Mortgages: estimating default correlation and forecasting default risk
Tobias Neumann ()
Additional contact information
Tobias Neumann: Bank of England, Postal: Bank of England, Threadneedle Street, London, EC2R 8AH
No 708, Bank of England working papers from Bank of England
Default correlation is a key driver of credit risk. In the Basel regulatory framework it is measured by the asset value correlation parameter. Though past studies suggest that the parameter is over-calibrated for mortgages — generally the largest asset class on banks’ balance sheets — they do not take into account bias arising from small samples or non-Gaussian risk factors. Adjusting for these biases using a non-Gaussian, non-linear state space model I find that the Basel calibration is appropriate for UK and US mortgages. This model also forecasts mortgage default rates accurately and parsimoniously. The model generates value-at-risk estimates for future mortgage default rates, which can be used to inform stress-testing and macroprudential policy.
Keywords: Mortgages; bank regulation; credit risk; default correlation; state space model; Basel Committee; stress testing; macroprudential policy (search for similar items in EconPapers)
JEL-codes: G11 G17 G21 G28 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ban, nep-for, nep-mac, nep-rmg and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
https://www.bankofengland.co.uk/-/media/boe/files/ ... C3789F4B1D2079EEF177 Full text (application/pdf)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:boe:boeewp:0708
Access Statistics for this paper
More papers in Bank of England working papers from Bank of England Bank of England, Threadneedle Street, London, EC2R 8AH. Contact information at EDIRC.
Bibliographic data for series maintained by Digital Media Team ().