This paper investigates the relationship between the two major sources of bank default risk: liquidity risk and credit risk. We use a sample of virtually all US commercial banks during the period 1998–2010 to analyze the relationship between these two risk sources on the bank institutional-level and how this relationship influences banks’ probabilities of default (PD). Our results show that both risk categories do not have an economically meaningful reciprocal contemporaneous or time-lagged relationship. However, they do influence banks’ probability of default. This effect is twofold: whereas both risks separately increase the PD, the influence of their interaction depends on the overall level of bank risk and can either aggravate or mitigate default risk. These results provide new insights into the understanding of bank risk and serve as an underpinning for recent regulatory efforts aimed at strengthening banks (joint) risk management of liquidity and credit risks

Little progress has been made so far in addressing—in a comprehensive way—the negative externalities caused by excessive maturity transformation and the implications for effective liquidity regulation of banks. The SRL model combines option pricing theory with market information and balance sheet data to generate probabilistic measure of systemic liquidity risk. It enhances price-based liquidity regulation by linking a bank’s maturity mismatch impacting the stability of its funding with those characteristics of other banks, subject to individual changes in risk profiles and common changes in market conditions impacting funding and market liquidity risk. This approach can then be used (i) to quantify an individual institution’s time-varying contribution to expected losses from system-wide liquidity shortfalls and (ii) to price insurance premia that provide incentives for banks to internalize the social cost of their individual funding decisions

The global financial crisis highlighted that the financial system can be most vulnerable when it seems most stable. This paper models non-linear dynamics in banking. Small shocks can lead from an equilibrium with few bank defaults straight to a full freeze. The mechanism is based on amplification between adverse selection on banks’ funding market and moral hazard in bank monitoring. Our results imply trade-offs between regulators’ microprudential desire to shield individual weak banks and the macroprudential consequences of doing so. Moreover, limiting bank reliance on wholesale funding always reduces systemic risk, but limiting the correlation between bank portfolios does not

Should central banks lend against low quality collateral? We characterize efficient central bank collateral policy in a model where a bank borrows from the interbank market or the central bank. Collateral has favorable incentive effects but is costly to transfer to lenders who value the collateral less because of imperfect collateral quality. We show that a fall in the quantity or the quality of the bank’s collateral can increase interest rates in the economy even with a constant policy rate. A looser central bank collateral policy can reduce the spread, alleviate the credit crunch and increase output

This paper investigates the consequences of the liquidity shocks in wholesale funding markets during the 2007–2009 financial crisis on bank lending and corporate financing. We show that banks that relied more heavily on wholesale funding contracted lending more severely than banks that relied more on insured deposits. We then examine the effects of loan contraction on the financial positions of publicly traded firms. We find that both during and after the crisis, the change in leverage of bank-dependent firms is less than that of firms with access to public debt markets. In addition, bank-dependent firms rely more on cash than net equity issuance to finance operations. We also find that firms with established bank lending relationships weather the crisis better. Such firms are able to attain higher levels of leverage during the crisis, add to their cash holdings, secure new bank credit, and achieve higher profitability as a result

New liquidity rules phased in under Basel III define the new net stable funding ratio (NSFR) to promote sustainable funding structures at financial institutions. In this paper, we analyze characteristics and drivers of NSFR for a sample of 921 Western European banks between 1996 and 2010. We find that a majority of banks have historically not fulfilled NSFR minimum requirements, in particular larger and faster growing institutions as well as banks also active in asset management and investment banking. Many of them have started increasing NSFR with the onset of financial crisis 2008 while this ratio had been sliding in earlier years. Interestingly, potential advantages in funding costs for low NSFR banks do not seem to translate into higher profitability and results of these banks are more volatile

Central banks (CBs) in Europe and the US have been providing virtually unlimited amounts of liquidity to banks for quite some time now. This may lead banks to expect that these CBs will be lenient in the future. Will this expectation be justified? I present a model in which a commercial bank, subject to idiosyncratic liquidity shocks, faces uncertainty about whether the CB is tough (Hawk) or lenient (Dove). Specifically, the CB knows its nature, but the bank does not. When uncertainty is high, the CB can use this to its advantage and try to build a reputation for toughness. In response, the bank chooses higher liquidity reserves in equilibrium. Furthermore, increasing bank capital and penalty rates make it easier to build a reputation, while bailouts by the fiscal government make it more difficult

We examine the implications of the sovereign debt tensions on the Italian credit market by estimating the effect of the 10-year BTP-Bund spread on a wide array of bank interest rates, categories of loans and income statement variables. We exploit the heterogeneity between large and small intermediaries to assess to what extent the transmission of sovereign risk differed in relation with different banks’ balance-sheet characteristics and business strategies. Regarding the cost of funding, we find that changes in the BTP-Bund spread have a sizeable effect on the interest rates on term deposits and newly issued bonds but virtually no effect on overnight deposits. Furthermore, the sovereign spread significantly affects the cost of credit for firms and households and exerts a negative effect on loan growth. All these results are magnified when considering alone the five largest banks, which are typically less capitalized, have a larger funding gap and incidence of bad loans and rely more on non-traditional banking activities. Sovereign tensions also affect the main items of banks’ income statement

We present a comprehensive analysis to calculate the Basel III liquidity coverage ratio (LCR) and the net stable funding ratio (NSFR) of U.S. commercial banks using Call Report data over the period 2001–2011, and provide indirect empirical evidence on net cash outflow rates of certain liability categories. In addition, we examine potential links between Basel III liquidity risk measures and bank failures using a model that differentiates between idiosyncratic and systemic liquidity risks. We find that while both the NSFR and the LCR have limited effects on bank failures, the systemic liquidity risk is a major contributor to bank failures in 2009 and 2010. This finding suggests that an effective framework of liquidity risk management needs to target liquidity risk at both the individual level and the system level

Systemic banking crises have placed enormous pressure on national governments to intervene. The empirical literature, however, is inconclusive on what an optimal bailout program should look like to mitigate the negative consequences of government interventions in the banking sector. We find that, in general government interventions have a negative impact on banking sector stability, significantly increasing its risk. In particular, we find that among bailout measures, nationalization and asset management companies (AMCs) contribute most to the risk effect and that among liquidity support mechanisms, public guarantees are the largest contributor to the risk effect. However, we also find that by making an appropriate choice of intervention mechanisms, governments can mitigate the negative consequences stemming from the above-mentioned effects