Estimating Asset Correlations from Stock Prices or Default Rates: Which Method is Superior?

Duellmann, Klaus; Küll, Jonathan; Kunisch, Michael

doi:10.2139/ssrn.2794008

Cited by 8 publications

(1 citation statement)

References 7 publications

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“…Equity market data are relative to fundamental asset data, not sparse, easily accessible, cover a long history (especially for companies that have been around before 2008) and could be considered a proxy to the asset prices and, finally, the credit default swaps. Unfortunately, the literature suggests that market equity returns can result in misstated asset returns (see, e.g., Düllmann et al 2008;Laurent et al 2016). However, using directly observed equity prices (compared to illiquid or non-existent corporate credit default spread data) to model default correlations could allow more transparency in understanding and risk managing the magnitude of the movements between obligors.…”

Section: Correlation Assumptionmentioning

confidence: 99%

Emerging Market Default Risk Charge Model

Joseph

2023

JRFM

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In a default event, several obligors simultaneously experience financial difficulty in servicing their debt to the point where the entire market can experience a sudden yet significant jump to a credit default. To help protect lenders against a jump-to-default event, regulators require banks to hold capital equivalent to the default risk charge as a buffer against the losses they may incur. The Basel regulatory committee has articulated and set default risk modelling guidelines to improve comparability amongst banks and enable a consistent bank-wide default risk charge estimation. Emerging markets are unique because they usually have illiquid markets and sparse data. Thus, implementing an emerging market default risk model and, at the same time, complying with the regulatory guidelines can be non-trivial. This research presents a framework for modelling the default risk charge in emerging markets in line with the regulatory requirements. The default correlation model inputs are derived and empirically calibrated using emerging market data. The paper ends with some considerations that regulators, supervisors, and banks can use to get financial institutions to adopt an emerging markets default risk charge model.

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Section: Correlation Assumptionmentioning

confidence: 99%