan and GCC, over the period from April 2003 to November 2018, using the permanent-transitory (P-T) decompositions approach of Centoni et al. (2007). Second, we investigate the spillover mechanisms of these shocks across Islamic stock markets and a set of global risk factors, using the Diebold and Yilmaz (DY) (2012) approach. The P-T decomposition results show that the DJIM U.S., U.K., Europe and GCC indices are sensitive to both domestic and foreign shocks, while the DJIM Canada, Japan and Asia-Pacific are most sensitive to domestic shocks. The empirical results of the DY approach indicate that: (i) the return and volatility spillover intensity increase during financial turmoil, supporting evidence of the contagion phenomenon, (ii) the DJIM U.S. is the main transmitter of return and volatility spillovers, while the DJIM GCC is identified as the main receiver of both return and volatility spillovers, (iii) the seven Dow Jones Islamic stock indices are weakly linked to movements of global risk factors, and (iv) there is evidence of possible portfolio diversification between the selected Islamic stock markets and the oil commodity market.     

Risk spillovers between cryptocurrencies and traditional currencies and gold under different global economic conditions

This paper applies a Diagonal BEKK model to investigate the risk spillovers of three major cryptocurrencies to ten leading traditional currencies and two gold prices (Spot Gold and Gold Futures). The daily data used are from 7 August 2015 to 15 June 2020. The dataset is analyzed in its entirety and is also subdivided into four distinct subsets in order to study and compare the patterns of spillover effects during economic turmoil, such as the 2018 cryptocurrency crash and the COVID-19 pandemic. The results reveal significant co-volatility spillover effects between cryptocurrency and traditional currency or gold markets, especially during the whole sample period and amid the uncertainty raised by COVID-19. The capabilities of cryptocurrency are time-varying and related to economic uncertainty or shocks. There are significant differences between normal and extreme markets with regard to the capabilities of cryptocurrency as a diversifier, a hedge or a safe haven. We find the significant co-volatility spillover effects are asymmetric in most cases especially during the COVID-19 pandemic period, which means the negative return shocks have larger impacts on co-volatility than positive return shocks of the same magnitude. Evidently, cryptocurrencies and traditional currencies or gold can be incorporated into financial portfolios for financial market participants who seek effective risk management and also for optimal dynamic hedging purposes against economic turmoil and downward movements.     

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.     

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.     

Volatility transmission across currencies and commodities with US uncertainty measures

This paper uses the Multi-chain Markov Switching model (MCMS) conditioned on US uncertainty measures (VIX, VIX-oil and FSI) to examine the patterns of volatility transmission across the resource, major and safe haven currencies The results with and without the uncertainty variables generally identify three patterns of volatility transmission: interdependence, spillover and comovement. They reveal the dominance of interdependence over spillovers and comovements when the uncertainty variables are excluded, highlighting the significance of mutual reciprocity of individual market shocks over common shocks across the selected assets. Within portfolios of a two-variable framework (two variables representing two minimum variance portfolios (à la Markowitz), containing a weighted combination of the currencies and of the commodities, respectively), we find interdependence between the two portfolios with and without the VIX, a spillover from commodities to currencies in the case when the FSI is included and independence between the two portfolios in the case when the oil-VIX is accounted for. The implications of the results are important for the portfolio managers in selecting portfolios’ components during high oil volatility periods.     

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.