Meklēšanas opcijas
Home Medijiem Noderīga informācija Pētījumi un publikācijas Statistika Monetārā politika Euro Maksājumi un tirgi Karjera
Ieteikumi
Šķirošanas kritērijs
Latviešu valodas versija nav pieejama

Heinrich Kick

31 August 2021
OCCASIONAL PAPER SERIES - No. 261
Details
Abstract
Asset encumbrance is a central concept in the context of banks’ liquidity crises, as it is associated with their capacity to obtain secured funding. This occasional paper summarises the work carried out by the task force on asset encumbrance, bringing together analyses by the ECB and those national competent authorities working on the topic. First, we describe how asset encumbrance has evolved in euro area banks, focusing on country and business model aggregates. Second, we conduct an econometric analysis of the driving factors of banks’ asset encumbrance, highlighting the relevance of credit risk, the availability of high quality collateral suitable for encumbrance, capital and sovereign funding conditions. Third, we turn our focus to the asset encumbrance dynamics of banks that have experienced a crisis. The outcome of this event study analysis indicates that asset encumbrance increases in the lead-up to a crisis, partly to offset early deposit outflows. Building on these findings, we show that asset encumbrance indicators carry predictive information for bank-specific crises as part of a multivariate early warning model.
JEL Code
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G01 : Financial Economics→General→Financial Crises
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
C23 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Panel Data Models, Spatio-temporal Models
C49 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→Other
22 January 2021
OCCASIONAL PAPER SERIES - No. 254
Details
Abstract
The cost of equity for banks equates to the compensation that market participants demand for investing in and holding banks’ equity, and has important implications for the transmission of monetary policy and for financial stability. Notwithstanding its importance, the cost of equity is unobservable and therefore needs to be estimated. This occasional paper provides estimates of the cost of equity for listed and unlisted euro area banks using a three-step methodology. In the first step, ten different models are estimated. In the second step, the models’ results are combined applying an equal-weighting procedure. In the third step, the combined costs of equity for individual banks are aggregated at the euro area level and according to banks’ business models. The results suggest that, since the Great Financial Crisis of 2007-08, the premia that investors demand to compensate them for the risk they bear when financing banks’ equity has been persistently higher than the return on equity (ROE) generated by banks. We show that our estimates of cost of equity have plausible relationships to banks’ fundamentals. The cost of equity tends to be higher for banks that are riskier (higher non-performing loan ratios), less efficient (higher cost-to-income ratio), and with more unstable funding sources (higher relative reliance on interbank deposits). Finally, we use bank fundamentals to estimate the cost of equity for unlisted banks. In general, unlisted banks are found to have a somewhat lower cost of equity compared to listed banks, with business model characteristics accounting for part of the estimated difference.
JEL Code
G20 : Financial Economics→Financial Institutions and Services→General
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
G1 : Financial Economics→General Financial Markets
24 January 2017
WORKING PAPER SERIES - No. 1992
Details
Abstract
This paper investigates the joint dynamics of nominal bond yields, real bond yields and dividend yields from the 80s up to the aftermath of the financial crisis by mapping them on a set of macro factors. It builds on an existing discrete time affine Gaussian model of the term structure model of nominal bonds, real bonds and equity and extends it by three important innovations. Firstly, allowing for structural shifts in inflation expectations. Secondly, accounting for the relevance of the zero lower bound in the period after 2008 by modelling a so-called shadow rate and deriving asset prices by explicitly considering the zero lower bound. Finally, calculating the standard errors to correctly capture the multi-step nature of the estimation process, which results in substantially larger standard errors than previously reported for the model. We achieve statistically signicant risk premia by imposing restrictions on the matrix of risk premia. Taken together, these modifications allow to better model asset prices also during the financial crisis and the ensuing economic environment of sluggish growth, low inflation rates, interest rates close to zero and quantitative easing.
JEL Code
C13 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Estimation: General
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
9 June 2016
WORKING PAPER SERIES - No. 1920
Details
Abstract
We analyse the SRISK measure with respect to its usage as a benchmark for the ECB/EBA 2014 stress test. By regressing the ECB/EBA stress test impact and the SRISK stress impact on a set of factors that are commonly associated with bank credit losses and bank vulnerability, we find that the ECB/EBA stress impact is consistent with findings in the literature on credit losses. In contrast, the SRISK measure bears much less relation to these factors; it is largely driven by the banks
JEL Code
C21 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Cross-Sectional Models, Spatial Models, Treatment Effect Models, Quantile Regressions
G01 : Financial Economics→General→Financial Crises
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
21 October 2015
WORKING PAPER SERIES - No. 1860
Details
Abstract
Forbearance is a practice of granting concessions to troubled borrowers, typically in the form of prolongation of maturity or refinancing of the loan. While economically useful in some circumstances, it can be used by banks in order to reduce the need for provisions and conceal potential losses. If forbearance is widespread in the banking system, it may result in systemic risk, increasing uncertainty about the quality of banks
JEL Code
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation