Essays on corporate risk and capital structure
Notice bibliographique
Résumé
This dissertation consists of two essays and five chapters. The first essay in chapter two addresses the zero-leverage puzzle, the observation that many firms do not issue debt and thus seem to forego sizable debt benefits. Based on the trade-off theory, a firm financed with debt saves on taxes, while it faces the debt costs associated with financial distress. Firms issue debt and net a positive gain by trading off costs and benefits. However, zero-levered firms seemingly ignore significant tax advantages associated with debt financing. I propose that this behavior is due to the value in waiting to issue debt and postponing debt costs. By considering the real option of issuing debt, small and risky firms have incentives to postpone debt issuance, even when standard trade-off theory predicts that these firms should have leverage. Thus, the value of debt-free firms should include an option component whose value is derived from future debt issuance benefits. I present a simple model for a firm's optimal issuance with optimal leverage and default, and find the factors that increase the propensity to remain zero-levered: high volatility, high debt costs, low tax levels, low payout rate, and small size. I verify the factors empirically on a sample of zero-leverage (ZL) firms by estimating a survival and a choice model and an out-of-sample test on levered firms.The second essay in chapter three provides an explanation for the underleverage puzzle by relating it to volatility risk premia. As a stylized fact, many firms have lower leverage compared to what the trade-off theory predicts, in particular based on their low asset volatility. In addition, the underleverage is the highest for Investment-Grade (IG) firms. Without volatility risk, the essay empirically documents that underleverage across firms increases with volatility risk premium at the asset level. The result is the motive to present two models with stochastic asset volatility that feature optimal capital structure. With priced asset volatility risk, the models in standard trade-off settings show that a higher premium implies lower leverage; the assets' Variance Risk Premia (VRP) reduce tax benefits and increase debt costs. Empirically, the models' calibration leaves no significant underleverage patterns in the cross-section of the firms. Thus, seemingly underleveraged firms have high asset volatility risk premia relative to their low physical asset volatility, which explains their apparent underleverage. In particular, the largest proportion of the volatility is systematic for IG firms; and, consequently, VRP are the highest. This in turn leads to a lower implied leverage, close to the IG firms' empirical leverage.Chapter four reviews the literature related to the earlier chapters. Chapter five concludes with the main findings and provides venues for the future research.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».