Decoding Default Risk: A Review of Modeling Approaches, Findings, and Estimation Methods

Gurdip Bakshi, Xiaohui Gao, Zhaodong Zhong

Research output: Contribution to journalReview articlepeer-review

Abstract

Default risk permeates the behavior of corporate bond returns and spreads, credit default swap spreads, estimation of default probabilities, and loss in default. Pertinent to this review are salient empirical findings and implications of default process estimation from 1974 to 2021. Both structural and reduced-form models are covered. In structural models, default occurs if the value of assets falls below some threshold obligation. The reduced-form models involve assumptions about the default process combined with recovery in default. Default process estimation and measurements of default probability have improved by exploiting data on defaultable bonds, credit default swaps, tally of default realizations, and options on individual equities. Empirical investigations continue to address the relevance of stochastic asset volatility, jumps in asset values, and modeling of default boundary and firm leverage process.

Original languageAmerican English
Pages (from-to)391-413
Number of pages23
JournalAnnual Review of Financial Economics
Volume14
DOIs
StatePublished - Nov 1 2022

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics

Keywords

  • Default
  • default intensity-based credit risk models
  • empirical facts in credit markets
  • model estimation
  • recovery in default
  • structural models

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