Multilayer financial networks and systemic importance: Evidence from China

In this paper, we develop a multilayer network structure and reveal the relationship between network structure and systemic risk. Unlike many previous studies, our model considers both liability and cross-holding of shares between financial institutions simultaneously. We propose a new systemic risk measurement by exploring the dynamic mechanism of financial contagion in the multilayer network. We display the network structure of Chinese financial institutions, including connectivity and diversity, and identify the systemic importance of them. We demonstrate that the multilayer network plays a non-linear role in financial risk spreading. Using the panel regression model and several experiment evidences, we show that the systemic risk can be explained more effectively by the linkage diversity more than the connectivity at both the institutional level and the system level. Our results highlight the importance of considering contagion mechanisms that go beyond a simple single-layer network structure.     

Failed bank takeovers and financial stability

Current discussion about the design of bank resolution frameworks suggests that the takeover of a failed bank by an incumbent one has two effects on financial stability. First, the incumbent takeover may boost financial stability by providing bankers with incentives to be solvent so as to profit from their competitors’ failure. Second, the incumbent takeover may spoil financial stability by creating “Systemically Important Financial Institutions”. The innovation of this paper is to capture these two effects in a theoretical model. We show that when incumbent bankers are impatient enough (i.e., they have high discount rates), the second effect prevails over the first one. We discuss the implications of this result for the design of bank resolution policies.     

Measuring systemic importance of financial institutions: An extreme value theory approach

This paper proposes a set of market-based measures on the systemic importance of a financial institution or a group of financial institutions, each designed to capture different aspects of systemic importance of financial institutions. Multivariate extreme value theory approach is used to estimate these measures. Using six big Canadian banks as the proxy for Canadian banking sector, we apply these measures to identify systemically important banks in Canadian banking sector and major risk contributors from international financial institutions to Canadian banking sector. The empirical evidence reveals that (i) the top three banks, RBC Financial Group, TD Bank Financial Group, and Scotiabank, are more systemically important than other banks, while we also find that the size of a financial institution should not be considered as a proxy of systemic importance; (ii) compared to the European and Asian banks, the crashes of the U.S. banks, on average, are the most damaging to Canadian banking sector, while the risk contribution to the Canadian banking sector from Asian banks is quite lower than that from banks in the U.S. and euro area; (iii) the risk contribution to Canadian banking sector exhibits “home bias”, that is, cross-country risk contribution tends to be smaller than domestic risk contribution.     

Econometric measures of connectedness and systemic risk in the finance and insurance sectors

We propose several econometric measures of connectedness based on principal-components analysis and Granger-causality networks, and apply them to the monthly returns of hedge funds, banks, broker/dealers, and insurance companies. We find that all four sectors have become highly interrelated over the past decade, likely increasing the level of systemic risk in the finance and insurance industries through a complex and time-varying network of relationships. These measures can also identify and quantify financial crisis periods, and seem to contain predictive power in out-of-sample tests. Our results show an asymmetry in the degree of connectedness among the four sectors, with banks playing a much more important role in transmitting shocks than other financial institutions.     

Derivatives holdings and systemic risk in the U.S. banking sector

This paper studies the impact of the banks’ portfolio holdings of financial derivatives on the banks’ individual contribution to systemic risk over and above the effect of variables related to size, interconnectedness, substitutability, and other balance sheet information. Using a sample of 95 U.S. bank holding companies from 2002 to 2011, we compare five measures of the banks’ contribution to systemic risk and find that the new measure proposed in this study, Net Shapley Value, outperforms the others. Using this measure we find that banks’ aggregate holdings of five classes of derivatives do not exhibit a significant effect on the bank’s contribution to systemic risk. On the contrary, the banks’ holdings of certain specific types of derivatives such as foreign exchange and credit derivatives increase the banks contributions to systemic risk whereas holdings of interest rate derivatives decrease it. Nevertheless, the proportion of non-performing loans over total loans and the leverage ratio have much stronger impact on systemic risk than derivatives holdings. Therefore, the derivatives’ impact plays a second fiddle in comparison with traditional banking activities related to the former two items.     

Credit information sharing in the nexus between charter value and systemic risk in Asian banking

In this paper, we assess whether the link between charter value and systemic risk in banking is affected by credit information sharing at the country level. Using a sample of Asian listed banks, we document that banks with higher charter value exhibit lower systemic risk because these banks hold more capital. Nevertheless, we find that the self-disciplining role of charter value in banking is more pronounced for countries with lower depth of credit information sharing. Specifically, our findings also reveal that higher charter value alleviates systemic risk and increases capitalization, particularly in countries with lower quality of private credit bureaus. These findings suggest that higher charter value can be detrimental for financial stability due to an increase in bank systemic risk, particularly when private credit bureaus are of better quality. In order to overcome bank systemic risk, this paper advocates the importance of strengthening bank competition to limit charter value, in addition to promoting the development of private credit bureaus.     

Stochastic dominance statistics for risk averters and risk seekers: an analysis of stock preferences for USA and China

Recent research has found a number of scaling law relationships in foreign exchange data. These relationships, estimated using simple ordinary least squares, can be used to forecast losses in foreign exchange time series from as little as one month’s tick data. We compare the loss forecasts from a new scaling law against six parametric Value at Risk models. Compared to these models, the new scaling law is easier to fit, provides more stable forecasts and is very accurate.     

Global systemic risk measures and their forecasting power for systemic events

Since the financial crisis of 2007–2009, many market-based systemic risk measures have been proposed. Prominent examples are MES, SRISK or ΔCoVaR. Based on a simulation study in an extended banking network model that incorporates several sources of systemic risk, we analyze how well these systemic risk measures perform in indicating the risk of a systemic event. For this analysis, the systemic risk measures of the banks that default and whose default is followed by a systemic event are compared with the systemic risk measures of those defaulting banks for which no subsequent systemic event can be observed. Within the simulation study, we find that many bank-individual systemic risk measures are statistically significant in explaining the likelihood of a systemic event after a bank’s default. However, the economic significance of the bank-individual systemic risk measures is relatively low.     

Measuring the systemic importance of interconnected banks

We propose a method for measuring the systemic importance of interconnected banks. In order to capture contributions to system-wide risk, our measure accounts fully for the extent to which a bank (i) propagates shocks across the system and (ii) is vulnerable to propagated shocks. An empirical implementation of this measure and a popular alternative reveals that interconnectedness is a key driver of systemic importance. However, since the two measures reflect the impact of interbank borrowing and lending on system-wide risk differently, they can disagree substantially about the systemic importance of individual banks.     

Market procyclicality and systemic risk

We develop a model that captures, at the same time, the temporal dynamics of single-firm credit risk and the contagion across banks via a network of obligations and common assets. In particular, we enrich the continuous-time modelling approach of default by accounting explicitly for the procyclical loop between asset prices and leverage. Contagion can spread well before any default occurs, through the value of the obligations held by counterparties. Moreover, the extent of procyclicality effects depends explicitly on the structure of both the interbank network and the asset bank network. We analyse the model in a simplified scenario of a densely connected core of banks and we carry out a systematic investigation of how procyclicality emerges from the multiplicative interplay of market illiquidity and tightness of capital requirements.     

Systemic risk and asymmetric responses in the financial industry

To date, an operational measure of systemic risk capturing nonlinear tail-comovements between system-wide and individual bank returns has not yet been developed. This paper proposes an extension of the CoVaR methodology in Adrian and Brunnermeier (2011) to capture the asymmetric response of the banking system to positive and negative shocks to the market-valued balance sheets of individual banks. Building on a comprehensive sample of U.S. banks in the period 1990–2010, the evidence in this paper shows that ignoring asymmetries that feature tail-interdependences may lead to a severe underestimation of systemic risk. On average, the relative impact on the system of a fall in individual market value is sevenfold that of an increase. Moreover, the downward bias in systemic-risk measuring from ignoring this asymmetric pattern increases with bank size. In particular, the conditional tail-comovement between the banking system and a bank that is losing market value belonging to the top size-sorted decile is nearly 5.5 times larger than the unconditional tail-comovement versus 3.3 times for banks in the bottom decile. The asymmetric model also produces much better fitting, with the restriction that gives rise to the standard symmetric model being rejected for most firms in the sample, particularly, in the segment of large-scale banks. This result is important from a regulatory and supervisory perspective, since the asymmetric generalization enhances the capacity to monitor systemic interdependences.     

Good for one,bad for all: Determinants of individual versus systemic risk

We analyze a sample of large international banks in major advanced economies and examine the impact that bank-specific factors have on an institution's solvency risk and its contribution to systemic risk. We focus on the five categories that the Basel Committee on Banking Supervision has recently proposed as indicators of systemic importance. Our findings suggest that unstable funding is the main factor driving systemic risk. Furthermore, the combination of significant trading activities with global presence appears to exacerbate spillover risks to the global financial system. Interestingly, whereas trading activities contribute to the build-up of correlated or ‘wrong-way’ risk they help to mitigate individual solvency risk. Conversely, a decentralized approach to liquidity management seems to alleviate individual solvency risk but amplifies the transmission of financial distress across the financial system. This suggests that a macro-prudential approach to financial regulation should focus not only on scaling up micro-prudential measures but also on enabling the efficient transfer of risk between financial institutions.     

The impact of imposing capital requirements on systemic risk

This paper examines the impact of imposing capital requirements on systemic risk. We use a static model on financial institutions’ risk-taking behavior to quantify the systemic risk in the cross-sectional dimension in both regulated and unregulated systems. Although imposing a capital requirement can lower individual risk, it simultaneously enhances systemic linkage within the system. By using a proper systemic risk measure combining both individual risk and systemic linkage, we show that systemic risk in a regulated system can be higher than that in an unregulated system. In addition, we analyze a sufficient condition under which the systemic risk in a regulated system is always lower.     

Leverage-induced systemic risk under Basle II and other credit risk policies

We use a simple agent based model of value investors in financial markets to test three credit regulation policies. The first is the unregulated case, which only imposes limits on maximum leverage. The second is Basle II and the third is a hypothetical alternative in which banks perfectly hedge all of their leverage-induced risk with options. When compared to the unregulated case both Basle II and the perfect hedge policy reduce the risk of default when leverage is low but increase it when leverage is high. This is because both regulation policies increase the amount of synchronized buying and selling needed to achieve deleveraging, which can destabilize the market. None of these policies are optimal for everyone: risk neutral investors prefer the unregulated case with low maximum leverage, banks prefer the perfect hedge policy, and fund managers prefer the unregulated case with high maximum leverage. No one prefers Basle II.     

Extreme observations and risk assessment in the equity markets of MENA region: Tail measures and Value-at-Risk

The standard “delta-normal” Value-at-Risk methodology requires that the underlying returns generating distribution for the security in question is normally distributed, with moments which can be estimated using historical data and are time-invariant. However, the stylized fact that returns are fat-tailed is likely to lead to under-prediction of both the size of extreme market movements and the frequency with which they occur. In this paper, we use the extreme value theory to analyze four emerging markets belonging to the MENA region (Egypt, Jordan, Morocco, and Turkey). We focus on the tails of the unconditional distribution of returns in each market and provide estimates of their tail index behavior. In the process, we find that the returns have significantly fatter tails than the normal distribution and therefore introduce the extreme value theory. We then estimate the maximum daily loss by computing the Value-at-Risk (VaR) in each market. Consistent with the results from other developing countries [see Gencay, R. and Selcuk, F., (2004). Extreme value theory and Value-at-Risk: relative performance in emerging markets. International Journal of Forecasting, 20, 287–303; Mendes, B., (2000). Computing robust risk measures in emerging equity markets using extreme value theory. Emerging Markets Quarterly, 4, 25–41; Silva, A. and Mendes, B., (2003). Value-at-Risk and extreme returns in Asian stock markets. International Journal of Business, 8, 17–40], generally, we find that the VaR estimates based on the tail index are higher than those based on a normal distribution for all markets, and therefore a proper risk assessment should not neglect the tail behavior in these markets, since that may lead to an improper evaluation of market risk. Our results should be useful to investors, bankers, and fund managers, whose success depends on the ability to forecast stock price movements in these markets and therefore build their portfolios based on these forecasts.     

Derivatives and systemic risk: Netting, collateral, and closeout

In the U.S., as in most countries with well-developed securities markets, derivative securities enjoy special protections under insolvency resolution laws. Most creditors are “stayed” from enforcing their rights while a firm is in bankruptcy. However, many derivatives contracts are exempt from these stays. Furthermore, derivatives enjoy netting and closeout, or termination, privileges which are not always available to most other creditors. The primary argument used to motivate passage of legislation granting these extraordinary protections is that derivatives markets are a major source of systemic risk in financial markets and that netting and closeout reduce this risk. To date, these assertions have not been subjected to rigorous economic scrutiny. This paper critically re-examines this hypothesis. These relationships are more complex than often perceived. We conclude that it is not clear whether netting, collateral, and/or closeout lead to reduced systemic risk, once the impact of these protections on the size and structure of the derivatives market has been taken into account.     

Alternative modeling for long term risk

In this paper, we propose an alternative approach to estimate long-term risk. Instead of using the static square root of time method, we use a dynamic approach based on volatility forecasting by non-linear models. We explore the possibility of improving the estimations using different models and distributions. By comparing the estimations of two risk measures, value at risk and expected shortfall, with different models and innovations at short-, median- and long-term horizon, we find that the best model varies with the forecasting horizon and that the generalized Pareto distribution gives the most conservative estimations with all the models at all the horizons. The empirical results show that the square root method underestimates risk at long horizons and our approach is more competitive for risk estimation over a long term.     

Diversification and systemic risk

Portfolio diversification makes investors individually safer but creates connections between them through common asset holdings. Such connections create “endogenous covariances” between assets and investors, and enhance systemic risk by propagating shocks swiftly through the system. We provide a theoretical model in which shocks spread through constrained selling from N diversified portfolio investors in a network of asset holdings with home bias, and study the desirability of diversification by comparing the multivariate distribution of implied losses for every level of diversification. There may be a region on the parameter set for which the propagation effect dominates the individually safer one. We derive analytically the general element of the covariance between two assets i and j. We find agents may minimize their exposure to endogenous risk by spreading their wealth across more and more distant assets. The resulting network enhances systemic stability.