Volatility clustering, with autocorrelations of the hyperbolic decay rate, is unquestionably one of the most important stylized facts of financial time series. This paper presents a market microstructure model that is able to generate volatility clustering with hyperbolically decaying autocorrelations via traders with multiple trading frequencies, using Bayesian information updates in an incomplete market. The model illustrates that signal extraction, which is induced by multiple trading frequencies, can increase the persistence of the volatility of returns. Furthermore, we show that the volatility of the underlying time series of returns varies greatly with the number of traders in the market.

This study examines the role of Chinese state ownership in deterring takeovers. We document state ownership’s reduction in firms’ susceptibility to potential takeovers. Using staggered privatization of the state-owned shareholders of public firms, as shocks to the deterrent effect of the state, we find that state-owned shareholders can insulate their portfolio firms from potential takeovers. The deterrent effect of state ownership is concentrated in strategic industries and well-functioning assets, alleviating managerial short-termism.

Counterparty risk is an important determinant of corporate credit spreads. However, there are only a few techniques available to isolate it from other factors. In this paper we describe a model of financial networks that is suitable for the construction of proxies for counterparty risk. Using data on North American supplier–customer network of public companies, we find that, for each supplier, counterparties’ leverage and option implied volatilities are significant determinants of corporate credit spreads in the period after the 2008–2009 U.S. recession. Our findings are robust after controlling for several idiosyncratic, industry, and market factors.

We consider a financial network where banks are heterogeneous in scale and each bank has only local knowledge regarding the network. Each bank must make counterparty and portfolio decisions while anticipating uncertainty regarding the network structure. Such network uncertainty is an important consideration in banks’ risk management practice, which aims to minimize the effect of exogenous liquidity shocks and hedge against possible fire-sale in asset markets. We show that network uncertainty gives rise to an endogenous core-periphery structure which is optimal in mitigating financial contagion yet concentrates systemic risk at the core of big banks.