Extreme risk spillover network: application to financial institutions

Using the CAViaR tool to estimate the value-at-risk (VaR) and the Granger causality risk test to quantify extreme risk spillovers, we propose an extreme risk spillover network for analysing the interconnectedness across financial institutions. We construct extreme risk spillover networks at 1% and 5% risk levels (which we denote 1% and 5% VaR networks) based on the daily returns of 84 publicly listed financial institutions from four sectors—banks, diversified financials, insurance and real estate—during the period 2006–2015. We find that extreme risk spillover networks have a time-lag effect. Both the static and dynamic networks show that on average the real estate and bank sectors are net senders of extreme risk spillovers and the insurance and diversified financials sectors are net recipients, which coheres with the evidence from the recent global financial crisis. The networks during the 2008–2009 financial crisis and the European sovereign debt crisis exhibited distinctive topological features that differed from those in tranquil periods. Our approach supplies new information on the interconnectedness across financial agents that will prove valuable not only to investors and hedge fund managers, but also to regulators and policy-makers.     

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.     

The behaviour of asset return and volatility spillovers in Turkey: A tale of two crises

This paper examines return and volatility spillovers between the Turkish stock market with international stock, exchange rate and commodity markets. Our aim is not only to examine spillover behaviour with a large emerging market but also to examine cross—asset spillovers and how they vary across two periods of financial market crisis; the dotcom crash and the liquidity-induced financial crisis. This is to be compared with existing work that typically focuses on industrialised countries or single asset markets only. Using the spillover index methodology we uncover an interesting distinction between these two periods of markets stress. Over the dotcom period spillovers are largely between the same asset class, notably two exchange rate series and two international stock markets series. However, in the period including the financial crisis, spillovers both increase and cross asset types and suggest a much greater degree of market interdependence. Understanding this changing nature in spillovers is key for investors, regulators and academics involved in theoretical model development.     

Spillovers among sovereign CDS,stock and commodity markets: A correlation network perspective

In the wake of the globalization of financial markets, studying spillovers among different asset markets, especially spillovers that include sovereign CDS markets, is of vital importance. This paper attempts to build a spillover network to investigate the complex interactions within the system of sovereign CDS, stock and commodity markets by adopting the spillover index based on forecast error variance (FEV) decomposition. The results reveal that emerging countries have larger average spillovers than developed countries with regard to sovereign CDS-to-stock returns spillovers, while the developed countries contribute more average spillovers than the emerging countries in the opposite direction. Moreover, the sovereign CDS market and the commodity market still demonstrate a relatively important role during certain periods although stock markets always occupy the dominant position during every phase. Our findings provide new insights into spillovers among the major global asset markets using a network perspective, which is valuable for regulation of financial markets, asset allocation and portfolio risk management.     

Cross-border interbank networks,banking risk and contagion

Recent events have highlighted the role of cross-border linkages between banking systems in transmitting local developments across national borders. This paper analyzes whether international linkages in interbank markets affect the stability of interconnected banking systems and channel financial distress within a network consisting of banking systems of the main advanced countries for the period 1994–2012. Methodologically, I use a spatial modeling approach to test for spillovers in cross-border interbank markets. The results suggest that foreign exposures in banking play a significant role in channeling banking risk: I find that countries that are linked through foreign borrowing or lending positions to more stable banking systems abroad are significantly affected by positive spillover effects. From a policy point of view, this implies that in stable times, linkages in the banking system can be beneficial, while they have to be taken with caution in times of financial turmoil affecting the whole system.     

Comparative analysis on the effects of the Asian and global financial crises on precious metal markets

The global financial crisis has vigorously struck major financial markets around the world, in particular in the developed economies since they have suffered the most. However, some commodity markets, and in particular the precious metal markets, seem to be unscathed by this financial downturn. This paper investigates therefore the nature of volatility spillovers between precious metal returns over fifteen years (1995-2010 period) with the attention being focused on these markets’ behavior during the Asian and the global financial crises. Daily closing values for precious metals are analyzed. In particular, the variables under study are the US$/Troy ounce for gold, the London Free Market Platinum price in US$/Troy ounce, the London Free Market Palladium price in US$/Troy once, and the Zurich silver price in US$/kg. The main sample is divided into a number of sub periods, prior to, during and after the Asian crisis. The aim of this division is to provide a wide and deep analysis of the behavior of precious metal markets during this financial event and of how these markets have reacted during times of market instability. In addition, this paper also looks at the effects of the global financial crisis from August 2007 to November 2010 using GARCH and EGARCH modeling. The main results show that there is clear evidence of volatility persistence between precious metal returns, a characteristic that is shared with financial market behavior as it has been demonstrated extensively by the existing literature in the area. In terms of volatility spillover effects, the main findings evidence volatility spillovers running in a bidirectional way during the periods; markets are not affected by the crises, with the exception of gold, that tends to generate effects in all other metal markets. However, there is little evidence in the case of the other precious metals generating any kind of influence on the gold market. On the other hand, there is little evidence of spillover effects during the two crisis episodes. Finally, the results from asymmetric spillover effects show that negative news/information have a stronger impact in these markets than positive news, again a characteristic that has been also exhibited by financial markets.     

Spatial linkage of volatility spillovers and its explanation across G20 stock markets: A network framework

This paper empirically estimates the spatial correlation relationship of volatility spillovers and its influencing factors across G20 stock market. We apply GARCH-BEKK model to estimate volatility spillover and construct dynamic volatility networks. The connectedness analysis shows that the spatial linkage of volatility spillover is time varying and has obvious multiple superposition phenomena. As somewhat innovation results, we use the factor analysis method to obtain centrality comprehensive indicators that can clearly depict the risk contagion intensity and risk acceptance intensity. In general, the developed markets are more influential than the emerging markets during periods of turbulence, and the emerging markets are more sensitive to volatility shocks than developed markets during any period. Finally, this paper introduces quadratic assignment procedure (QAP) method to identify the major factors that influence the spatial linkage of volatility spillovers. Results show that geography influences the volatility spatial correlation differently across economic cycles, and the centrality structure factors have greater impact on the spatial correlation than the external economic factors. The QAP regression analysis shows that these influencing factors can explain about 50% of the spatial correlation variation of international financial markets' volatility spillovers.     

Spillovers in risk of financial institutions

ABSTRACT

We analyse the total and directional spillovers across a set of financial institution systemic risk state variables: credit risk, real estate market risk, interest rate risk, interbank liquidity risk and overall market risk. We examine the response of the spillover levels, within the set of systemic risk state variables, to a number of events in the financial markets and to initiatives undertaken by the European Central Bank and the Bank of England. The relationship between the time-varying spillovers and policy-related events is analysed using a multiple structural break estimation procedure and looking at the temporary increases in the spillover indices. Our sample includes five European Union countries: core countries France and Germany, periphery countries Spain and Italy, and a reference country, the UK. We show that national stock markets and real estate markets have a leading role in shock transmission across selected state variables. However, the role of the other variables reverses over the course of the crisis. We document that the total and net spillover indices react strongly to the events relating to financial assistance packages in Europe.     

中国金融周期与横向关联:时空双维度相结合视角

宏观审慎政策关注各金融子市场在时间维度上的金融周期和空间维度上的横向关联。本文结合时间维度与空间维度视角,使用股票市场、货币市场、房地产市场以及信贷市场的数据,测算2001—2019年中国金融周期和横向关联的波动特征、作用关系与频域叠加机理。研究结果表明:时间维度金融周期与空间维度横向关联的波动趋势具有一致性。我国金融周期长度约为10.33年,横向关联波动周期的长度约为10.58年。从作用关系上看,首先,我国房地产周期达到波峰后,会对股票市场和信贷市场产生较强的溢出效应。随后,股市周期达到波峰后,会向房地产市场和信贷市场产生较强的溢出效应。最后,我国信贷市场接受股票市场和房地产市场溢出后,信贷周期会逐渐达到波峰。从频域叠加机理的角度看,我国金融子市场间横向关联的波动主要由中低频波段驱动,中低频波段横向关联的持续期在2个月以上。     

Does linkage fuel the fire? The transmission of financial stress across the markets

This paper develops an indicator of financial stress transmission, called Financial Stress Spillover Index (FSSI), to monitor the condition of financial system and to identify periods of excessive spillover that may lead to financial instability. Specifically, using the “spillover index” approach of Diebold and Yilmaz (2012), we modify and extend the financial stress indices proposed by Oet et al. (2011) to track both total and directional stress spillovers across the U.S. equity, debt, banking, and foreign exchange markets. Unlike other previous studies, the important linkages among these four major financial sectors in an interconnected world are directly taken into account by considering the average and time-varying connectedness of each individual market. The evidence suggests that there are important stress episodes and fluctuations across markets; the total cross-market stress spillovers were rather limited until the onsets of financial crises. As the crises intensified, so too did the financial stress spillovers; with significant stress carrying over from debt and equity markets to the others. In addition, our results indicate that FSSI has a significant predictive power for the economic activity and provides useful information for dating financial crisis.     

Risk spillovers from China's and the US stock markets during high-volatility periods: Evidence from East Asianstock markets

This paper studies cross-country risk spillovers through C-vine copula quantile regression. We find Both China's and the US markets can result in large risk spillovers to East Asian markets. Furthermore, their significant conditional spillovers indicate they can emit risk through an intermediary market. However, their distinctive dependency structures with East Asian markets reflect their differences in spillovers to the markets in magnitude. The risk spillovers from US are stronger than China in magnitude. Moreover, the risk spillover from China's stock market during its high-volatility period is weaker than the whole period, which is contrary to the US market. It may imply Chinese financial influences gradually increase with Chinese financial liberalization and regional integration. Our results have implications for macroprudential regulators adopt the effective supervision and regulation to deal with the cross-border risk spillovers, and for international investors in risk hedging, derivative valuation and investment.     

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.     

How strong are the linkages between real estate and other sectors in China?

International experience points to the critical role of stable property markets in maintaining financial stability. This paper investigates the real and financial linkages between real estate sector and other sectors. The real linkage based on input–output analysis shows that the linkages have strengthened. The financial linkages in terms of credit risk spillovers across sectors are studied by using DAG method and SVAR. We find that that credit risk in the real estate sector has large-scale spillover effects onto other sectors. Consequently, shocks to the property market could have much larger impact on the Chinese economy than suggested by headline figures.     

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.     

Internal and external spillover effects for the BRIC countries: Multivariate GARCH-in-mean approach

This paper examines mean-to-mean, volatility-to-mean and volatility-to-volatility spillover effects for the stock markets of BRIC countries. External and internal spillovers of returns and volatilities are estimated using 4-dimensional BEKK-GARCH-in-mean model. The model also includes the returns of stock markets in the USA, Germany, Japan and the MSCI Emerging market index, as well as time-return interaction terms which allow taking into account the dynamics of their influence on BRIC stock markets during pre-crisis, crisis and recovery time periods. Some evidence for the famous ‘decoupling’ phenomenon is found. The research contributes to the literature on spillover effects by using multivariate GARCH models.     

Volatility spillovers between WTI and Brent spot crude oil prices: an analysis of granger causality in variance patterns over time

There has been an increase in price volatility in oil prices during and since the global financial crisis (GFC). This study investigates the Granger causality patterns in volatility spillovers between West Texas International (WTI) and Brent crude oil spot prices using daily data. We use Hafner and Herwartz’s (2006) test and employ a rolling sample approach to investigate the changes in the dynamics of volatility spillovers between WTI and Brent oil prices over time. Volatility spillovers from Brent to WTI prices are found to be more pronounced at the beginning of the analysis period, around the GFC, and more recently in 2020. Between 2015 and 2019, the direction of volatility spillovers runs unidirectionally from WTI to Brent oil prices. In 2020, however, a Granger-causal feedback relation between the volatility of WTI and Brent crude oil prices is again detected. This is due to the uncertainty surrounding how the COVID-19 pandemic will evolve and how long the economies and financial markets will be affected. In this uncertain environment, commodities markets participants could be reacting to prices and volatility signals on both WTI and Brent, leading to the detection of a feedback relation.     

Static and dynamic liquidity spillovers in the Eurozone: The role of financial contagion and the Covid-19 pandemic

This paper investigates static and dynamic liquidity spillovers for a pool of ten Eurozone countries for the period 2000–2021. We estimate a generalised vector autoregressive (VAR) model based on Diebold and Yilmaz (2009, 2012). We find evidence for static and dynamic transmission of shocks through the liquidity channel. We propose a static measure of liquidity spillovers which captures total and pairwise average spillovers across Eurozone countries. Our measure shows strong evidence of interconnection within the Eurozone through the liquidity channel. We investigate the dynamic intensity and direction of liquidity spillovers, finding significant evidence of contagion during crisis periods. Our results indicate that most of the shocks during periods of financial uncertainty arise from leading economies within the Euro area.     

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.     

Artificial intelligence-based tokens: Fresh evidence of connectedness with artificial intelligence-based equities

The main focus of this research is to investigate the potential spillover effects between AI-based stocks and tokens by using the quantile connectedness approach developed by Ando et al. (2022). The study aims to investigate both static and dynamic spillovers at the lower and upper tails of the return distribution. AI-based stocks and tokens may have relatively low levels of connectedness, which also varies over time and increases during periods of economic turbulence. In addition, in line with previous work analysing other financial markets and assets, this research finds that the system is more sensitive to the tails of the distribution (i.e., the lower and upper quantiles) than to the median (Q = 0.50). This finding is consistent with expectations, and measures of dynamic connectedness change over time, with the intensity of spillovers increasing at the extremes of the distribution. These results have practical implications for portfolio managers, as they can use the results to adjust their investment portfolios according to the evolution of the dynamic spillovers observed in the system. Overall, this study sheds light on the potential tail spillovers in the AI-based stock and token market and provides valuable insights for investment decisions.