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.     

Financial and Economic Integration's Impact on Asian Equity Markets’ Sensitivity to External Shocks

This paper investigates the spillover effects from U.S. and regional stock markets on local stock markets in the Pacific Basin region and China. We also analyze if the spillover depends on countries’ financial and economic integration. We apply a stochastic volatility model with jumps in order to separate the spillover of extreme shocks from those of normal shocks. We find that the spillovers of both normal and extreme shocks are significant for almost all Asian countries except China. We also find that the time‐variation in stock market interdependence can largely be associated with economic integration.     

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.     

Comparing the impact of Chinese and U.S. economic policy uncertainty on the volatility of major global stock markets

This study compares the impact of Chinese and U.S. economic policy uncertainty (EPU) (proxied by the EPU index) on the volatility of 11 major stock markets. Unlike previous research that only utilizes monthly EPU for such a comparison, this study uses both daily and monthly data to examine the impact within a month as well as over months. In order to provide a detailed analysis, EPU shocks are investigated from a two-sided viewpoint: one considering the effects of EPU indices as exogenous shocks, and the other examining the spillovers from EPU indices as endogenous variables. Meanwhile, the role of global turmoil, such as the 2007–2008 global financial crisis (GFC) and the COVID-19 pandemic, in influencing the impact of Chinese (or U.S.) EPU is highlighted. The results show that the impact of U.S. EPU is reinforced at both daily and monthly frequencies during the GFC, with a greater effect on the European stock markets. After the GFC, the rising influence of Chinese EPU is observed at a monthly frequency in several markets in Asia and elsewhere. Overall, the dynamic spillovers from the EPU indices to stock volatility suggest the dominant role of U.S. EPU in most markets at a daily frequency, while the extent of the spillovers is driven by turbulent events, including the GFC and the COVID-19 pandemic.     

Return and Volatility Spillovers and Cojump Behavior Between the U.S. and Korean Stock Markets

ABSTRACT

In this study, we examine return spillover, volatility transmission, and cojump behavior between the U.S. and Korean stock markets. In particular, we focus on cojump behavior between the two markets in order to explain the transmission of unexpected shocks. We find that the U.S. stock market causes return spillover effects in the Korean stock market, and there is significant volatility transmission between the two markets. Importantly, we find a stronger association in size, as compared with intensity, of cojumps between the U.S. and Korean stock markets, particularly during the recent financial crisis.     

Asymmetric volatility spillover among Chinese sectors during COVID-19

Inter-sectoral volatility linkages in the Chinese stock market are understudied, especially asymmetries in realized volatility connectedness, accounting for the catastrophic event associated with the COVID-19 outbreak. In this paper, we examine the asymmetric volatility spillover among Chinese stock market sectors during the COVID-19 pandemic using 1-min data from January 2, 2019 to September 30, 2020. In doing so, we build networks of generalized forecast error variances by decomposition of a vector autoregressive model, controlling for overall market movements. Our results show evidence of the asymmetric impact of good and bad volatilities, which are found to be time-varying and substantially intense during the COVID-19 period. Notably, bad volatility spillover shocks dominate good volatility spillover shocks. The findings are useful for Chinese investors and portfolio managers constructing risk hedging portfolios across sectors and for Chinese policymakers monitoring and crafting stimulating policies for the stock market at the sectoral level.     

Financial crises and the dynamics of the spillovers between the U.S. and BRICS stock markets

We examine the spillover dynamics between the U.S. and BRICS stock markets using the multivariate DECO-GJR-GARCH model and spillover index method. We identify time variations in volatility equicorrelation and significant dynamic spillovers between these stock markets, as well as an increased impact of uncertainty on spillovers. Spillovers between markets intensify after the inception of the global financial crisis and subsequent European sovereign debt crisis. We also find, following the commencement of the crisis periods, that the U.S., Brazilian, and Chinese markets are net volatility transmitters, whereas the Russian, Indian, and South African markets are net recipients. These results shed new light on the information transmission channels between the U.S. and BRICS stock markets.     

Price and Volatility Spillovers in the Case of Stock Markets Located in Different Time Zones

This paper investigates the interdependence of price volatility across the U.S. stock market and two emerging markets: Poland and Hungary. Using daily data for countries located in different time zones, we point out the problems caused by the presence of nonsynchronous trading effects. To address this problem we use open-to-close logarithmic returns of major stock market indexes. The asymmetric impact of good and bad news is described by a multivariate exponential general autoregressive conditional heteroskedastic model. We investigate the sample from May 2004 to December 2011. The evidence is that the U.S. prices spill over to other markets. Our results show no pronounced volatility spillovers among the three examined markets. Moreover, we observe the presence of negative asymmetry in the case of all markets.     

Firm size and volatility analysis in the Spanish stock market

Using Spanish stock market data, this paper examines volatility spillovers between large and small firms and their impact on expected returns. By using a conditional capital asset pricing model (CAPM) with an asymmetric multivariate GARCH-M covariance structure, it is shown that there exist bidirectional volatility spillovers between both types of companies, especially after bad news. After estimating the model, a positive and significant price of risk is obtained. This result is consistent with the volatility feedback effect, one of the most popular explanations of the asymmetric volatility phenomenon, and explains why risk premiums are much more sensitive to negative return shocks coming from the whole market or other related markets.     

Is U.S. economic policy uncertainty priced in China's A-shares market? Evidence from market,industry, and individual stocks

This paper is motivated by Bali, Brown, and Tang (2017) who find U.S. economic policy uncertainty (EPU) is priced in the cross-section of U.S. stock returns, and uses weekly data from March 2006 to April 2016 to study whether shocks in U.S. EPU also influence prices of China's A-shares from a market, industry, and individual stock perspective. Our methodology relies on an ARMA (1,1) model to extract shocks in the U.S. EPU series and a GARCH (1,1) model to examine how returns of China's A-shares respond to these shocks after controlling for business conditions proxied by term and credit spread in China. Generally, we find that shocks in U.S. EPU significantly and negatively explain returns of Chinese A-shares with a lag of one week. In addition, the market index containing small and growth stocks is more sensitive to shocks in U.S. EPU than the index containing big and value stocks. Furthermore, we find that firms in manufacturing, information technology, and media industries in China are more sensitive to shocks in U.S. EPU, while firms in agriculture and real estate industries respond less to shocks in U.S. EPU. Finally, China's A-shares which decline more in response to shocks in U.S. EPU have higher returns, smaller market capitalization, weaker operating profitability, higher asset growth, and better past year's cumulative returns. Overall, our findings show that investors in the Chinese A-shares market require a premium to hold stocks that are sensitive to shocks in U.S. economic policy uncertainty.     

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     

Modeling the Conditional Covariance Between Stock and Bond Returns: A Multivariate GARCH Approach

To analyze the intertemporal interaction between the stock andbond market returns, we assume that the conditional covariancematrix follows a multivariate GARCH process. We allow for asymmetriceffects in conditional variances and covariances. Using dailydata, we find strong evidence of conditional heteroskedasticityin the covariance between stock and bond market returns. Theresults indicate that not only variances, but also covariancesrespond asymmetrically to return shocks. Bad news in the stockand bond market is typically followed by a higher conditionalcovariance than good news. Cross asymmetries, that is, asymmetriesfollowed from shocks of opposite signs, appear to be importantas well. Covariances between stock and bond returns tend tobe relatively low after bad news in the stock market and goodnews in the bond market. A financial application of our modelshows that optimal portfolio shares can be substantially affectedby asymmetries in covariances. Moreover, our results show sizablegains due to asymmetric volatility timing.     

Transmission of Stock Returns and Volatility between the U.S. and Japan: Evidence from the Stock Index Futures Markets

In this paper, we examine the nature of transmission of stock returns and volatility between the U.S. and Japanese stock markets using futures prices on the S&P 500 and Nikkei 225 stock indexes. We use stock index futures prices to mitigate the stale quote problem found in the spot index prices and to obtain more robust results. By employing a two-step GARCH approach, we find that there are unidirectional contemporaneous return and volatility spillovers from the U.S. to Japan. Furthermore, the U.S.'s influence on Japan in returns is approximately four times as large as the other way around. Finally, our results show no significant lagged spillover effects in both returns and volatility from the Osaka market to the Chicago market, while a significant lagged volatility spillover is observed from the U.S. to Japan. This revised version was published online in August 2006 with corrections to the Cover Date.     

Spillover and Cojumps Between the U.S. and Chinese Stock Markets

There is an urgent need to understand the spillover and cojump effects between the U.S. and Chinese stock markets. The paper finds that since July 2005, the U.S. stock market has caused short-run spillover effects on returns on the Chinese stock market. More specifically, price changes in the United States can be used to predict both closing-to-opening and closing-to-closing returns on the Chinese stock market on the next day. However, there is no significant volatility spillover between the two markets. Both markets have shown stronger cojump behavior since the subprime crisis. The return relationships between the two stock markets are robust.     

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.     

Trading with Asymmetric Volatility Spillovers

Abstract:  We study the profitability of trading strategies based on volatility spillovers between large and small firms. By using the Volatility Impulse-Response Function of Lin (1997) and its extensions, we detect that any volatility shock coming from small companies is important to large companies, but the reverse is only true for negative shocks coming from large firms. To exploit these asymmetric patterns in volatility, different trading rules are designed based on the inverse relationship existing between expected return and volatility. We find that most strategies generate excess after-transaction cost profits, especially after very bad news and very good news coming from large or small firm markets. These results are of special interest because of their implications for risk and portfolio management.     

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.     

Can Stock Volatility Be Benign? New Measurements and Macroeconomic Implications

We find nonsynchronized movements of two new measures of financial market uncertainty—good and bad volatility—which are based on the maximum and minimum stock prices within a month. Good (bad) volatility is associated with better (worse) expectations about the future economic situation and clearly signals acceleration (deceleration) in economic activity. The VAR results indicate that (i) output, employment, and stock price plummet rapidly in response to a bad volatility shock, while their responses to a good volatility shock are modest, and (ii) bad volatility shocks explain the bulk of economic activity and stock price fluctuations in the medium run.     

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.     

Dynamic and frequency-domain spillover among economic policy uncertainty,stock and housing markets in China

This study examines the dynamic characteristics of information spillover effect among economic policy uncertainty (EPU), stock and housing markets in China's first-, second- and third-tier cities. To measure return and volatility spillovers over time and across frequencies simultaneously, the researchers utilize the time-frequency connectedness network approach developed by Baruník and Křehlík (2018). The empirical findings suggest that return and volatility spillovers are stronger in the longer period (more than 3 months) than in the shorter period (1 to 3 months). In the short term, second and third-tier cities are net transmitters of information spillovers, while in the long term, first-tier cities, EPU, and stock markets are the net information transmitters. Furthermore, the long-term information from the EPU and stock market affect most of the real estate markets for different tier cities. Additionally, market segmentation reveals the city-specific characteristics of China's real estate market, especially the close connections between first-tier cities and the stock market. These results have important empirical implications for real estate policymakers and investors when they make related short or long-term decisions.