VOLATILITY SPILLOVERS BETWEEN THE BLACK MARKET AND OFFICIAL MARKET FOR FOREIGN CURRENCY IN GREECE

The issue of volatility spillovers between the black and official exchange markets for U.S. dollars in Greece for 1975–89 is examined. A vector error correction‐bivariate EGARCH model is developed and estimated to capture potential asymmetric effects of innovations and volatility. During the period under investigation, reciprocal spillovers are found between the black and official exchange markets for dollars. Furthermore, spillovers are asymmetric in that bad news in one market has a greater effect on the volatility of the other market than good news. Additionally, the size of spillover effects is greater from the official market to the black market. Finally, the removal of the foreign exchange controls in January 1986 made the volatility of the official exchange rate higher and changed the nature of volatility spillovers between the two markets. JEL Classification: F31, F32     

Asymmetric volatility spillovers between economic policy uncertainty and stock markets: Evidence from China

This study explores the spillovers between economic policy uncertainty (EPU) and stock market realized volatility (RV). The monthly index of Chinese and US EPU and RV are used to analyze the pairwise directional spillovers. We find that RV is a net receiver that is more vulnerable to shocks from U.S. EPU than to shocks from Chinese EPU. We further decompose the RV into good and bad volatility to test the asymmetric spillover effect between the stock market and EPU. The results suggest that EPU has a bigger effect on bad volatility in the stock market throughout most of the sample period. However, we find that good volatility spillovers become larger during periods of stimulated reform, whereas bad volatility spillovers become larger during periods of international disputes. We show that Chinese stock market volatility is sensitive to both U.S. and Chinese EPU and that the spillover is asymmetric in different periods.     

Shock and Volatility Transmission in the Futures and Spot Markets: Evidence from Turkish Markets

This paper examines the volatility transmission mechanism between the futures and corresponding underlying asset spot markets, focusing on Turkish currency and stock index futures traded on the lately established Turkish Derivatives Exchange (TURKDEX). Employing multivariate generalized autoregressive conditional heteroskedasticity modeling, which allows for potential spillovers and asymmetries in the variance-covariance structure for the market returns, the paper investigates the volatility interactions among each of the three futures-spot market systems. For all market systems under study, the volatility spillovers are found to be important and bidirectional. For the stock index market system, in line with the previous literature, volatility shows asymmetric behavior and strong asymmetric shock transmission. The main implication is that investors need to account for volatility spillovers and asymmetries among the futures and the spot markets to correctly build hedging strategies.     

Asymmetric volatility connectedness on the forex market

We show how bad and good volatility propagate through the forex market, i.e., we provide evidence for asymmetric volatility connectedness on the forex market. Using high-frequency, intra-day data of the most actively traded currencies over 2007–2015 we document the dominating asymmetries in spillovers that are due to bad, rather than good, volatility. We also show that negative spillovers are chiefly tied to the dragging sovereign debt crisis in Europe while positive spillovers are correlated with the subprime crisis, different monetary policies among key world central banks, and developments on commodities markets. It seems that a combination of monetary and real-economy events is behind the positive asymmetries in volatility spillovers, while fiscal factors are linked with negative spillovers.     

R&D, knowledge spillovers and stock volatility

Firms improve their know‐how not only by innovations (producing new knowledge), but also by knowledge spillovers (learning from others). The objective of this study is to test for two major hypotheses developed from a theoretical model explaining the relationship between R&D, knowledge spillovers and stock volatility. Analytically, the model suggests that asymmetric information caused by R&D activities with uncertain future output increases stock volatility, even though dividends and consumptions remain unchanged. However, interfirm knowledge spillovers have a negative impact on stock volatility by reducing the degree of asymmetric information. Both hypotheses are supported by empirical evidence from this study.     

Return and volatility spillovers between currency and bond markets in India

This paper examines the return and volatility spillovers between the foreign exchange and bond markets of India using a bivariate asymmetric BEKK-GARCH (1,1) model for the period 4 April 2005 to 31 March 2017. We find the evidence of bidirectional return and volatility spillovers with asymmetric effects between these two markets. The spillovers are evidenced even during the periods when foreign portfolio investments in the Indian bond markets were relatively low suggests the existence of strong inter-linkages between both the markets.     

Price dynamics in refined petroleum spot and futures markets

This article characterizes the spot and futures price dynamics of two important physical commodities, gasoline and heating oil. Using a non-linear error correction model with time-varying volatility, we demonstrate many new results. Specifically, the convergence of spot and futures prices is asymmetric, non-linear, and volatility inducing. Moreover, spreads between spot and futures prices explain virtually all spot return volatility innovations for these two commodities, and spot returns are more volatile when spot prices exceed futures prices than when the reverse is true. Furthermore, there are volatility spillovers from futures to spot markets (but not the reverse), futures volatility shocks are more persistent than spot volatility shocks, and the convergence of spot and futures prices is asymmetric and non-linear. These results have important implications. In particular, since the theory of storage implies that spreasd vary with fundamental supply and demand factors, the strong relation between spreads and volatility suggests that these fundamentals — rather than trading induced noise — are the primary determinants of spot price volatility. The volatility spillovers, differences in volatility persistence, and lead-lag relations are consistent with the view that the futures market is the primary locus of informed trading in refined petroleum product markets. Finally, our finding that error correction processes may be non-linear, asymmetric, and volatility inducing suggests that traditional approaches to the study of time series dynamics of variables that follow a common stochastic trend that ignore these complexities may be mis-specified.     

Volatility spillover in the foreign exchange market: the Indian experience

We find evidence of significant volatility co-movements and/or spillover from different financial markets to the forex market in India. Among a large number of variables examined, volatility spillovers from domestic stock, government securities, overnight index swap, Ted spread and international crude oil markets to the foreign exchange market are found to be significant. There is evidence of asymmetric reactions in the forex market volatility. Comparisons between pre-crisis and post-crisis volatility indicate that the reform measures and changes in financial markets microstructure during the crisis period had significant impact on volatility spillover. During the post-crisis period, the lagged volatility component that represents persistent or fundamental changes had significant spillover effect on forex volatility, rather than the temporary shocks component. There is evidence of a decline in the asymmetric response in the forex volatility during the post-crisis period in India.     

Dynamic spillovers across oil,gold and stock markets in the presence of major public health emergencies

Extreme events have a systemic impact on global financial markets, leading to significant cross-market spillovers in the oil, gold, and stock markets and raising widespread concerns about market linkages and risk contagion. In this paper, with a focus on both return and volatility, a frontier spillover network analysis is used to examine the strength and scale characteristics of spillovers in the oil, gold and stock markets under major public health emergency shocks. In addition, the paper adopts a marginal spillover and network analysis to evaluate linkage relationships, risk sources and transmission paths in the oil, gold, and stock markets during such events. The results show that the return and volatility spillover effects generated across the oil, gold, and stock markets are significant, with return spillovers being more stable and volatility spillovers being highly sensitive to emergencies. Meanwhile, the COVID-19 pandemic has displayed the strongest return and volatility spillovers. The high intensity of the shocks during the COVID-19 period has changed the usual characteristics of the market, with the gold market becoming the risk receiver and the oil market becoming risk sources.     

Conditional volatility persistence and volatility spillovers in the foreign exchange market

I investigate the magnitudes and determinants of volatility spillovers in the foreign exchange (FX) market, using realized measures of volatility and heterogeneous autoregressive (HAR) models. I confirm both meteor shower effects (i.e., inter-regional volatility spillovers) and heat wave effects (i.e., intra-regional volatility spillovers) in the FX market. Furthermore, I find that conditional volatility persistence is the dominant channel linking the changing market states of each region to future volatility and its spillovers. Market state variables contribute to more than half of the explanatory power in predicting conditional volatility persistence, with the model that calibrates volatility persistence and spillovers conditionally on market states performing statistically and economically better. The utilization of market state variables significantly extends our understanding of the economic mechanisms of volatility persistence and spillovers and sheds new light on econometric techniques for volatility modeling and forecasting.     

Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method

This paper analyzes dynamic volatility spillovers between four major energy commodities (i.e., crude oil, gasoline, heating oil and natural gas) in the oil-natural gas future markets. We construct a time-varying spillover method by combining the TVP-VAR-SV model and the spillover method of Diebold and Yilmaz (2009, 2012, 2014). We use the spillover method to obtain time-varying total, directional and pairwise volatility spillover indices. Our results summarize as follows: (1) The volatility spillover indices present peaks and troughs during some periods, such as shale gas revolution, financial crisis, and oil price crash; (2) After the U.S. shale gas revolution, the size of volatility spillover from natural gas future market has reduced sharply, but volatility doesn't decouple from the other three oil future markets; (3) The directional spillover is asymmetric. The crude oil and heating oil futures market are main net transmitter of volatility risk information, while the gasoline and natural gas futures markets are the net receiver; (4) For natural gas future market, the pairwise volatility spillover from crude oil future market has the most significant influence.     

Extreme spillovers of VIX fear index to international equity markets

This study analyzes the impact of VIX spillovers on market activities during extreme market conditions in 42 international equity markets from 1998 to 2014. Specifically, tail cross-dependence suggests that a small change in VIX significantly influences global market activities during extreme market conditions. The impact of VIX is asymmetric, which is more pronounced in bearish, highly volatile, and low trading volume markets. Moreover, VIX spillovers exhibit a stronger impact on returns in developed markets and on volatility in emerging markets. In terms of geographical location, the impact of VIX spillovers is more pronounced on returns in Europe and on volatility in Latin America. These findings indicate that international investors can potentially benefit from international portfolio diversification and can serve as useful guidance to policymakers in designing appropriate policies.

     

中国利率与股市间波动溢出效应的实证研究

采用多变量EGARCH模型分别对中国利率与沪深股市间的波动溢出效应进行的实证研究表明,股票收益率对利率收益率有着显著的短期动态影响;利率与沪深股市间存在着显著的双向波动溢出,除了利率对深圳市场的方向外,其他方向的波动溢出均存在着不对称性.     

Volatility returns with vengeance: Financial markets vs. commodities

To assess how financial markets and commodities are inter-related, this paper introduces a ‘volatility surprise’ component into the asymmetric DCC with one exogenous variable (ADCCX) framework. We develop an econometric model in which returns and volatility allow to influence pairs of assets, and derive several case studies linking commodities to stocks, bonds and currencies from 1983 to 2013. The innovative feature of our model is that these volatility spillovers are modeled consistently within the correlation dynamics of the ADCCX. We find evidence that return and volatility spillovers do exist between commodity and financial markets and that in turn, their relative impact on each other is very substantial.     

波动溢出网络视角的金融风险传染研究

当前各类经济风险交叉关联,金融系统的风险溢出效应备受关注,为刻画我国金融系统性风险传染的路径特征,本文从波动溢出网络的视角分析金融系统内部的风险传染机制。首先使用广义动态因子模型对收益波动的共同波动率成分和特质性波动率成分进行区分。然后,根据货币市场、资本市场、大宗商品交易市场、外汇市场、房地产市场和黄金市场之间的特质性波动溢出效应,利用基于TVP-VAR模型的方差分解溢出指数分析金融系统波动溢出的动态联动性和风险传递机制。在分析方向性波动溢出效应的基础上,采用方差分解网络方法构建起信息溢出复杂网络,从网络视角分析金融系统内部的风险传染特征。实证研究发现,房地产市场和外汇市场的净溢出效应绝对值相较于其他市场更大,其受其他市场风险冲击的影响强于对外风险溢出效应,而股票市场的单向对外风险溢出效应强度最大。在波动溢出的基础上,进一步考虑股市波动率指数与其他市场波动率指数进行投资组合的资产配置权重,计算了波动率指数投资组合的最优组合权重和对冲策略。研究结论有助于更好地理解我国金融系统的风险传染机制,对监管机构加强宏观审慎监管、投资者规避投资风险具有重要意义。     

Does Bitcoin still own the dominant power? An intraday analysis

The study investigates the intraday dynamics and price patterns of the primary cryptocurrencies. The Granger Mackey-Glass (M-G) model is employed to examine the asymmetric and nonlinear dynamic interactions in the first moment using positive and negative returns. The bivariate BEKK-GARCH model is applied to identify cross-market volatility shocks and volatility transmissions in the cryptocurrency market. The intra-cryptocurrency market analysis reveals that Bitcoin contains predictive information that can nonlinearly forecast the performance of other digital currencies when cryptocurrency prices either are rising or declining. The dominant power of Bitcoin is not dismissed using the intraday data. Further, Bitcoin's intraday lagged shocks and volatility induces more rapid and destabilizing effects on the conditional volatility of other currencies than each of the other currencies does on BTC's conditional volatility. The virtual currency markets are dynamically correlated and integrated through first and second-moment spillovers.     

Investigating the dependence structure between credit default swap spreads and the U.S. financial market

Under Basel II framework, credit risk assessment is of high significance in the light of correlation risk. Correlation risk is often envisioned along with business conditions and financial market’s impact. We employ copula methodology to identify the dependence structures that may exist between market risk fundamentals and credit risk fundamentals. Considering credit derivative spreads as credit risk fundamentals and market data as market risk determinants, we describe and quantify the asymmetric link prevailing between credit risk and market risk. Credit risk is negatively linked with market price risk whereas it becomes positively linked with market volatility risk. Such patterns give rise to interesting asymmetric dependence structures between both risk sources. We are then able to balance reliably market price risk with market volatility feedback, the market trend supporting a common correlation between securities. In the light of the previous trade-off, we propose also a simple credit risk management rule.     

Volatility spillovers and dynamic correlation in European bond markets

This paper examines the dynamic linkages among the European bond markets. We model the price and volatility spillovers from the US bond market and the aggregate Euro area bond market to twelve individual European bond markets using an EGARCH model that allows for a dynamic correlation structure. Our results suggest that significant volatility spillovers exist from both the aggregate Euro area bond market and the US bond market to the individual European markets. Moreover, the introduction of the Euro has strengthened the volatility spillover effects and the cross-correlations for most European bond markets.     

Modeling systemic risk and dependence structure between oil and stock markets using a variational mode decomposition-based copula method

This study combines the variational mode decomposition (VMD) method and static and time-varying symmetric and asymmetric copula functions to examine the dependence structure between crude oil prices and major regional developed stock markets (S&P500, stoxx600, DJPI and TSX indexes) during bear, normal and bull markets under different investment horizons. Furthermore, it analyzes the upside and downside short- and long-run risk spillovers between oil and stock markets by quantifying three market risk measures, namely the value at risk (VaR), conditional VaR (CoVaR) and the delta CoVaR (∆CoVaR). The results show that there is a tail dependence between oil and all stock markets for the raw return series. By considering time horizons, we show that there is an average dependence between the considered markets for the short-run horizons. However, the tail dependence is also found for the long-run horizons between the oil and stock markets, with the exception of the S&P500 index which exhibits average dependence with the oil market. Moreover, we find strong evidence of up and down risk asymmetric spillovers from oil to stock markets and vice versa in the short-and long run horizons. Finally, the market risk spillovers are asymmetric over the time and investment horizons.     

On detection of volatility spillovers in overlapping stock markets

This paper applies a recently proposed structural vector autoregressive model identification method to an established, previously unidentified theoretical model of stock market volatility spillovers. The structural model is identified and can be estimated with the method of maximum likelihood. Volatility spillovers can then be tested with the standard likelihood ratio test. This way our test, unlike the majority of the existing volatility spillover tests, has its foundations firmly in the economic theory. Our test is developed for fully overlapping stock markets. The empirical application of the paper considers stock markets of the eurozone in the years 2010–2011. Evidence of volatility spillovers is found.