Robustness of Distance-to-Default

Cathrine Jessen, David Lando

Publikation: Kapitel i bog/rapport/konferenceprocesKonferencebidrag i proceedingsForskningpeer review

Resumé

Distance-to-default is a remarkably robust measure for ranking firms according to their risk of default. The ranking seems to work despite the fact that the Merton model from which the measure is derived produces default probabilities that are far too small when applied to real data. We use simulations to investigate the robustness of the distance-to-default measure to different model specifications. Overall we find distance-to-default to be robust to a number of deviations from the simple Merton model that involve different asset value dynamics and different default triggering mechanisms. A notable exception is a model with stochastic volatility of assets. In this case both the ranking of firms and the estimated default probabilities using distance-to-default perform significantly worse. We therefore propose a volatility adjustment of the distance-to-default measure, that significantly improves the ranking of firms with stochastic volatility.
Distance-to-default is a remarkably robust measure for ranking firms according to their risk of default. The ranking seems to work despite the fact that the Merton model from which the measure is derived produces default probabilities that are far too small when applied to real data. We use simulations to investigate the robustness of the distance-to-default measure to different model specifications. Overall we find distance-to-default to be robust to a number of deviations from the simple Merton model that involve different asset value dynamics and different default triggering mechanisms. A notable exception is a model with stochastic volatility of assets. In this case both the ranking of firms and the estimated default probabilities using distance-to-default perform significantly worse. We therefore propose a volatility adjustment of the distance-to-default measure, that significantly improves the ranking of firms with stochastic volatility.

Konference

KonferenceThe 26th Australasian Finance and Banking Conference 2013
Nummer26
LokationShangri-la Hotel
LandAustralien
BySydney
Periode17/12/201319/12/2013
Internetadresse

Emneord

  • Default risk
  • Default prediction
  • Distance-to-default
  • Stochastic volatility

Citer dette

Jessen, C., & Lando, D. (2013). Robustness of Distance-to-Default. I F. Moshirian (red.), 26th Australasian Finance & Banking Conference 2013 Sydney: UNSW Australia Business School. DOI: 10.2139/ssrn.2311228
Jessen, Cathrine ; Lando, David. / Robustness of Distance-to-Default. 26th Australasian Finance & Banking Conference 2013. red. / Fariborz Moshirian. Sydney : UNSW Australia Business School, 2013.
@inproceedings{bf9b5e7217634fc1a4d814e12d13924b,
title = "Robustness of Distance-to-Default",
abstract = "Distance-to-default is a remarkably robust measure for ranking firms according to their risk of default. The ranking seems to work despite the fact that the Merton model from which the measure is derived produces default probabilities that are far too small when applied to real data. We use simulations to investigate the robustness of the distance-to-default measure to different model specifications. Overall we find distance-to-default to be robust to a number of deviations from the simple Merton model that involve different asset value dynamics and different default triggering mechanisms. A notable exception is a model with stochastic volatility of assets. In this case both the ranking of firms and the estimated default probabilities using distance-to-default perform significantly worse. We therefore propose a volatility adjustment of the distance-to-default measure, that significantly improves the ranking of firms with stochastic volatility.",
keywords = "Default risk, Default prediction, Distance-to-default, Stochastic volatility",
author = "Cathrine Jessen and David Lando",
year = "2013",
doi = "10.2139/ssrn.2311228",
language = "English",
isbn = "9780987312754",
editor = "Fariborz Moshirian",
booktitle = "26th Australasian Finance & Banking Conference 2013",
publisher = "UNSW Australia Business School",
address = "Australia",

}

Jessen, C & Lando, D 2013, Robustness of Distance-to-Default. i F Moshirian (red.), 26th Australasian Finance & Banking Conference 2013. UNSW Australia Business School, Sydney, The 26th Australasian Finance and Banking Conference 2013, Sydney, Australien, 17/12/2013. DOI: 10.2139/ssrn.2311228

Robustness of Distance-to-Default. / Jessen, Cathrine; Lando, David.

26th Australasian Finance & Banking Conference 2013. red. / Fariborz Moshirian. Sydney : UNSW Australia Business School, 2013.

Publikation: Kapitel i bog/rapport/konferenceprocesKonferencebidrag i proceedingsForskningpeer review

TY - GEN

T1 - Robustness of Distance-to-Default

AU - Jessen,Cathrine

AU - Lando,David

PY - 2013

Y1 - 2013

N2 - Distance-to-default is a remarkably robust measure for ranking firms according to their risk of default. The ranking seems to work despite the fact that the Merton model from which the measure is derived produces default probabilities that are far too small when applied to real data. We use simulations to investigate the robustness of the distance-to-default measure to different model specifications. Overall we find distance-to-default to be robust to a number of deviations from the simple Merton model that involve different asset value dynamics and different default triggering mechanisms. A notable exception is a model with stochastic volatility of assets. In this case both the ranking of firms and the estimated default probabilities using distance-to-default perform significantly worse. We therefore propose a volatility adjustment of the distance-to-default measure, that significantly improves the ranking of firms with stochastic volatility.

AB - Distance-to-default is a remarkably robust measure for ranking firms according to their risk of default. The ranking seems to work despite the fact that the Merton model from which the measure is derived produces default probabilities that are far too small when applied to real data. We use simulations to investigate the robustness of the distance-to-default measure to different model specifications. Overall we find distance-to-default to be robust to a number of deviations from the simple Merton model that involve different asset value dynamics and different default triggering mechanisms. A notable exception is a model with stochastic volatility of assets. In this case both the ranking of firms and the estimated default probabilities using distance-to-default perform significantly worse. We therefore propose a volatility adjustment of the distance-to-default measure, that significantly improves the ranking of firms with stochastic volatility.

KW - Default risk

KW - Default prediction

KW - Distance-to-default

KW - Stochastic volatility

U2 - 10.2139/ssrn.2311228

DO - 10.2139/ssrn.2311228

M3 - Article in proceedings

SN - 9780987312754

BT - 26th Australasian Finance & Banking Conference 2013

PB - UNSW Australia Business School

CY - Sydney

ER -

Jessen C, Lando D. Robustness of Distance-to-Default. I Moshirian F, red., 26th Australasian Finance & Banking Conference 2013. Sydney: UNSW Australia Business School. 2013. Tilgængelig fra, DOI: 10.2139/ssrn.2311228