Asset Volatility

Correia, Maria; Kang, Johnny; Richardson, Scott

doi:10.2139/ssrn.2361686

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Estimating Value Relevance1

Calibration Of the Merton Model1

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Cited by 13 publications

(4 citation statements)

References 30 publications

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“…7 CART is part of a family of decision tree-based estimation methods that can increase explanatory power relative to traditional linear methods, detect relative importance of explanatory variables, and uncover nonlinearities and interactions in the marginal relations between the independent and dependent variables (Breiman 2001). These methods are used in a variety of non-accounting research settings, including facial recognition, spam e-mail detection, and disease diagnosis (see Verikas, Gelzinis, and Bacauskiene 2011 for a review), and in accounting research (Gerakos, Hahn, Kovrijynkh, and Zhou 2016;Beaver, Cascino, Correia, and McNichols 2017;Correia, Kang, and Richardson 2017;Jones 2017).…”

Section: Estimating Value Relevancementioning

confidence: 99%

Evolution in Value Relevance of Accounting Information

2017

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Section: Estimating Value Relevancementioning

confidence: 99%

Evolution in Value Relevance of Accounting Information

2017

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“…Results are insensitive to other reasonable choices of values for L>0.75. See alsoCorreia, Kang, and Richardson (2014) for an assessment of different approaches to calculating asset volatility.…”

mentioning

confidence: 99%

The Myth of the Credit Spread Puzzle

Feldhütter

Schaefer

2018

The Review of Financial Studies

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Are standard structural models able to explain credit spreads on corporate bonds? In contrast to much of the literature, we find that the Black-Cox model matches the level of investmentgrade spreads well. Model spreads for speculative-grade debt are too low, and we find that bond illiquidity contributes to this underpricing. Our analysis makes use of a new approach for calibrating the model to historical default rates that leads to more precise estimates of investment-grade default probabilities. (JEL C23, G12, G13)

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“…Our dataset consist of actual transactions which are unevenly spaced in time and constructing a return series is considerably more difficult. See also Correia, Kang, and Richardson (2014) for an assesment of different approaches to calculating asset volatility.…”

Section: Calibration Of the Merton Modelmentioning

confidence: 99%