• Media type: E-Book
  • Title: Stochastic Default Risk Estimation : Evidence from the South African Financial Market
  • Contributor: Alfeus, Mesias [Author]; Kirsty, Fitzhenry [Author]; Lederer, Alessia [Author]
  • Published: [S.l.]: SSRN, [2022]
  • Extent: 1 Online-Ressource (30 p)
  • Language: English
  • DOI: 10.2139/ssrn.4011771
  • Identifier:
  • Keywords: Default intensity ; unobservable state variables ; CIR ; α-CIR ; extended kalman filtering
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments January 18, 2022 erstellt
  • Description: The present paper provides empirical studies to estimate defaultable bonds in the South African financial market. The main goal is to estimate the unobservable factors affecting bond yields for South African major banks. The maximum likelihood approach is adopted for the estimation methodology. Extended Kalman filtering techniques are employed in order to tackle the situation that the factors cannot be observed directly. Multi-dimensional Cox-Ingersoll-Ross (CIR)-type factor models are considered. Results show that default risk increased sharply in the South African financial market during COVID-19 and the CIR model with jumps exhibits better performance
  • Access State: Open Access