Paul Bochmann - Academia.edu (original) (raw)
Papers by Paul Bochmann
Social Science Research Network, 2023
We propose new dynamic models for the dependence structure of high-dimensional nancial data. The ... more We propose new dynamic models for the dependence structure of high-dimensional nancial data. The models are based on recently proposed factor copula models, which we augment with regime-switching dynamics. We apply the proposed models to a data set of eight major European government debt indices and a Euro Area nancial sector index to study government debt systemic risk for the nancial sector. As a systemic risk measure we employ a multivariate extension of the CoVaR measure, which takes distress spillovers among government debt markets into account and which we characterize through copulas. We nd that a model with multiple skewed and asymmetric common factors and regime-switching dynamics is able to describe the time-variation and non-normal features of the dependence structure of our data well. Our results show a distinct dierence in Euro Area government debt systemic risk prior to the nancial crisis and thereafter, induced by a regime change in the dependence structure. We nd that at the height of the nancial crisis the government debt markets of Portugal, Italy, Ireland, Greece and Spain become positively dependent with the nancial sector and imply positive systemic risk, whereas the government debt markets of Germany, France and the Netherlands continue to imply negative systemic risk. The total systemic risk, implied by joint distress of all eight debt markets, is highest shortly after the Lehman brothers default and peaks again in the second half of 2011. Contents II 6 Conclusion References Contents III List of Abbreviations AIC Akaike information criterion ARCH autoregressive conditional heteroscedasticity ARMA autoregressive moving average BIC bayesian information criterion cdf cumulative distribution function CoVaR conditional Value-at-Risk DCC dynamic conditional correlation EMU European Monetary Union GARCH generalized autoregressive conditional heteroscedasticity
Social Science Research Network, 2021
Disclaimer: This paper should not be reported as representing the views of the European Central B... more Disclaimer: This paper should not be reported as representing the views of the European Central Bank (ECB). The views expressed are those of the authors and do not necessarily reflect those of the ECB.
Social Science Research Network, 2022
Social Science Research Network, 2023
Macroprudential Bulletin, Jun 28, 2021
Macroprudential Bulletin, Oct 19, 2020
Financial Stability Review, 2019
In dieser Arbeit werden neue dynamische Modelle fur die Copula von hoch-dimensionalen Finanzmarkt... more In dieser Arbeit werden neue dynamische Modelle fur die Copula von hoch-dimensionalen Finanzmarktdatensatzen entwickelt. Die Modelle basieren auf kurzlich entwickelten Faktor-Copula-Modellen, welche wir um regime-switching dynamics erweitern. Wir wenden die Modelle auf einen Datensatz bestehend aus Renditen von acht europaischen Staatsanleihen und einem Finanzmarktindex fur die Eurozone an, um systemisches Risiko von Staatsanleihenmarkten fur den Finanzsektor zu untersuchen. Als Mas fur systemisches Risiko verwenden wir eine multivariate Erweiterung des CoVaR Mases, welches Spillover-Effekte zwischen Staatsanleihenmarkten berucksichtigt und welches wir durch Copulas charakterisieren. Unsere Ergebnisse zeigen deutliche Unterschiede des systemischen Risikos von Staatsanleihenmarkten fur den Finanzsektor vor und nach der Finanzkrise, hervorgerufen durch einen Regimewechsel in der Copula. Wir zeigen, dass die Staatsanleihenmarkte von Portugal, Italien, Irland, Griechenland und Spanien a...
Risk Management & Analysis in Financial Institutions eJournal, 2017
How do capital and liquidity buffers affect the evolution of bank loans in periods of financial a... more How do capital and liquidity buffers affect the evolution of bank loans in periods of financial and economic distress? To answer this question we study the responses of 219 individual banks to aggregate demand, standard and unconventional monetary policy shocks in the euro area between 2007 and 2015. Banks’ responses are derived from a factor-augmented VAR, which relates macroeconomic aggregates to individual bank balance sheet items and interest rates. We find that banks with high capital and liquidity buffers show a more muted response in their lending to adverse real economy shocks. Capital and liquidity buffers also affect bank responses to monetary policy shocks. High bank capitalisation reduces the degree to which banks increase the average duration of loans to the non-financial corporate sector, while high bank liquidity strengthens the positive response to policy easing of both longand short-term loans to the non-financial corporate sector. The latter findings substantiate t...
SSRN Electronic Journal
The cost of equity for banks equates to the compensation that market participants demand for inve... more 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 Classification: G20, G21, E44, G1
Social Science Research Network, 2023
We propose new dynamic models for the dependence structure of high-dimensional nancial data. The ... more We propose new dynamic models for the dependence structure of high-dimensional nancial data. The models are based on recently proposed factor copula models, which we augment with regime-switching dynamics. We apply the proposed models to a data set of eight major European government debt indices and a Euro Area nancial sector index to study government debt systemic risk for the nancial sector. As a systemic risk measure we employ a multivariate extension of the CoVaR measure, which takes distress spillovers among government debt markets into account and which we characterize through copulas. We nd that a model with multiple skewed and asymmetric common factors and regime-switching dynamics is able to describe the time-variation and non-normal features of the dependence structure of our data well. Our results show a distinct dierence in Euro Area government debt systemic risk prior to the nancial crisis and thereafter, induced by a regime change in the dependence structure. We nd that at the height of the nancial crisis the government debt markets of Portugal, Italy, Ireland, Greece and Spain become positively dependent with the nancial sector and imply positive systemic risk, whereas the government debt markets of Germany, France and the Netherlands continue to imply negative systemic risk. The total systemic risk, implied by joint distress of all eight debt markets, is highest shortly after the Lehman brothers default and peaks again in the second half of 2011. Contents II 6 Conclusion References Contents III List of Abbreviations AIC Akaike information criterion ARCH autoregressive conditional heteroscedasticity ARMA autoregressive moving average BIC bayesian information criterion cdf cumulative distribution function CoVaR conditional Value-at-Risk DCC dynamic conditional correlation EMU European Monetary Union GARCH generalized autoregressive conditional heteroscedasticity
Social Science Research Network, 2021
Disclaimer: This paper should not be reported as representing the views of the European Central B... more Disclaimer: This paper should not be reported as representing the views of the European Central Bank (ECB). The views expressed are those of the authors and do not necessarily reflect those of the ECB.
Social Science Research Network, 2022
Social Science Research Network, 2023
Macroprudential Bulletin, Jun 28, 2021
Macroprudential Bulletin, Oct 19, 2020
Financial Stability Review, 2019
In dieser Arbeit werden neue dynamische Modelle fur die Copula von hoch-dimensionalen Finanzmarkt... more In dieser Arbeit werden neue dynamische Modelle fur die Copula von hoch-dimensionalen Finanzmarktdatensatzen entwickelt. Die Modelle basieren auf kurzlich entwickelten Faktor-Copula-Modellen, welche wir um regime-switching dynamics erweitern. Wir wenden die Modelle auf einen Datensatz bestehend aus Renditen von acht europaischen Staatsanleihen und einem Finanzmarktindex fur die Eurozone an, um systemisches Risiko von Staatsanleihenmarkten fur den Finanzsektor zu untersuchen. Als Mas fur systemisches Risiko verwenden wir eine multivariate Erweiterung des CoVaR Mases, welches Spillover-Effekte zwischen Staatsanleihenmarkten berucksichtigt und welches wir durch Copulas charakterisieren. Unsere Ergebnisse zeigen deutliche Unterschiede des systemischen Risikos von Staatsanleihenmarkten fur den Finanzsektor vor und nach der Finanzkrise, hervorgerufen durch einen Regimewechsel in der Copula. Wir zeigen, dass die Staatsanleihenmarkte von Portugal, Italien, Irland, Griechenland und Spanien a...
Risk Management & Analysis in Financial Institutions eJournal, 2017
How do capital and liquidity buffers affect the evolution of bank loans in periods of financial a... more How do capital and liquidity buffers affect the evolution of bank loans in periods of financial and economic distress? To answer this question we study the responses of 219 individual banks to aggregate demand, standard and unconventional monetary policy shocks in the euro area between 2007 and 2015. Banks’ responses are derived from a factor-augmented VAR, which relates macroeconomic aggregates to individual bank balance sheet items and interest rates. We find that banks with high capital and liquidity buffers show a more muted response in their lending to adverse real economy shocks. Capital and liquidity buffers also affect bank responses to monetary policy shocks. High bank capitalisation reduces the degree to which banks increase the average duration of loans to the non-financial corporate sector, while high bank liquidity strengthens the positive response to policy easing of both longand short-term loans to the non-financial corporate sector. The latter findings substantiate t...
SSRN Electronic Journal
The cost of equity for banks equates to the compensation that market participants demand for inve... more 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 Classification: G20, G21, E44, G1