Volatility Spillovers Research Articles

Does Volatility Spillover among Sectors Varies from Normal to Turbulent Periods? Evidence from Pakistan Stock Exchange

This study investigates how six financial market performances are affected by spillover volatility sectors in both during and following the 2007 financial crisis in Pakistan. By offering a wealth of material to fill in the gaps during the 2007 pre- and post-financial crisis timeframe, this study adds to the body of current knowledge. The pre-crisis era, which ran from January 1, 2003, to December 31, 2007, was used for the analysis on the Pakistani sectors. The period from January 1, 2008, to December 31, 2015, was known as the post-crisis era. The Pakistan Stock Exchange and other sources provided the data, which was routinely gathered. An ARCH, GARCH & EGARCH model is used to investigate the asymmetric volatility spillover among the six industries. The results provide compelling evidence for the existence of a spillover impact in Pakistani businesses in the years after the crisis. Furthermore, there is a significant transmission of volatility throughout Pakistan's many industries during the financial crisis. Overall, the results provide insight into the varying degrees of integration between sectors in Pakistan, ranging from stable to volatile eras. The results indicate that no significant vulnerability was detected. Additional elements can be included and the timing of data can be adjusted. In this study, data is currently gathered monthly. However, in the future, data might be collected on a daily, weekly, or yearly basis to enhance the reliability of the data and its corresponding conclusions. This study expands the existing body of research on volatility and spillover effects in several industries of Pakistan. This research is an innovative study being conducted in six market sectors. The primary impetus for conducting this inquiry is the financial catastrophe in the United States, which has had repercussions on global markets as a whole. Moreover, this time frame is also utilized to inspect the correlation in between financial crises and stock market returns in Asian emerging markets.

Analyzing the impact of remittance, FDI and inflation rate on GDP: A comparative study of Bangladesh, Pakistan and Sri-Lanka using VAR and BEKK-GARCH approach

This study examines the impact, conditional correlation and volatility spillover effect of remittances, foreign direct investment and inflation rate on GDP in Bangladesh, Pakistan, and Sri-Lanka, three Asian nations that are particularly vulnerable. While numerous studies have examined the relationship between remittances, FDI and IR on GDP but this paper approaches advanced econometric techniques to capture spillover effect and the dynamic interactions between the variables. For estimation purposes the study employs different econometric techniques such as Augmented Dickey-Fuller (ADF) test, VAR model, Granger causality tests, Impulse Response function, Variance Decomposition and BEKK-GARCH model. Bangladesh and Sri Lanka's REM, FDI and IR have no significant effects on GDP according to the VAR model. BEKK-GARCH demonstrates that three countries have both unidirectional and bidirectional transmissions of volatility, with the exception of Pakistan's REM and Bangladesh's FDI. We find that VAR model may not be adequate in capturing the complex dynamics between variables, which can be better captured by BEKK-GARCH model. Our comparison research shows how these variables affect GDP differently and similarly in each of the three nations, giving policymakers information they can use to create customized policies that encourage economic growth.

Oil Prices and Economic Growth in China: A Time-Frequency Analysis

This study analyses the inherent evolution dynamics of economic activity and global oil prices in China using the tools of wavelet and wavelet-based VAR-GARCH-BEKK model. Besides, the Wavelet-Granger causality test of Olayeni (2016) provides us further insights into the magnitude and direction of causal connectedness between oil prices and economic activity in China over time and across different frequencies simultaneously. We find that the spillover effects between China’s economic activity and global oil prices are time-varying in different time and frequencies in terms of direction and strength. More accurately, the prices and volatility spillovers between them are significant in the short and medium run but eventually neutral toward the long run. The Wavelet-Granger causality provides us further insights into the lead-lag relationships between oil prices and China’s economic activity from an economic perspective. The dynamic time-frequency association findings suggest crucial implications that might assist policymakers and other market participants in mitigating risk.

Evaluation of volatility spillovers for asymmetric realized covariance

This study proposes a new method for evaluating volatility spillovers in asymmetric realized covariance. The proposed method uses the realized semicovariance model, which decomposes the realized covariance based on positive and negative intraday returns. This method enables the measurement of volatility spillovers for both realized semivariance and asymmetric realized covariance. Asymmetric covariance spillovers are clearly observed when the method is applied to high-frequency data from major ETFs. Furthermore, our results demonstrate that accounting for asymmetric covariances plays an important role in the measurement of volatility spillovers.

Volatility Spillover Benefits of the Hang Seng Index and Shanghai Composite Index: A Vector Autoregressive (VAR) Model and Granger Causality Test Analysis

This study aims to explore the volatility spillover benefits between two major stock markets in Hong Kong and Shanghai, namely the Hang Seng Index and the Shanghai Composite Index. Empirical analysis is conducted using a Vector Autoregressive (VAR) model and Granger causality test based on daily return data from 2013 to 2023. The research finds a significant volatility interaction between the Hang Seng Index and the Shanghai Composite Index, which is more pronounced during periods of global economic instability. Impulse response analysis reveals that positive shocks in Hang Seng Index lead to increased volatility in the short term for the Shanghai Composite Index but gradually weaken to a weak negative effect in the long term. Conversely, positive shocks in the Shanghai Composite Index have a short-term inhibitory effect on the Hang Seng Index but transform into a weak promoting effect in the long term. These findings have important implications for investors and policymakers in risk management, forecasting future stock market trends, and capital allocation.

The Volatility Spillover of Global Oil Price Uncertainty

This manuscript, for the first time, analyses the volatility spillover of oil price uncertainty in the world using data from oil price uncertainty recently developed by Abdul and Qureshi (2023), spanning the time 1996-2019 on a monthly frequency. ARCH/GARCH (Autoregressive Conditional Heteroskedasticity and Generalized Autoregressive Conditional Heteroskedasticity) models are employed as an econometric tool. The findings suggest that ARCH model is more consistent than GARCH model in assessing the volatility of oil price uncertainty in the world. The results show that the volatility of oil price uncertainty is high in the world. The transition to renewable energy sources is proposed as a way to resist unexpected oil shocks since the production of renewables does not depend on the fluctuations of oil prices. Consequently, uncertainties in the oil price do not hinder economic activities.

High–low volatility spillover network between economic policy uncertainty and commodity futures markets

AbstractBased on the formation and evolution of systemic risk, we study the high‐low volatility spillovers between economic policy uncertainty (EPU) and commodity futures and identify the source of risk accumulation and risk outbreak, as well as the corresponding contagion mechanisms. Upon comparing topological characteristics on each volatility layer, our results demonstrate that high and low volatility spillover networks have different network characteristics and evolution behaviors. At the system level, high volatility spillovers are relatively stronger than spillovers in in low volatility network, while the risk propagation efficiency in the low volatility network is higher. At the market level, EPU is not only an important risk‐emitter but also a risk‐recipient most of the time. Additionally, compared with high volatility network, low volatility network characteristics have greater predictive ability for risk spillover among commodity futures, which means that it contains additional information and provides early warning signals for financial stress.

Terms of trade or market power? Further evidence from dynamic spillovers in return and volatility between Malaysian crude palm oil and foreign exchange markets

This study examines whether the Malaysian ringgit (MYR) provides terms of trade or market power for crude palm oil (CPO). We consider MYR exchange rates against three currencies of major CPO-importing countries, including the Indian rupee (INR), euro (EUR) and Chinese yuan (CNY). Using daily data on Malaysian CPO prices (spot and futures) and foreign exchange rates (INRMYR, EURMYR and CNYMYR) from 2000 to 2018, our results provide three notable findings. First, volatility spillovers from EURMYR to CPO spot and futures are more significant during the global financial crisis of 2008–2009. Second, the return spillovers from CPO spot and futures to INRMYR and EURMYR exchange rates experience significant bursts after the crisis. Third, the volatility of CPO spot price changes shows the predictive ability of the volatility of INRMYR exchange rate changes at the end of 2018. Overall, our findings support that the terms of trade are a driver of the CPO market after the crisis.

“Relationship Between The Volume Of Trade And Volatility Spillover Between The Selected Developed And Emerging Asian Markets”

“Relationship Between The Volume Of Trade And Volatility Spillover Between The Selected Developed And Emerging Asian Markets”

Volatility spillover between China's crude oil futures and sectoral stock markets from a frequency dynamics perspective

Volatility spillover between China's crude oil futures and sectoral stock markets from a frequency dynamics perspective

Do loosened trading rules restore the stock index futures price discovery ability in China?

In response to the severe liquidity depletion caused by extremely stringent trading restrictions, which were initially designed to deter speculative activities, China's regulatory authorities progressively loosened the trading rules governing the stock index futures market from 2017 to 2019. This paper explores the evolution of price discovery and volatility spillover between the index futures and its spot market amidst the four-phased loosening of trading rules. Utilizing a high-frequency dataset (5-min intervals), our findings unearth that the initial restrictive regulatory framework notably hinders the index futures market's functions of price discovery and volatility spillover. These functions then begin to exhibit signs of recovery as the restrictions are incrementally loosened. However, our analysis also uncovers that an excessive loosening of trading rules conversely impairs these critical market functions. The findings underscore the necessity for regulatory bodies to develop adaptable and reactive regulatory frameworks that can align with the market's continuous evolution.

A Pandemic's grip: Volatility spillovers in Asia-Pacific equity markets during the onset of Covid-19

The emergence of Covid-19 in late 2019 rapidly shattered the Asia-Pacific region (APR), a bastion of economic dynamism, and it became the epicenter of the global health crisis. This unprecedented pandemic not only triggered a public health catastrophe but also unleashed a financial storm, exposing vulnerability within the region's interconnected economies. This study identifies the factors driving volatility spillovers within Asian-Pacific financial markets during the initial wave of the Covid-19 pandemic (January 2020–February 2021). We analyze the interplay of pandemic transmission dynamics, government interventions, central bank policies, and socioeconomic variables. Our findings reveal a robust and persistent association between the rising number of Covid-19 cases per million and volatility spillovers. We introduce three novel determinants—the number of intensive care unit beds, population density, and the proportion of the elderly population—which significantly impact volatility transmission in response to new cases. Stringent government measures, such as travel bans and lockdowns, mitigate volatility spillovers. Conversely, central bank policies increase volatility spillovers. These insights contribute to a deeper understanding of financial market dynamics in the context of global health emergencies. This knowledge equips policy makers in the APR with valuable tools for navigating future crises.

Asymmetric Effects of Oil Price Volatility on Government Expenditure in Oil-Importing African Countries: Evidence from Zambia

This paper examines the impact of disaggregated oil price shocks the government expenditure in oil-importing African countries using the case of Zambia. The analysis utilizes a“Structural Vector Autoregressive (SVAR) Model” to evaluate the short-run effects, while a “Vector Error Correction Model (VECM) is employed to analyze the relationship over the long-run. Results of the short-run analysis reveal a notable positive influence of oil price shocks”on government expenditure that emanates from global aggregate and precautionary demand factors. The aforementioned results are clarified by the effects that increased global aggregate demand has on copper priсes, which in turn influences government revenue derived from taxes. Additionally, the transmission of “financial contagion and volatility spillovers” from the οil to the copper market clarifies the influence of precautionary demand on government expenditure. The findings obtained from the VECM indicate that global aggregate demand has positive effects on public sector spending in the long run. Additionally, the analysis demonstrates that the rate at which public sector spending recovers to its equilibrium level after a temporary deviation is both monotonic and statistically significant. Moreover, among the three categories of οil priсe hikes, Forecast Error Variance Decomposition analysis reveals that shocks related to precautionary demand have the most significant impact, accounting for 11.7% of the observed variation in public sector spending.

A STUDY ON THE VOLATILITY SPILLOVER BETWEEN NIGERIAN AND BRICS ECONOMIES USING MULTIVARIATE GARCH MODELS

BRIC-African relation has been of interest to key stakeholders especially given the inclusion of South Africa. In the existing literature some researchers hypothesized inclusion of Nigeria will accelerate BRICS objective of enhancing market access to ensure rapid economic growth among other objectives. This study utilized daily exchange rates of Naira/Dollar together with BRICS Dollar exchange rate for a period of 18 years. The study aimed to determine the volatility spillover between Nigerian and BRICS nations via Multivariate GARCH family: VECH, DBEKK and CCC Models. The result of VECH and DBEKK Models showed that all parameters were significant at 5% level, indicating clearly that there is positive impact of Exchange Rate shocks of Nigeria on the Exchange Rate Volatility of the BRICS economies, while for the CCC model only one parameter was significant at 5% level. This clearly indicated the existence of positive impacts of Exchange rates shocks of Nigeria on the Exchange Rate Volatility of the BRICS economies. On the other hand, only VECH model was able to capture the volatility spillover (own and cross) both on negative direction, suggesting a causal relationship between past volatility shocks in Nigeria and current volatility in the BRICS economies. Conclusively based on the information above VECH model was found to be appropriate to capture the volatility spillover between Nigerian exchange rate and that of the BRICS nations.

INTERMARKET INFLUENCE BETWEEN TRADITIONAL STOCK MARKETS AND CRYPTOCURRENCIES: A CASE STUDY OF JSX AND BTC

This study explores the intermarket dynamics between the Jakarta Stock Exchange Composite Index (JSX) and Bitcoin (BTC), focusing on their behavior during periods of market stress, such as the COVID-19 pandemic. Using historical data from 2017 to 2024, the research employs volatility analysis, Vector Autoregression (VAR) models, and correlation analysis to investigate the volatility spillovers and interdependencies between these two distinct markets. The findings reveal that BTC exhibits significantly higher volatility compared to JSX and USD/IDR, underscoring its high-risk nature. The study also uncovers that while volatility spillovers from JSX to BTC are present, the reverse is less pronounced, suggesting that traditional stock markets can influence cryptocurrency markets during periods of economic stress. The results have important implications for investors, highlighting the need for careful risk management and portfolio diversification strategies, especially in emerging markets like Indonesia.

Forecasting Volatility Spillovers Using Advanced GARCH Models: Empirical Evidence for Developed Stock Markets from Austria and USA

Forecasting Volatility Spillovers Using Advanced GARCH Models: Empirical Evidence for Developed Stock Markets from Austria and USA

A Study on the Exchange Rate Linkage between Korea and China following the Reform of the Yuan Exchange Rate System

Purpose - This study aims to conduct an empirical analysis of exchange rate volatility and dynamic correlation between Korea and China based on the “8.11” central exchange rate reform in China. Unlike other developed countries’ foreign exchange markets, the Chinese Yuan has not yet achieved complete free circulation, and China has an onshore Yuan exchange rate (CNY) and an offshore Yuan exchange rate (CNH). In this study, we investigated the dynamic correlation between Korea’s won exchange rate and China’s onshore yuan exchange rate and offshore yuan exchange rate around the “8.11” central exchange rate reform in China. Design/Methodology – In this study, we attempted to analyze the average and the volatility spillover effect of the won exchange rate from China’s onshore and offshore yuan exchange rate before and after the 8.11 central parity exchange rate reform. In addition, the relation between the won exchange rate and on- and off-shore yuan exchange rate at various stages were analyzed through the VAR model and the VAR-BEKK-GARCH model. Findings – The results of analyzing the volatility spillovers between the KRW exchange rate and the offshore RMB exchange rate show that there are two-way volatility spillovers between the two markets, both before and after the “8.11” central parity rate reform. The dynamic correlation between the two exchange rates (CNY and KRW, CNH and KRW) is increasing over time. In addition, the two exchange rates are positively correlated with each other, implying that the volatility of the two exchange rate markets is moving in the same direction. The dynamic dependence relations between CNY and KRW become significantly higher after the “8.11” central parity rate reform. Originality/value - As a non-international currency, the won must engage in export trade and capital market transactions with other international reserve currency countries. Therefore, it is important for Korean export-import companies and investors to explore changes in the dynamic correlation between the won and the Chinese yuan through exploration.

Equity markets and ESG dynamics: Assessing spillovers and portfolio strategies through time-varying parameters

Motivated by the recent surge of socially responsible activism, we examine the return and volatility transmission between the global Environmental, Governance, and Social index and traditional equity markets of G7 countries. For this purpose, we employ the TVP-VAR model on the returns and volatilities from 04 April 2011 to 09 September 2023. The variance co-variance matrix of the TVP-VAR model is used for portfolio analysis. Our finding indicates a significant level of connectedness between green and traditional equity markets. Moreover, green equity functions as a transmitter of both return and volatility spillovers to the traditional equity markets. In addition, our analysis of dynamic connectedness reflects a spike in both total return and volatility spillover amid the COVID-19 period. This indicates that the relationship between green and traditional equity markets intensifies during times of market stress and uncertainty which further infer implications for portfolio diversification. Furthermore, we calculated optimal asset allocation within portfolios and identified effective hedging ratios for different ESG and G7 equity pairs. The implications of the study include informing portfolio diversification strategies, and guiding decision-making for policymakers, hedge fund managers, and portfolio professionals amidst market uncertainties, based on identified market dynamics and connectedness.

WTI, Brent or implied volatility index: Perspective of volatility spillover from oil market to Chinese stock market.

This study investigates the impact of oil market uncertainty on the volatility of Chinese sector indexes. We utilize commonly used realized volatility of WTI and Brent oil price along with the CBOE crude oil volatility index (OVX) to embody the oil market uncertainty. Based on the sample span from Mar 16, 2011 to Dec 31, 2019, this study utilizes vector autoregression (VAR) model to derive the impacts of the three different uncertainty indicators on Chinese stock volatilities. The empirical results show, for all sectors, the impact of OVX on sectors volatilities are more economically and statistically significant than that of realized volatility of both WTI and Brent oil prices, especially after the Chinese refined oil pricing reform of March 27, 2013. That implies OVX is more informative than traditional WTI and Brent oil prices with respect to volatility spillover from oil market to Chinese stock market. This study could provide some important implications for the participants in Chinese stock market.

Uncertainty and cryptocurrency returns: A lesson from turbulent times

This paper explores the interplay between economic uncertainty and cryptocurrency behaviour. Using data spanning from April 2018 to December 2022, we examine the relationship between ten major cryptocurrencies and a repertoire of uncertainty measures covering geopolitical events, economic policy, and commodity, equity, and bond markets. Cryptocurrency returns exhibit dynamic and positive correlation with stock market and oil volatility, but no significant association with other uncertainty proxies. In terms of volatility spillovers, the transmission from uncertainty indices to cryptocurrency markets is weak, but intensifies during turbulent periods such as the COVID-19 outbreak or the Ukraine war. Overall, while the pricing of cryptocurrencies remains largely disconnected from economic risks, there are doubts cast on their alleged ‘safe haven’ properties.