We develop a multivariate unobserved components model to extract business cycle and financial cycle indicators from a panel of economic and financial time series of four large developed economies. Our model is flexible and allows for the inclusion of cycle components in different selections of...

We model and measure simultaneous large losses of the market value of insurers to understand the impact of shocks on the insurance sector. The downside risk of insurers is explicitly modelled by common and idiosyncratic risk factors. Since reinsurance is important for the capacity of insurers,...

We develop Hawkes models in which events are triggered through self as well as cross-excitation. We examine whether incorporating cross-excitation improves the forecasts of extremes in asset returns compared to only self-excitation. The models are applied to US stocks, bonds and dollar exchange...

Does demand for safety create instability ? Secured (repo) funding can be made so safe that it never runs, but shifts risk to unsecured creditors. We show that this triggers more frequent runs by unsecured creditors, even in the absence of fundamental risk. This effect is separate from the...

We experimentally investigate how price expectations are formed in a large asset market where subjects' only task is to forecast the future price of a risky asset. The realized prices depend on these expectations. We observe small (6 participants) and large markets (about 100 participants). In...

Can a wealth shift to emerging countries explain instability in developed countries? Investors exposed to political risk seek safety in countries with better property right protection. This induces private intermediaries to offer safety via inexpensive demandable debt, and increase lending into...

We propose various specification tests for Hawkes models based on the Lagrange Multiplier (LM) principle. Hawkes models can be used to model the occurrence of extreme events in financial markets. Our specific testing focus is on extending a univariate model to a multivariate model, that is, we...

Crowded trades by similarly trading peers influence the dynamics of asset prices, possibly creating systemic risk. We propose a market clustering measure using granular trading data. For each stock the clustering measure captures the degree of trading overlap among any two investors in that...

We empirically investigate why wholesale funding is fragile by providing the first study of how individual banks borrow and lend in the euro unsecured and secured interbank market. Consistent with theories in which lenders enforce market discipline by monitoring counterparty credit risk and...

We introduce a new model for time-varying spatial dependence. The model extends the well-known static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the...