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Trevor Fitzpatrick

29 September 2006
We combine the dynamic dividend-discount model with an accounting-based vector autoregression framework that allows for a decomposition of EU banks' stock returns to cash-flow and expected return news components. The main findings are that while the bulk of the variability of EU banks' stock returns is due to cash flow shocks, the expected return shocks are relatively more important for larger than for smaller banks. Moroever, variables used in the literature as cash-flow proxies explain a higher share of the cash-flow component of the total excess returns for smaller than for larger EU banks. This suggests that large banks could be more prone to market wide news and events - that in the literature are associated with the expected return news component - as opposed to the bank-specific news, typically assumed to be incorporated in the cash-flow component.
JEL Code
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
9 January 2009
The first part of this paper provides a brief survey of the recent literature that employs survey data on household finance and consumption. Given the breadth of the topic, it focuses on issues that are particularly relevant for policy, namely: i) wealth effects on consumption, ii) housing prices and household indebtedness, iii) retirement income, consumption and pension reforms, iv) access to credit and credit constraints, v) financial innovation, consumption smoothing and portfolio selection and vi) wealth inequality. The second part uses concrete examples to summarise how results from such surveys feed into policy-making within the central banks that already conduct such surveys.
JEL Code
C42 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→Survey Methods
D12 : Microeconomics→Household Behavior and Family Economics→Consumer Economics: Empirical Analysis
D14 : Microeconomics→Household Behavior and Family Economics→Household Saving; Personal Finance
Eurosystem Monetary Transmission Network
11 February 2009
In terms of regulatory and economic capital, credit risk is the most significant risk faced by banks. We implement a credit risk model - based on publicly available information - with the aim of developing a tool to monitor credit risk in a sample of large and complex banking groups (LCBGs) in the EU. The results indicate varying credit risk profiles across these LCBGs and over time. Furthermore, the results show that large negative shocks to real GDP have the largest impact on the credit risk profiles of banks in the sample. Notwithstanding some caveats, the results demonstrate the potential value of this approach for monitoring financial stability.
JEL Code
C02 : Mathematical and Quantitative Methods→General→Mathematical Methods
C19 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Other
C52 : Mathematical and Quantitative Methods→Econometric Modeling→Model Evaluation, Validation, and Selection
C61 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Optimization Techniques, Programming Models, Dynamic Analysis
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles