Stochastic Default Risk Estimation: Evidence from the South African Financial Market

30 Pages Posted: 15 Mar 2022

See all articles by Mesias Alfeus

Mesias Alfeus

Department of Statistics and Actuarial Science - Stellenbosch University

Fitzhenry Kirsty

Stellenbosch University

Alessia Lederer

Stellenbosch University

Date Written: January 18, 2022

Abstract

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.

Keywords: Default intensity, unobservable state variables, CIR, α-CIR, extended kalman filtering

JEL Classification: C6, C63, G1, G13

Suggested Citation

Alfeus, Mesias and Kirsty, Fitzhenry and Lederer, Alessia, Stochastic Default Risk Estimation: Evidence from the South African Financial Market (January 18, 2022). Available at SSRN: https://ssrn.com/abstract=4011771 or http://dx.doi.org/10.2139/ssrn.4011771

Mesias Alfeus (Contact Author)

Department of Statistics and Actuarial Science - Stellenbosch University ( email )

Matieland
m
Stellenbosch, 7602
South Africa
0633236629 (Phone)
7405 (Fax)

Fitzhenry Kirsty

Stellenbosch University ( email )

Carl Cronje Dr, Bellville, Cape Town, 7530, South
Cape Town, 7530

Alessia Lederer

Stellenbosch University ( email )

Carl Cronje Dr, Bellville, Cape Town, 7530, South
Cape Town, 7530

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