On the Determinants of the Implied Default Barrier

We use the maximum likelihood (ML) estimation approach to estimate the default barriers from market values of equities for a sample of 762 public industrial Canadian firms. The ML approach allows us to estimate the asset instantaneous drift, volatility and barrier level simultaneously, when the firm's equity is priced as a Down-and-Out European call (DOC) option. We find that the estimated barrier is positive and significant in our sample. Moreover, we compare the default prediction accuracy of the DOC framework with the KMV-Merton approach. Using probit estimation, we find that the default probability from the two structural models provides similar in-sample fits, but the barrier option framework achieves better out-of-sample forecasts. Regression analysis shows that leverage is not the only determinant of the default barrier. The implied default threshold is also positively related to financing costs, and negatively to liquidity, asset volatility and firm size. We also find that liquidation costs, renegotiation frictions and equity holders' bargaining power increase the implied default barrier level.Barrier option, default barrier, bankruptcy prediction, maximum likelihood estimation, strategic default

On the Determinants of the Implied Default Barrier

We use the maximum likelihood (ML) estimation approach to estimate the default barriers from market values of equities for a sample of 762 public industrial Canadian firms. The ML approach allows us to estimate the asset instantaneous drift, volatility and barrier level simultaneously, when the firm’s equity is priced as a Down-and-Out European call (DOC) option. We find that the estimated barrier is positive and significant in our sample. Moreover, we compare the default prediction accuracy of the DOC framework with the KMV-Merton approach. Using probit estimation, we find that the default probability from the two structural models provides similar in-sample fits, but the barrier option framework achieves better out-of-sample forecasts. Regression analysis shows that leverage is not the only determinant of the default barrier. The implied default threshold is also positively related to financing costs, and negatively to liquidity, asset volatility and firm size. We also find that liquidation costs, renegotiation frictions and equity holders’ bargaining power increase the implied default barrier level

Estimation of the Default Risk of Publicly Traded Canadian Companies

In this paper, we investigate the hybrid contingent claim approach with publicly traded Canadian companies listed on the Toronto Stock Exchange. Our goal is to assess how combining their continuous valuation by the market with the value given in their financial statements improves our ability to predict their probability of default. Our results indicate that the predicted structural probabilities of default (PDs from the structural model) contribute significantly to explaining default probabilities when PDs are included alongside the retained accounting variables. We also show that quarterly updates to the PDs add a large amount of dynamic information to explain the probabilities of default over the course of a year. This flexibility would not be possible with a reduced-form model. We also conducted a preliminary analysis of correlations between sructural probabilities of default for the firms in our database. Our results indicate that there are substantial correlations in the studied data.Default risk, public firm, structural model, reduced form model, hybrid model, probit model, Toronto Stock Exchange, correlations between default probabilities

Estimation of the Default Risk of Publicly Traded Canadian Companies

Two models of default risk are prominent in the financial literature: Merton's structural model and Altman's non-structural model. Merton's structural model has the benefit of being responsive, since the probabilities of default can continually be updated with the evolution of firms' asset values. Its main flaw lies in the fact that it may over- or underestimate the probabilities of default, since asset values are unobservable and must be extrapolated from the share prices. Altman's nonstructural model, on the other hand, is more precise, since it uses firms' accounting data-but it is less flexible. In this paper, the authors investigate the hybrid contingent claims approach with publicly traded Canadian companies listed on the Toronto Stock Exchange. The authors' goal is to assess how their ability to predict companies' probability of default is improved by combining the companies' continuous market valuation (structural model) with the value given in their financial statements (non-structural model). The authors' results indicate that the predicted structural probabilities of default (PDs from the structural model) contribute significantly to explaining default probabilities when PDs are included alongside the retained accounting variables in the hybrid model. The authors also show that quarterly updates to the PDs add a large amount of dynamic information to explain the probabilities of default over the course of a year. This flexibility would not be possible with a non-structural model. The authors conduct a preliminary analysis of correlations between structural probabilities of default for the firms in their database. Their results indicate that there are substantial correlations in the studied data.Debt management; Credit and credit aggregates; Financial markets; Recent economic and financial developments; Econometric and statistical methods

Structural Credit Risk Models: A Review

In this paper, the author reviews the literature on credit structural models. Contingent claim analysis offers an appealing theoretical framework allowing not only evaluating firm’s claims and default risk, but also financing and investment decisions, as well as determining the impact of policy changes on the firm value and decisions. First, we present the major structural models and their underlying assumptions, beginning with exogenous default models and the following development leading to endogenous default models as well as other models that accounts for bankruptcy procedures, capital structure decisions and strategic defaults among others. The second part of the paper covers the empirical works related to the structural credit models. These works could be classified into three major categories: the first group examines the ability of structural models to explain the credit spread, the second one evaluate their performance to forecast default occurrence, the last group uses the structural models to study the relationship between credit risk and stock returns.Dans ce papier, l’auteur revoit la littérature sur les modèles structurels de crédit. Du côté théorique, les modèles d’analyse d’actifs contingents procurent un cadre qui permet non seulement la valorisation des actifs de l’entreprise et son risque de défaut, mais aussi les décisions d’investissement et de financement ainsi que leur impact sur la valeur de l’entreprise et ses décisions.Dans la première partie, nous présentons les principaux modèles structurels, leurs hypothèses sous-jacentes, à commencer par les modèles à défaut exogènes et les développements subséquents qui ont mené aux modèles de défaut endogènes, ainsi que l’intégration des procédures de faillite, les décisions de structure de capital et les décisions de défaut stratégiques et d’autres développements. La deuxième partie est consacrée aux recherches empiriques. Ces travaux empiriques peuvent être classés en trois groupes. Le premier examine la capacité de différents modèles structurels à expliquer les écarts de crédit. Le deuxième groupe évalue la performance de ces modèles dans la prévision des défauts. Finalement, certains travaux utilisent les modèles structurels pour étudier la relation entre le risque de crédit de l’entreprise et la performance boursière de ses actions