Systemic Risk Propagation Research Articles

FINANCIAL CRISIS AND INSTABILITY

Financial crises and instability are common occurrences in the world economy, and they have significant effects on both developed and developing nations. The numerous causes of financial crises and the ensuing instability in the financial markets are thoroughly examined. It explains the theoretical foundations of financial crises, going over important ideas including market bubbles, excessive leverage, and regulatory shortcomings The paper also looks into how regulations and governmental actions can either exacerbate or lessen financial crises, how financial institutions contribute to systemic risk propagation and how interconnected they are. It looks at how the spread of crises across borders and asset classes can aggravate their severity through the contagion effect. It also covers the socio-economic fallout from financial crises, such as social unrest, income inequality, and unemployment. The summary concludes by highlighting how crucial it is to have strong regulatory control and proactive risk management to avert and lessen future financial disasters. It promotes a comprehensive strategy that blends international collaboration, regulatory changes, and responsible risk-taking to promote long-term economic growth and stability in a global financial system that is becoming more linked.

Dynamic spillovers in higher moments and jumps across ETFs and economic and financial uncertainty factors in the context of successive shocks

Hedging is a particularly important tool in the Exchange Traded Fund (ETF) markets where market makers seek the best ways to mitigate the uncertainty of their exposures. This study relies on high frequency data to assess the spillover effects among ten US sector ETFs and various economic and financial uncertainty indexes based on realized volatility, realized higher moments as well as jumps under a relatively new spillover framework. Next, a time-varying parameter vector autoregression (TVP-VAR) model is used to examine the dynamic connectedness among ETFs and uncertainty factors volatilities while avoiding the sensitivity of spillover results to the choice of the rolling window. Our results showcase higher total connectedness between the different uncertainty indexes and ETFs, though with varying sensitivities. Notably, skewness and kurtosis can spread from one market to another, especially during times of market turbulence, reflecting the significant spillovers in higher-order moments. Interestingly, the market’s 30-day forward looking expectations of US stock market volatility (VIX) has stronger effect on the US sector equity ETFs than the expected 30-day volatility of returns on oil and gold. This analysis emphasizes the implications and contributions of assessing the spillover in higher-order moments covering volatility, skewness, and kurtosis to portfolio hedging and financial risk management. Overall, the results are of considerable practical interest for economic and market agents who are keen to understand market integration and systemic risk propagation to infer asymmetric or fat tail risk related to extreme or downside/upside risks.

The determinants of systemic risk contagion

The elevated interconnectedness of the global financial system has resulted in an increased frequency of financial crises, characterized by the swift transmission of turmoil between countries. This study introduces a novel quantile-connectedness-based contagion metric and investigates the drivers of systemic risk contagion, employing methodologies that address endogeneity and time-variation. We analyze data spanning two decades from 27 international banks and encompassing balance sheet-derived variables. Our findings indicate that contagion during the 2004–2021 period is largely driven by credit risk and leverage, while the impact of size and capital adequacy weakens after 2012. Furthermore, funding structure and profitability only display a significant effect during the 2014–2017 and Covid-19 periods, respectively. We also observe distinct peaks and troughs in each bank's systemic risk propagation, although they share commonalities with their counterparts. Given our findings, we suggest a holistic systemic risk surveillance model that employs high-frequency data and simultaneously incorporates multiple risk factors.

Multilayer interbank networks and systemic risk propagation: Evidence from China

Multilayer interbank networks and systemic risk propagation: Evidence from China

Systemic risk propagation in the Eurozone: A multilayer network approach

In this paper, we study systemic risk propagation by exploring the dynamic mechanism of financial contagion among Eurozone countries. Using a multilayer information spillover network framework, we can consider the sovereign, banking and equity sectors’ risk spillover between countries simultaneously. This specification helps us to better identify the systemically important countries, i.e., the Eurozone financial stability. The findings emphasise the prominence of considering systemic risk propagation in a multilayer network structure. In fact, our empirical analysis suggests that considering intra-layer and inter-layer propagation is essential to gain a deeper insight into Eurozone systemic risk mechanisms.

From stress testing to systemic stress testing: The importance of macroprudential regulation

Stability of the banking system and macroprudential regulation are essential for healthy economic growth. In this paper we study the European bank network and its vulnerability to stressing different bank assets. The importance of macroprudential policy is emphasized by the inherent vulnerability of the financial system, high level of leverage, interconnectivity of system's entities, similar risk exposure of financial institutions, and susceptibility for systemic crisis propagation through the system. Current stress tests conducted by the European Banking Authority do not take in consideration the connectivity of the banks and the potential of one bank vulnerability spilling over to the rest of the system. We create a bipartite network with bank nodes on one hand and asset nodes on the other with weighted links between the two layers based on the level of different countries’ sovereign debt holdings by each bank. We propose a model for systemic risk propagation based on common bank exposures to specific asset classes. We introduce the similarity in asset distribution among the banks as a measure of bank closeness. We link the closeness of asset distributions to the likelihood that banks will experience a similar level and type of distress in a given adverse scenario. We analyze the dynamics of tier 1 capital ratio after stressing the bank network and find that while the system is able to withstand shocks for a wide range of parameters, we identify a critical threshold for both asset risk and bank response to a shock beyond which the system transitions from stable to unstable.

Institutional Ownership and the Propagation of Systemic Risk among Banks

Recent regulatory discussions concentrate on the role institutional investors play in the financial sector. We investigate whether institutional ownership (IO) is related to tail risk comovement in banks. We find robust evidence suggesting that IO is positively associated with a bank’s future tail risk. We find this relationship is stronger during economic downturns at the economy-wide level, as well as for banks demonstrating greater capital needs. Correspondingly, we find that there is a greater reduction in lending during recessionary periods for banks with higher levels of IO. Our results suggest a trading mechanism through which high turnover institutions in particular play a role in increasing tail risk comovement. We find the relationship exists in both overlapping and non-overlapping ownership, and the result is concentrated when the IO base exhibits low monitoring incentives. Lastly, we find evidence suggesting that disclosure may play a role in mitigating the relationship between IO and tail risk.

Identifying fragility for the stock market: Perspective from the portfolio overlaps network

In a financial system, the interconnectedness among entities from investing in common assets (portfolio overlaps) is considered an important channel for the propagation of systemic risk because this interconnectedness can facilitate the contagion of fire sales and lead to widespread sales as well as spiral devaluation of assets. This mechanism also applies to the stock market. Particularly, it is responsible for the presence of fragility, which is defined as the potential global instability of stock prices when confronted by a local negative shock. Thus, we propose to quantitatively explore the temporal pattern of the topological features of the portfolio overlaps network (PON) to identify fragility, with the aim of either capturing a precursor for imminent market crashes or confirming further downward falls during market turmoil. Here, PON is the projected monopartite network used to characterise the mutual overlaps between funds pairs, which is induced from the bipartite network of stocks-funds ownerships. Further, we adopt a solid statistical procedure to construct the validated PON by filtering out mildly risky connections that are not statistically robust. Based on an empirical investigation of the Chinese stock market from 2005 to 2018 that witnessed collective unquenchable price slumps, we found that the topology of the validated PON can indeed provide some sensible indicators for identifying market fragility. The results suggest that (i) the average closeness centrality and the critical value of effective infection rate could serve as leading indicators of impending market turmoil, and (ii) the simple degree-based measure for nodes and relative frequency measures for links are actual synchronous indicators that could also explain the source of fragility.

International trade, foreign direct investments, and firms’ systemic risk : Evidence from the Netherlands

This paper measures the contribution of firms in the financial and non-financial sectors to systemic risk. We quantify systemic risk as possible risk spillovers from individual firms to the economy by taking into account time-varying linkages between the firm and the economy. Based on a novel dataset that combines data on international trade and foreign direct investments with daily stock data for 67 Dutch listed companies from 2006–2015, our results indicate that high systemic risk contributions are not only present in the financial sector, but also occur in other sectors of the economy. We find that firms within the financial sector are more capable than non-financial firms of reverting to their pre-financial crisis level of systemic risk contribution. Having examined the potential role globalization fulfills in determining systemic risk, we find two main opposing effects. First, firms in internationally trade-intensive sectors contribute less to systemic risk than firms in sectors with low trade intensity. Second, systemic risk rises when firms are engaged in foreign direct investment activity, suggesting that international networks and global supply chains contribute to systemic risk propagation. Our empirical results imply that macro-prudential policy aimed at monitoring systemic risk should be extended to non-financial sectors and should take into consideration globalization measures, such as foreign direct investments and global supply chains.

Identifying Fragility for the Stock Market: Perspective from the Portfolio Overlaps Network

In a financial system, the interconnectedness among entities from investing in common assets (portfolio overlaps) is considered an important channel for the propagation of systemic risk because this interconnectedness can facilitate the contagion of fire sales and lead to widespread sales as well as spiral devaluation of assets. This mechanism also applies to the stock market. Particularly, it is responsible for the presence of fragility, which is defined as the potential global instability of stock prices when confronted by a local negative shock. Thus, we propose to quantitatively explore the temporal pattern of the topological features of the portfolio overlaps network (PON) to identify fragility, with the aim of either capturing a precursor for imminent market crashes or confirming further downward falls during market turmoil. Here, PON is the projected monopartite network used to characterise the mutual overlaps between funds pairs, which is induced from the bipartite network of stocks-funds ownerships. Further, we adopt a solid statistical procedure to construct the validated PON by filtering out mildly risky connections that are not statistically robust. Based on an empirical investigation of the Chinese stock market from 2005--2018 that witnessed collective unquenchable price slumps, we found that the topology of the validated PON can indeed provide some sensible indicators for identifying market fragility. The results suggest that (i) the average closeness centrality and the critical value of effective infection rate could serve as leading indicators of impending market turmoil, and (ii) the simple degree-based measure for nodes and relative frequency measures for links are actual synchronous indicators that could also explain the source of fragility.

Measuring the propagation of financial distress with Granger-causality tail risk networks

Using the test of Granger-causality in tail of Hong et al. (2009), we define and construct Granger-causality tail risk networks between 33 systemically important banks (G-SIBs) and 36 sovereign bonds worldwide. Our purpose is to exploit the structure of the Granger-causality tail risk networks to identify periods of distress in financial markets and possible channels of systemic risk propagation. Combining measures of connectedness of these networks with the ratings of the sovereign bonds, we propose a flight-to-quality indicator to identify periods of turbulence in the market. Our measure clearly peaks at the onset of the European sovereign debt crisis, signaling the instability of the financial system. Finally, we use the connectedness measures of the networks to forecast the quality of sovereign bonds. We find that connectedness is a significant predictor of the cross-section of bond quality.

MODELING INTERNATIONAL STOCK PRICE COMOVEMENTS WITH HIGH-FREQUENCY DATA

This paper studies stock price comovements in two key regions [the United States and Europe, which is represented by three major European developed countries (France, Germany, and the United Kingdom)]. Our paper uses recent high-frequency data (HFD) and investigates price comovements in the context of “normal times” and crisis periods. To this end, we applied a non-Gaussian Asymmetrical Dynamic Conditional Correlation (ADCC)-GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model and the Marginal Expected Shortfall (MES) approach. This choice has three advantages: (i) With the development of high-frequency trading (HFT), it is more appropriate to use HFD to test price linkages for overlapping and nonoverlapping data. (ii) The ADCC-GARCH model captures further asymmetry in price comovements. (iii) The use of the MES enables to measure systemic risk contributions around the distribution tails. Accordingly, we offer two interesting findings. First, while the hypothesis of asymmetrical and time-varying stock return linkages is not rejected, the MES approach indicates that both European and US indices make a considerable contribution to each other's systemic risk, with significant input from Frankfurt to the French and US markets, especially following the collapse of Lehman Brothers. Second, we show that the propagation of systemic risk is higher during the crisis period and overlapping trading hours than during nonoverlapping hours. Thus, the MES test is recommended as an indicator to help monitor market exposure to systemic risk and to gauge expected losses for other markets.

Systemic Risk and Vulnerabilities of Bank Networks

Stability of the banking system and macro-prudential regulation are essential for healthy economic growth. In this paper we study the European bank network and its vulnerability to stressing differ- ent bank assets. The importance of macro-prudential policy is emphasized by the inherent vulnerability of the financial system, high level of leverage, interconnectivity of system’s entities, similar risk exposure of financial institutions, and susceptibility for systemic crisis propagation through the system. Current stress tests conducted by the European Banking Authority do not take in consideration the connectivity of the banks and the potential of one bank vulnerability spilling over to the rest of the system. We create a bipartite network with bank nodes on one hand and asset nodes on the other with weighted links between the two layers based on the level of different countries’ sovereign debt holdings by each bank. We propose a model for systemic risk propagation based on common bank exposures to specific asset classes. We introduce the similarity in asset distribution among the banks as a measure of bank closeness. We link the closeness of asset distributions to the likelihood that banks will experience a similar level and type of distress in a given adverse scenario. We analyze the dynamics of tier 1 capital ratio after stressing the bank network and find that while the system is able to withstand shocks for a wide range of parameters, we identify a critical threshold for asset risk beyond which the system transitions from stable to unstable.

Uncertainty, systemic shocks and the global banking sector: Has the crisis modified their relationship?

We estimate the impact of equity market uncertainty and an unobservable systemic risk factor on the returns of the major banks in the global banking sector. Our estimation combines quantile regressions, structural changes, and factor models and allows us to explore the stability of systemic risk propagation among financial institutions. We find that risk propagation has remained stable over the last decade, and we report evidence indicating that equity market uncertainty is a major systemic factor for the global banking system. Additionally, we provide a new simple tool for measuring the resilience of financial institutions to systemic shocks.

Margin Procyclicality and Systemic Risk

We develop a model in which margin procyclicality, asset market depth and banks' propensity for liquidity hoarding interact to generate a systemic liquidity crisis. In this model, banks trade derivatives to hedge market risk or to speculate on interest rate movements. To mitigate counterparty credit risk, daily mark-to-market is required which results in daily margin calls. We show that when banks holdings of high quality liquid assets are insufficient to cover a margin call, banks hoard liquidity in the interbank market. Other banks might do the same leading to a liquidity hoarding contagion that is exacerbated by high interbank connectivity. We also show that distressed banks that do not have access to the interbank market sell their less liquid assets leading to consecutive declines in the price of these assets. This fire sale contagion is more severe if collateral haircuts are excessively high. Finally, we find that the propagation of systemic risk is unaffected by whether derivatives are centrally or bilaterally cleared, assuming the same daily mark-to-market rules apply.

Transmission of Systemic Risk Through Latent Leverage Channel

This paper examines the mechanism of systemic risk propagation through system-wide latent leverage channel. We focus on the hidden leverage-induced asset value dynamics in the financial markets, intertwined with balance-sheet components of the banking system. We propose a latent leverage index by estimating smooth transition regression models based on the intrinsic element of the financial system, off-balance-sheet transaction, and cross-border activities of the Korean commercial banking system. We find that a shock to the latent leverage index impacts the macroeconomy with the lag of three quarters. This finding provides an important policy-oriented implication for macroprudential supervision of banking system.

Assessing systemic risk and its determinants for advanced and major emerging economies: the case of ΔCoVaR

The paper examines conditional risk relationships among sovereign CDS prices and stock market indices for 11 economies with particular relevance for international portfolio investment holdings (Canada, China, Brazil, France, Germany, Italy, Japan, Russia, Spain, the USA, and the UK). The analysis is based on delta conditional value at risk (ΔCoVaR). The UK, France, and Italy significantly contribute to the overall systemic risk in both markets. The USA, the UK, and Russia appear to be important contributors to it in the stock market. In the meantime, the advanced economies exhibit much higher resilience to the systemic risk propagation in comparison with China, Brazil and Russia. Gross government debt to GDP, state fragility index, EU membership and world gross GDP share of a country in distress are key determinants of ΔCoVaRs for the sovereign CDS prices. Stock market total value traded to GDP and world gross GDP share of a country in distress drive ΔCoVaRs in the stock market. In both cases geographic distance tends to deter systemic risk propagation. Inflation, trade and financial openness as well as common language and time zone differences are less important predictors of bilateral ΔCoVaR exposures.

Systemic Leverage and Homogeneity: Assessing Multifaceted Amplifying Mechanism of Systemic Risk

This paper examines the amplifying mechanism of systemic risk propagation within a nonlinear framework. We focus on the hidden leverage-induced asset value dynamics in the financial markets, intertwined with balance-sheet components of the banking system. We propose a systemic leverage index by estimating smooth transition regression models based on the intrinsic element of the financial system, off-balance-sheet transaction, and cross-border activities of the Korean commercial banking system. We find strong evidence that the amplification is more pronounced with the cross-sectional homogeneity in managing systemic leverage as a whole. This observation provides the important policy-oriented implication that an individual bank’s systemic importance can be gauged by its marginal contribution to system-wide homogeneity.

What Makes Systemic Risk Systemic? Contagion and Spillovers in the International Sovereign Debt Market

We analyze the cross-border propagation of systemic risk in the international sovereign debt market. Using daily data on CDS spreads for 67 sovereign borrowers from 2002 to 2013 we define sovereign credit events as those in which the spread widens by more than 99.9% of all spread changes within regions. We find a total of 89 such credit events, most of them taking place after 2007. We analyze contagion by studying the immediate effects of these events on CDS spreads of other sovereigns within the region and in the rest of the world. Although a few events had effects that were global in scope, we find that such “fast and furious” contagion has been by and large a regional phenomenon. To analyze “slow burn” spillover effects, we extract the first principal component of CDS spread changes to identify a global sovereign risk factor. The corresponding loadings on this factor then serve to measure the sensitivity of individual sovereign CDS spreads to the global factor. We allow these loadings to vary over time and interpret them as measures of vulnerability to global systemic risk. We find that the global “slow-burn” spillover of credit events works through the global risk factor rather than through sovereign obligors’ systemic vulnerabilities. While the global factor and regional vulnerabilities are both influenced by investors’ risk appetites, such vulnerabilities also depend on economic fundamentals, including the sovereign’s level of government debt.

Erratum: Cascading Failures in Bi-partite Graphs: Model for Systemic Risk Propagation

As economic entities become increasingly interconnected, a shock in a financial network can provoke significant cascading failures throughout the system. To study the systemic risk of financial systems, we create a bi-partite banking network model composed of banks and bank assets and propose a cascading failure model to describe the risk propagation process during crises. We empirically test the model with 2007 US commercial banks balance sheet data and compare the model prediction of the failed banks with the real failed banks after 2007. We find that our model efficiently identifies a significant portion of the actual failed banks reported by Federal Deposit Insurance Corporation. The results suggest that this model could be useful for systemic risk stress testing for financial systems. The model also identifies that commercial rather than residential real estate assets are major culprits for the failure of over 350 US commercial banks during 2008–2011.