Robustness of Distance-to-Default

Cathrine Jessen, David Lando

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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.
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.

Conference

ConferenceThe 26th Australasian Finance and Banking Conference 2013
Number26
LocationShangri-la Hotel
CountryAustralia
CitySydney
Period17/12/201319/12/2013
Internet address

Keywords

    Cite this

    Jessen, C., & Lando, D. (2013). Robustness of Distance-to-Default. In F. Moshirian (Ed.), 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. editor / 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",
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    }

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

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

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

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-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. In Moshirian F, editor, 26th Australasian Finance & Banking Conference 2013. Sydney: UNSW Australia Business School. 2013. Available from, DOI: 10.2139/ssrn.2311228