Yves S. Schüler
- 5 August 2022
- WORKING PAPER SERIES - No. 2698Details
- Abstract
- We propose the CoJPoD, a novel framework explicitly linking the cross-sectional and cyclical dimensions of systemic risk. In this framework, banking sector distress in the form of the joint probability of default of financial intermediaries (reflecting contagion from both direct and indirect interconnectedness) is conditioned on the financial cycle (reflecting the buildup and unwinding of system-wide balance sheet leverage). An empirical application to large systemic banks in the euro area, US and UK illustrates how the unravelling of excess leverage can magnify banking sector distress. Capturing this dependence of banking sector distress on prevailing financial imbalances can enhance risk surveillance and stress testing alike. An empirical signaling exercise confirms that the CoJPoD outperforms the individual capacity of either its unconditional counterpart or the financial cycle in signaling financial crises – particularly around their onset – suggesting scope to increase the precision with which macroprudential policies are calibrated.
- JEL Code
- C19 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Other
C54 : Mathematical and Quantitative Methods→Econometric Modeling→Quantitative Policy Modeling
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G01 : Financial Economics→General→Financial Crises
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
- 28 March 2018
- WORKING PAPER SERIES - No. 2138Details
- Abstract
- I show that the detrending of financial variables with the Hodrick and Prescott (1981, 1997) (HP) and band-pass filters leads to spurious cycles. I find that distortions become especially severe when considering medium-term cycles, i.e., cycles that exceed the duration of regular business cycles. In particular, these medium-term filters amplify the variances of cycles of duration around 20 to 30 years up to a factor of 204, completely cancelling out shorter-term fluctuations. This is important because it is common practice, and recommended under Basel III, to extract medium-term cycles using such filters; e.g., the HP filter with a smoothing parameter of 400,000. In addition, I find that financial cycle facts, i.e., differing amplitude, duration, and synchronisation of cycles in financial variables relative to cycles in GDP, are robust. For HP and band-pass filters, differences to GDP become marginal due to spurious cycles.
- JEL Code
- C10 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→General
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G01 : Financial Economics→General→Financial Crises
- 14 September 2015
- WORKING PAPER SERIES - No. 1846Details
- Abstract
- We introduce a methodology to characterise financial cycles combining a novel multivariate spectral approach to identifying common cycle frequencies across a set of indicators, and a time varying aggregation emphasising systemic developments. The methodology is applied to 13 European Union countries as well a synthetic euro area aggregate, based on a quarterly dataset spanning 1970-2013. Results suggest that credit and asset prices share cyclical similarities, which, captured by a synthetic financial cycle, outperform the credit-to-GDP gap in predicting systemic banking crises on a horizon of up to three years. Financial cycles tend to be long, particularly in upswing phases and with important dispersion across country cases. Concordance of financial and business cycles is observed only 2/3 of the time. While a similar degree of concordance for financial cycles is apparent across countries, heterogeneity is high
- JEL Code
- E30 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→General
E40 : Macroeconomics and Monetary Economics→Money and Interest Rates→General
C54 : Mathematical and Quantitative Methods→Econometric Modeling→Quantitative Policy Modeling
- 27 November 2014
- FINANCIAL STABILITY REVIEW - ARTICLEFinancial Stability Review Issue 2, 2014Details
- Abstract
- This special feature discusses ways of measuring financial cycles for macro-prudential policymaking. It presents some estimates and empirical characteristics of financial cycles. Existing studies on financial cycle measurement remain quite nascent in comparison with the voluminous literature on business cycles. In this context, two approaches – turning point and spectral analysis – are used to capture financial and business cycles at the country level. The results of the empirical analysis suggest that financial cycles tend to be more volatile than business cycles in the euro area, albeit with strong cross-country heterogeneity. Both aspects underscore the relevance of robust financial cycle estimates for macro-prudential policy design in euro area countries.
- JEL Code
- G00 : Financial Economics→General→General