What Explains Herd Behavior in the Chinese Stock Market?

This article examines the causes of herd behavior in the Chinese stock market. Using the nonlinear model of Chang, Cheng, and Khorana [2000 Chang, E. C., J. W. Cheng, and A. Khorana. “An Examination of Herd Behavior in Equity Markets: An International Perspective.” Journal of Banking and Finance, 24, (2000), pp. 1651–1679.[Crossref], [Web of Science ®] , [Google Scholar]], the authors of this article find robust evidence of herding in both the up and down markets. They contribute to the existing literature by exploring the underlying reasons for herding in China. It is shown that analyst recommendation, short-term investor horizon, and risk are the principal causes of herding. However, the authors cannot find evidence that relates herding to firm size, nor can they detect significant differences in herding between state-owned enterprises and non–state-owned enterprises.     

A model of a systemic bank run

This paper provides a model of the view that the 2008 financial crisis is reminiscent of a bank run, focussing on six stylized key features. In particular, core financial institutions have invested their funds in asset-backed securities rather than committed to long-term projects: in distress, these can potentially be sold to a large pool of outside investors at steep discounts. I consider two different motives for outside investors and their interaction with banks trading asset-backed securities: uncertainty aversion versus adverse selection. I shall argue that the version with uncertainty averse investors is more consistent with the stylized facts than the adverse selection perspective: in the former, the crisis deepens, the larger the market share of distressed core banks, while a run becomes less likely instead as a result in the adverse selection version. Therefore, the outright purchase of troubled assets by the government at prices above current market prices may both alleviate the financial crises as well as provide tax payers with returns above those for safe securities.     

Systemic banks and the lender of last resort

We propose a model where systemic and non-systemic banks are exposed to liquidity shortfalls so that a lender of last resort policy is required. We find that it is socially optimal to override the decision of the central bank by the unconditional provision of liquidity support when the shortfall is large enough, i.e. in crisis times. The existence of systemic banks provides a rationale for the central bank to act as lender of last resort for non-systemic banks in a larger range of their liquidity shortfalls. However, the impact of systemic risk on the optimal allocation of the lender of last resort responsibilities for systemic banks depends on the relative size of counteracting effects.     

What is the systemic risk exposure of financial institutions?

I compare the performance of three measures of institution-level systemic risk exposure — Exposure CoVaR (Adrian and Brunnermeier, 2016), systemic expected shortfall (Acharya et al., 2016), and Granger causality (Billio et al., 2012). I modify Exposure CoVaR to allow for forecasting, and estimate the ability of each measure to forecast the performance of financial institutions during systemic crisis periods in 1998 (LTCM) and 2008 (Lehman Brothers). I find that Exposure CoVaR forecasts the within-crisis performance of financial institutions, and provides useful forecasts of future systemic risk exposures. Systemic expected shortfall and Granger causality do not forecast the performance of financial institutions reliably during crises. I also find, using cross-sectional regressions, that foreign equity exposure and securitization income determine systemic risk exposure during the 1998 and 2008 crises, respectively; financial institution size determines systemic risk exposure during both crisis periods; and executive compensation does not determine systemic risk exposure.     

Systemic risk in an interconnected banking system with endogenous asset markets

We analyze the emergence of systemic risk in a network model of interconnected bank balance sheets. The model incorporates multiple sources of systemic risk, including size of financial institutions, direct exposure from interbank lendings, and asset fire sales. We suggest a new macroprudential risk management approach building on a system wide value at risk (SVaR). Under the SVaR metric, the contribution of individual banks to systemic risk is well defined and can be approximated by a Shapley value-type measure. We show that, in a SVaR regime, a fair systemic risk charge which is proportional to a bank's individual contribution to systemic risk diverges from the optimal macroprudential capitalization of the banks from a planner's perspective. The results have implications for the design of macroprudential capital surcharges.     

Systemic risk spillovers in the European banking and sovereign network

We propose a framework for estimating time-varying systemic risk contributions that is applicable to a high-dimensional and interconnected financial system. Tail risk dependencies and systemic risk contributions are estimated using a penalized two-stage fixed-effects quantile approach, which explicitly links time-varying interconnectedness to systemic risk contributions. For the purposes of surveillance and regulation of financial systems, network dependencies in extreme risks are more relevant than simple (mean) correlations. Thus, the framework provides a tool for supervisors, reflecting the market's view of tail dependences and systemic risk contributions. The model is applied to a system of 51 large European banks and 17 sovereigns during the period from 2006 through 2013, utilizing both equity and CDS prices. We provide new evidence on how banking sector fragmentation and sovereign-bank linkages evolved over the European sovereign debt crisis, and how they are reflected in estimated network statistics and systemic risk measures. Finally, our evidence provides an indication that the fragmentation of the European financial system has peaked.     

Systemic risk of insurers around the globe

We study the exposure and contribution of 253 international life and non-life insurers to systemic risk between 2000 and 2012. For our full sample period, we find systemic risk in the international insurance sector to be small. In contrast, the contribution of insurers to the fragility of the financial system peaked during the recent financial crisis. In our panel regressions, we find the interconnectedness of large insurers with the insurance sector to be a significant driver of the insurers’ exposure to systemic risk. In contrast, the contribution of insurers to systemic risk appears to be primarily driven by the insurers’ leverage.     

What is the net effect of financial liberalization on bank productivity? A decomposition analysis of bank total factor productivity growth

We employ a unique framework to quantify the net effect of financial liberalization on banks’ total factor productivity (TFP) growth through a decomposition analysis of two effects: a positive direct effect of financial liberalization on bank TFP growth; and a negative indirect effect operating through a higher propensity to systemic banking crisis. The empirical decomposition is based on a sample of 1530 banks operating in 88 countries over the period 1999–2011. We find that the net effect of financial liberalization on bank TFP growth is positive: the direct positive effect outweighs the negative one. An important policy implication flows from these findings.     

Testing macroprudential stress tests: The risk of regulatory risk weights

We compare the capital shortfall measured by regulatory stress tests, to that of a benchmark methodology — the “V-Lab stress test” — that employs only publicly available market data. We find that when capital shortfalls are measured relative to risk-weighted assets, the ranking of financial institutions is not well correlated to the ranking of the V-Lab stress test, whereas rank correlations increase when required capitalization is a function of total assets. We show that the risk measures used in risk-weighted assets are cross-sectionally uncorrelated with market measures of risk, as they do not account for the “risk that risk will change.” Furthermore, the banks that appeared to be best capitalized relative to risk-weighted assets were no better than the rest when the European economy deteriorated into the sovereign debt crisis in 2011.     

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.