Cyclicality in Losses on Bank Loans
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- Bart Keijsers & Bart Diris & Erik Kole, 2018. "Cyclicality in losses on bank loans," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 533-552, June.
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- Drew Creal & Bernd Schwaab & Siem Jan Koopman & Andr� Lucas, 2014.
"Observation-Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk,"
The Review of Economics and Statistics, MIT Press, vol. 96(5), pages 898-915, December.
- Drew Creal & Bernd Schwaab & Siem Jan Koopman & Andre Lucas, 2011. "Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk," Tinbergen Institute Discussion Papers 11-042/2/DSF16, Tinbergen Institute.
- Schwaab, Bernd & Koopman, Siem Jan & Lucas, André & Creal, Drew, 2013. "Observation driven mixed-measurement dynamic factor models with an application to credit risk," Working Paper Series 1626, European Central Bank.
- Duffie, Darrell & Saita, Leandro & Wang, Ke, 2007.
"Multi-period corporate default prediction with stochastic covariates,"
Journal of Financial Economics, Elsevier, vol. 83(3), pages 635-665, March.
- Darrel Duffie & Leandro Saita & Ke Wang, 2005. "Multi-Period Corporate Default Prediction With Stochastic Covariates," CIRJE F-Series CIRJE-F-373, CIRJE, Faculty of Economics, University of Tokyo.
- Darrel Duffie & Leandro Saita & Ke Wang, 2005. "Multi-Period Corporate Default Prediction With Stochastic Covariates," CARF F-Series CARF-F-047, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
- Darrell Duffie & Leandro Siata & Ke Wang, 2006. "Multi-Period Corporate Default Prediction With Stochastic Covariates," NBER Working Papers 11962, National Bureau of Economic Research, Inc.
- Pesaran, M. Hashem & Schuermann, Til & Treutler, Bjorn-Jakob & Weiner, Scott M., 2006.
"Macroeconomic Dynamics and Credit Risk: A Global Perspective,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1211-1261, August.
- M. Hashem Pesaran & Til Schuermann & Björn-Jakob Treutler & Scott M. Weiner & April, "undated". "Macroeconomic Dynamics and Credit Risk: A Global Perspective," Center for Financial Institutions Working Papers 03-13, Wharton School Center for Financial Institutions, University of Pennsylvania.
- Til Schuermann & Björn-Jakob Treutler & Scott M. Weiner & M. Hashem Pesaran, 2003. "Macroeconomic Dynamics and Credit Risk: A Global Perspective," CESifo Working Paper Series 995, CESifo.
- Pesaran, M.H. & Schuermann, T. & Treutler, B-J. & Weiner, S.M., 2003. "Macroeconomic Dynamics and Credit Risk: A Global Perspective," Cambridge Working Papers in Economics 0330, Faculty of Economics, University of Cambridge.
- R. H. Shumway & D. S. Stoffer, 1982. "An Approach To Time Series Smoothing And Forecasting Using The Em Algorithm," Journal of Time Series Analysis, Wiley Blackwell, vol. 3(4), pages 253-264, July.
- Calabrese, Raffaella & Zenga, Michele, 2010. "Bank loan recovery rates: Measuring and nonparametric density estimation," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 903-911, May.
- Ben S. Bernanke & Mark Gertler & Mark Watson, 1997.
"Systematic Monetary Policy and the Effects of Oil Price Shocks,"
Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 28(1), pages 91-157.
- Bernanke, Ben S. & Gertler, Mark & Waston, Mark, 1997. "Systematic Monetary Policy and the Effects of Oil Price Shocks," Working Papers 97-25, C.V. Starr Center for Applied Economics, New York University.
- Ben S. Bernanke & Mark Gertler & Mark W. Watson, 1997. "Systematic Monetary Policy and the Effects of Oil Price Shocks," Working Papers 1997-1, Princeton University. Economics Department..
- Basso, Rodrigo M. & Lachos, Víctor H. & Cabral, Celso Rômulo Barbosa & Ghosh, Pulak, 2010. "Robust mixture modeling based on scale mixtures of skew-normal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 2926-2941, December.
- Bruche, Max & González-Aguado, Carlos, 2010.
"Recovery rates, default probabilities, and the credit cycle,"
Journal of Banking & Finance, Elsevier, vol. 34(4), pages 754-764, April.
- Carlos González-Aguado & Max Bruche, 2006. "Recovery Rates, Default Probabilities and the Credit Cycle," FMG Discussion Papers dp572, Financial Markets Group.
- Bruche, Max & Gonzalez-Aguado, Carlos, 2006. "Recovery rates, default probabilities and the credit cycle," LSE Research Online Documents on Economics 24524, London School of Economics and Political Science, LSE Library.
- Max Bruche & Carlos González-Aguado, 2006. "Recovery Rates, Default Probabilities and the Credit Cycle," Working Papers wp2006_0612, CEMFI.
- Edward I. Altman & Brooks Brady & Andrea Resti & Andrea Sironi, 2005. "The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2203-2228, November.
- Durbin, James & Koopman, Siem Jan, 2012.
"Time Series Analysis by State Space Methods,"
OUP Catalogue,
Oxford University Press,
edition 2, number 9780199641178.
- Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543.
- Raffaella Calabrese, 2014. "Predicting bank loan recovery rates with a mixed continuous‐discrete model," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 30(2), pages 99-114, March.
- Grunert, Jens & Weber, Martin, 2009. "Recovery rates of commercial lending: Empirical evidence for German companies," Journal of Banking & Finance, Elsevier, vol. 33(3), pages 505-513, March.
- Borus Jungbacker & Siem Jan Koopman, 2007. "Monte Carlo Estimation for Nonlinear Non-Gaussian State Space Models," Biometrika, Biometrika Trust, vol. 94(4), pages 827-839.
- Hartmann-Wendels, Thomas & Miller, Patrick & Töws, Eugen, 2014. "Loss given default for leasing: Parametric and nonparametric estimations," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 364-375.
- Calabrese, Raffaella, 2014. "Downturn Loss Given Default: Mixture distribution estimation," European Journal of Operational Research, Elsevier, vol. 237(1), pages 271-277.
- Martin Knaup & Wolf Wagner, 2012. "A Market-Based Measure of Credit Portfolio Quality and Banks' Performance During the Subprime Crisis," Management Science, INFORMS, vol. 58(8), pages 1423-1437, August.
- Watson, Mark W. & Engle, Robert F., 1983. "Alternative algorithms for the estimation of dynamic factor, mimic and varying coefficient regression models," Journal of Econometrics, Elsevier, vol. 23(3), pages 385-400, December.
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- Kashif Abbass & Abdul Aziz Khan Niazi & Abdul Basit & Tehmina Fiaz Qazi & Huaming Song & Halima Begum, 2021. "Uncovering Effects of Hot Potatoes in Banking System: Arresting Die-Hard Issues," SAGE Open, , vol. 11(4), pages 21582440211, December.
- Jean-David Fermanian, 2020. "On the Dependence between Default Risk and Recovery Rates in Structural Models," Annals of Economics and Statistics, GENES, issue 140, pages 45-82.
- Aleksey Min & Matthias Scherer & Amelie Schischke & Rudi Zagst, 2020. "Modeling Recovery Rates of Small- and Medium-Sized Entities in the US," Mathematics, MDPI, vol. 8(11), pages 1-18, October.
- Betz, Jennifer & Kellner, Ralf & Rösch, Daniel, 2018. "Systematic Effects among Loss Given Defaults and their Implications on Downturn Estimation," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1113-1144.
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More about this item
Keywords
Loss-given-default; default rates; credit risk; capital requirements; dynamic factor models;All these keywords.
JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
- G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BAN-2015-05-16 (Banking)
- NEP-CFN-2015-05-16 (Corporate Finance)
- NEP-RMG-2015-05-16 (Risk Management)
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