Cross-border transmission of stock price volatility: evidence from the overlapping trading hours

Using high-frequency (5-minute returns) data, the transmission pattern of intraday volatility among three international stock markets (i.e., the United States, the United Kingdom, and Canada) during their overlapping trading hours (9:30–11:30 a.m. New York time). The major findings are as follows. First, the conditional variance of a domestic market is affected not only by the volatility surprises of its own market, but also by those of foreign markets. This finding holds for the United States as well as for Canada and the United Kingdom, implying that the information contained in the volatility surprises of each national market is clearly transmitted to other national markets. The volatility spillover is not unidirectional. Second, the magnitude of volatility spillover does not decrease monotonically as the lag length increases, indicating that the effect of a foreign volatility shock on the conditional variance of the domestic market tends to persist.     

Liquidity,implied volatility and tail risk: A comparison of liquidity measures

Liquidity is easily perceived but not easily measured in financial markets. Researchers and practitioners develop and test new measures of liquidity which may be good candidates for measuring this elusive concept. In this study, we present a comparison of variables within two empirical exercises using up to eight traditional liquidity proxies and two proposed proxies based on semi-deviations in a sample of NYSE-listed stocks. The first empirical exercise analyzes the relationship between liquidity and implied volatility, showing that increases in implied volatility impacts increases illiquidity. Using a decomposition of the squared VIX, we show that both conditional variance and variance premium components affects liquidity. Our second empirical exercise investigates the relationship between common factors in liquidity and tail risk. Common factors increase individual stocks' Value-at-Risk and Expected Shortfall, although the effect is not significant for market risk. In both applications, most of the studied proxies present results aligned with the body of literature.     

The dynamic relationship of volatility,volume, and market depth in currency futures markets

This study examines the dynamic interactions among return volatilities, volume, and market depth for five currency futures markets. We use vector autoregressive analysis (VAR) to identify not only the nature of these relations but also the direction and speed of the information flow between variables. We find that return volatility is subject to strong reversal effects from trading volume and market depth. The results also indicate that the volatility appears to have predictive power on volume but not on market depth. Furthermore, this study finds that volume and depth are not endogenously determined, as their lead–lag relationship is asymmetrical. We also observe an increasing trend of integration between offshore and domestic information that affects the movement of currency futures prices.     

The role of private information in return volatility,bid–ask spreads and price levels in the foreign exchange market

Trading volume and order flow have both been closely associated with informed trader activity in the market microstructure literature. Using theory that explains regular intraday patterns in trading data, we transform these two variables into proxies for private information and examine their relationships with bid–ask spreads and return volatility. We use a unique and unusually rich high-frequency intraday dataset from the world's largest financial market, namely, the electronic inter-dealer spot foreign exchange market. Our analysis takes account of institutional features peculiar to this order-driven market. Our empirical results strongly affirm our theoretical understanding of how these markets work. They also reveal how the structure of the inter-dealer spot FX market affects exchange rate volatility. Finally, we also explore how private information contributes to the evolution of prices.     

Dynamic volatility spillover effects between oil and agricultural products

The strong volatility spillover between crude oil and agricultural commodity markets reduces the diversification benefits and implies costly risk management process faced by portfolio managers and agricultural producers. This paper proposes a comprehensive study of their dynamic implied volatility spillover effects after the global financial crisis 2008–2009, while considering the transition between oil volatility's regimes. By using implied volatility, our analysis emphasizes on the forward-looking information that market traders usually convey in making decisions. We employ the generalized spillover indices within a fractionally integrated VAR model to capture the dynamic patterns of the volatility spillover effects alongside the Markov Switching Autoregressive model to extract the regimes of oil. Our results show new evidence that the net volatility spillover effect from crude oil to all agricultural commodities tends to decrease when crude oil remains in its low volatility regime. Conversely, this effect experiences an increasing trend when crude oil remains in its relatively high volatility regime. A dynamic strategy that combines oil and the most balanced agricultural commodity in terms of volatility transmission with oil (i.e., close-to-zero net volatility spillovers) depending on oil's regimes consistently outperforms the buy and hold strategy in terms of information ratio.     

US exports and time-varying volatility of real exchange rate

The effect of exchange rate volatility on trade is a controversial issue in international economics. Despite a widespread view that an increase in exchange rates volatility reduces trade, there is no real consensus on the direction or the size of the exchange rate volatility–trade level linkages. This paper investigates the relationship between US trade volume and exchange rate volatility using cointegration and error-correction models. We use conditional variances of the real effective exchange rate (REER) series modeled as a generalized autoregressive conditional heteroskedastic (GARCH) process to measure the exchange rate volatility. The cointegration results indicate a significant negative relationship between US export volume and exchange rate volatility. The short-run dynamics of the relationship, however, show that the effects of both real exchange rates and exchange rate volatility are insignificant.     

Volatility and information flows in emerging equity market: A case of the Korean Stock Exchange

Applying the generalized autoregressive conditional heteroskedasticity (GARCH) model to the Korean Stock Exchange, this study examines: (1) the statistical property of time-varying volatility in returns and trading volume data found in an emerging capital market, and (2) the property of the conditional variances of returns in predicting the flow patterns of information across the firms of different sizes. The results find that current trading volume as a proxy of information arrival dramatically reduces the persistence of the conditional variance, meaning that the arrival of information is a source of the ARCH effect in the emerging market just as it is in the U.S. The results also show that just as the volatility of larger firms can be predicted by shocks to smaller firms, the volatility of smaller firms can be predicted by shocks to larger firms. However, the volatility spillover effect from larger to smaller firms is more significant than that from smaller to larger firms.     

Forecasting aggregate stock market volatility with industry volatilities: The role of spillover index

In this paper, we aim to improve the predictability of aggregate stock market volatility with industry volatilities. The empirical results show that individual industry volatilities can provide useful predictive information, while the predictive contribution is limited. We further consider the spillover index between industry volatilities and find it displays strong predictive power for stock market volatility. Based on the portfolio exercise, we find that a mean-variance investor can achieve sizeable economic gains by using volatility forecasts of the spillover index. In addition, we conduct three extended analyses and further demonstrate the superior performance of the spillover index. Also, our results show robustness to a series of alternative settings. Finally, we investigate why the spillover index performs better and answer what information it contains. The results show that the spillover index can reflect and explain investor sentiments that are related to stock market volatility.     

When noise trading fades,volatility rises

We hypothesize and test an inverse relation between liquidity and price volatility derived from microstructure theory. Two important facets of liquidity trading are examined: volume and noisiness. As represented by the expected turnover rate (volume) and realized average commission cost per share (noisiness) of NYSE equity trading, both facets are found negatively associated with the ex post and ex ante return volatilities of the NYSE stock portfolios and the NYSE composite index futures. Furthermore, the inverse association between noisiness and volatility is amplified in times of market crisis. The negative noisiness–volatility relation is also supported by our analysis on the effects of trade size on price volatility. The overall results demonstrate that volatility increases as noise trading declines.     

Stock market volatility and equity returns: Evidence from a two-state Markov-switching model with regressors

This paper proposes a two-state Markov-switching model for stock market returns in which the state-dependent expected returns, their variance and associated regime-switching dynamics are allowed to respond to market information. More specifically, we apply this model to examine the explanatory and predictive power of price range and trading volume for return volatility. Our findings indicate that a negative relation between equity market returns and volatility prevails even after having controlled for the time-varying determinants of conditional volatility within each regime. We also find an asymmetry in the effect of price range on intra- and inter-regime return volatility. While price range has a stronger effect in the high volatility state, it appears to significantly affect only the transition probabilities when the stock market is in the low volatility state but not in the high volatility state. Finally, we provide evidence consistent with the ‘rebound’ model of asset returns proposed by Samuelson (1991), suggesting that long-horizon investors are expected to invest more in risky assets than short-horizon investors.     

Time and dynamic volume–volatility relation

This paper examines volume and volatility dynamics by accounting for market activity measured by the time duration between two consecutive transactions. A time-consistent vector autoregressive (VAR) model is employed to test the dynamic relationship between return volatility and trades using intraday irregularly spaced transaction data. The model is used to identify the informed and uninformed components of return volatility and to estimate the speed of price adjustment to new information. It is found that volatility and volume are persistent and highly correlated with past volatility and volume. The time duration between trades has a negative effect on the volatility response to trades and correlation between trades. Consistent with microstructure theory, shorter time duration between trades implies higher probability of news arrival and higher volatility. Furthermore, bid–ask spreads are serially dependent and strongly affected by the informed trading and inventory costs.     

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.     

Currency futures market in India: an empirical analysis of market efficiency and volatility

As the Indian currency futures market has been in existence for over 7 years, this paper analyses the effectiveness of the 1-month USD/INR currency futures rates in predicting the expected spot rate. The volatility of the USD/INR spot returns was also analysed. Modelling volatility of the USD/INR spot rate using a generalized autoregressive conditional heteroskedasticity (GARCH) and exponential generalized autoregressive conditional heteroskedasticity (EGARCH) model indicated the presence of volatility clustering. Using multivariate GARCH models such as the constant conditional correlation and dynamic conditional correlation, signs of a volatility spillover between the USD/INR spot and currency futures market were also observed.     

Asymmetric volatility spillover between oil-importing and oil-exporting countries' economic policy uncertainty and China's energy sector

While the relationship between economic policy uncertainty(EPU) and energy market is of great interest to economist, previous research dose not differentiate the effect from oil-importing countries to oil-exporting countries' EPU on the a country's energy sector. In this paper, we address this issue by testing the effect of importer and exporter's EPU on the largest oil-importing country, China, as oil-importing affected greatly by the economic policy. TVP-FAVAR model is applied to obtain the factors and time-varying coefficients of 21 countries' EPU monthly indexes and energy stock realized volatility. We find that the Chinese energy sector's stock volatility is positively related to EPU shocks and that bad volatility has a stronger impact than good volatility. Second, the volatility spillover from oil-exporting countries' EPU on the Chinese energy sector is stronger than that from oil-importing countries' EPU, with a stronger effect for bad volatility than for good volatility. Finally, The bad volatility spillover and spillover asymmetry is stronger during the crisis periods, such as the debt crisis, energy contention, oil price turbulence, or limited production agreement, both symmetric and asymmetric spillovers increase. Our findings have potentially important implications for the regulators and investors on Chinese oil market with different types of countries' EPU.     

Dynamic relations of uncertainty expectations: a conditional assessment of implied volatility indices

This study examines the spillover effects in international financial markets with respect to implied volatility indices. The use of the latter as the basis of integration analysis means that we test market participants’ expectations and not the actual price fluctuations. The empirical analysis, which includes all publicly available implied volatility indices, employs the dynamic conditional correlation model of Engle (2002) and its findings suggest that there is significant integration of investors’ expectations about future uncertainty. Furthermore, by accounting for the dynamic volatility of implied volatility inter-dependencies, we are able to reveal possible shifts in conditional correlations of market expectations over time. More specifically, our findings show a slight increase in the conditional correlations for all the volatility indices under review over the years and prove that in periods of turbulence in the financial markets the conditional correlations across implied volatility indices increase.     

Causality in volatility and volatility spillover effects between US, Japan and four equity markets in the South China Growth Triangular

In examining co-movement across international stock markets, previous researchers usually pre-determine the direction of causation and neglect the Chinese equity markets. In this study, we examine the spillover effects of volatility among the two developed markets and four emerging markets in the South China Growth Triangular using Chueng and Ng's causality-in-variance test. Several findings deserve mention: (1) the Japanese stock market affects the US stock market and there is a feedback relationship between the Hong Kong and US stock market. (2) Markets of the SCGT are contemporaneously correlated with the return volatility of the US market. (3) Econometric models constructed according to the results of variance-in-causality tests have greater explanatory power than the conventional GARCH(1,1) model. (4) Using the return volatility of foreign exchange as a proxy for informational arrival can explain excess kurtosis of a stock return series, especially for the less open emerging market. (5) Geographic proximity and economic ties do not necessarily lead to a strong relationship in volatility across markets.     

基于MSV与CoVaR模型的公司债市场与股票市场间风险溢出效应研究

依据2015—2017年中证公司债指数与沪深300指数的日收益数据,运用GC-t-MSV模型,检验中国公司债市场与股票市场间的风险溢出效应,并通过条件在险价值(CoVaR)模型度量两市场间风险溢出效应。结果表明：公司债市场与股票市场间存在不对称的双向风险溢出效应,且公司债市场对股票市场的风险溢出效应强于股票市场对公司债市场的风险溢出效应;公司债市场与股票市场的波动受其自身波动的影响较大,鉴此,监管部门和投资者应增强对公司债市场的关注,根据公司债市场的风险变化及时采取应对措施,充分发挥其风险信号作用。     

Dynamic volatility spillovers and investment strategies between the Chinese stock market and commodity markets

Building on the increased interest in the volatility spillover effects between Chinese stock market and commodity markets, this paper investigates the dynamic volatility spillovers of Chinese stock market and Chinese commodity markets based on the volatility spillover index under the framework of TVP-VAR. The result shows that there is a highly dependent relationship between the stock market and commodity markets. On average, the Chinese stock market is the net recipient of spillover, non-ferrous metals and chemical industry have a very obvious spillover impact on the stock market. The degree of total volatility spillover is different in different periods. After major crisis events, the volatility correlation between markets increases. Since the outbreak of COVID-19, the spillover effect of the stock market on the commodity market has been significantly enhanced. Then optimal portfolio weights and hedge ratios are calculated for portfolio diversification and risk management. The result shows that the ability of most commodities to hedge against risks is significantly reduced when the crisis occurs; NMFI (precious metals) and CRFI (grain) still have good hedging ability after the crisis, but the effectiveness of hedging risk is relatively low. Besides, the combination of CRFI and SHCI (the Shanghai composite index) is the most effective for risk reduction.     

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.     

Asymmetry in return and volatility spillover between equity and bond markets in Australia

We document asymmetry in return and volatility spillover between equity and bond markets in Australia for daily returns during the period 1992–2006 using a bivariate GARCH modelling approach. Negative bond market returns spillover into lower stock market returns whereas good news originating in the equity market leads to lower bond returns. Bond market volatility spills over into the equity market but the reverse is not true. Transmission of bond volatility into equity volatility depends in a complex way upon the respective signs of the return shocks in each market.