Showing 1 - 7 of 7
We study the effect of a bond's place in its issuer's maturity structure on credit risk. Using a structural model as motivation, we argue that bonds due relatively late in their issuers' maturity structure have greater credit risk than do bonds due relatively early. Empirically, we find robust...
Persistent link: https://www.econbiz.de/10011968837
Using a structural model of default, we construct a measure of systemic default defined as the probability that many firms default at the same time. We account for correlations in defaults between firms through exposures to common shocks. The systemic default measure spikes during recession...
Persistent link: https://www.econbiz.de/10011810905
This paper investigates predictions of structural credit risk models for interest rate sensitivities of corporate bond returns. Recent evidence has shown that the existing models fail to capture this sensitivity (a stylized fact referred to as the interest rate sensitivity puzzle). We propose...
Persistent link: https://www.econbiz.de/10011810957
We document a strong positive cross-sectional relation between corporate bond yield spreads and bond return volatilities. As corporate bond prices are generally attributable to both credit risk and illiquidity as discussed in Huang and Huang (2012), we apply a decomposition methodology to...
Persistent link: https://www.econbiz.de/10011772268
with the view that growth options provide a hedge against macroeconomic uncertainty, we find evidence that the relation is … weaker for firms with more growth options …
Persistent link: https://www.econbiz.de/10011962224
Since 1965, average idiosyncratic risk (IR) has never been lower than in recent years. In contrast to the high IR in the late 1990s that has drawn considerable attention in the literature, average market-model IR is 44% lower in 2013-2017 than in 1996-2000. Macroeconomic variables help explain...
Persistent link: https://www.econbiz.de/10011969105
This paper documents a persistent structure in cryptocurrency returns and analyzes a broad set of characteristics that explain this structure. The results show that similarities in size, trading volume, age, consensus mechanism, and token industries drive the structure of cryptocurrency returns....
Persistent link: https://www.econbiz.de/10012216714