Funding liquidity risk has played a key role in all historical banking crises. Nevertheless, a measure for funding liquidity risk based on publicly available data remains so far elusive. We address this gap by showing that aggressive bidding at central bank auctions reveals funding liquidity risk. We can extract an insurance premium from banks’ bids which we propose as a measure of funding liquidity risk. Using a unique data set consisting of all bids in all auctions for the main refinancing operation conducted at the ECB between June 2005 and October 2008 we find that funding liquidity risk is typically stable and low, with occasional spikes especially around key events during the recent crisis. We also document downward spirals between funding liquidity risk and market liquidity. As measurement without clear definitions is impossible, we initially provide definitions of funding liquidity and funding liquidity risk.

Credit and interest rate risk are the two most important risks faced by commercial banks in their banking book. In this paper we derive a consistent and comprehensive framework to measure the integrated impact of both risks. By taking account of the repricing characteristics of assets, liabilities and off balance sheet items, we assess the integrated impact of credit and interest rate risk on banks’ economic value and capital adequacy. We then stress test a hypothetical but realistic bank using our framework and show that it is fundamental to measure the impact of credit and interest rate risk jointly.

Banks often measure credit and interest rate risk in the banking book separately and then add the risk measures to determine economic capital. This approach misses complex interactions between the two risk types. We develop a framework where these risks are analysed jointly. Since banking book positions are generally not marked to market, our model is based on book value accounting. Our simulations show that interactions matter, and that ignoring them leads to risk overstatement. The magnitude of the errors depends on the structure of the balance sheet and on the repricing characteristics of assets and liabilities.

We report results of an Internet experiment designed to test the theory of informational cascades in financial markets (Christopher Avery and Peter Zemsky, 1998). More than 6,400 subjects, including a subsample of 267 consultants from an international consulting firm, participated in the experiment. We find that the presence of a flexible market price prevents herding. The presence of contrarian behavior distorts prices, however, and even after 20 decisions, convergence to the fundamental value is rare. We also report some interesting differences with respect to subjects' fields of study. Reassuringly, the behavior of the consultants turns out to be not significantly different from that of the remaining subjects.