Credit cycles and macro fundamentals

We study the relation between the credit cycle and macro economic fundamentals in an intensity based framework. Using rating transition and default data of U.S. corporates from Standard and Poor’s over the period 1980–2005 we directly estimate the credit cycle from the micro rating data. We relate this cycle to the business cycle, bank lending conditions, and financial market variables. In line with earlier studies, these variables appear to explain part of the credit cycle. As our main contribution, we test for the correct dynamic specification of these models. In all cases, the hypothesis of correct dynamic specification is strongly rejected. Moreover, accounting for dynamic mis-specification, many of the variables thought to explain the credit cycle, turn out to be insignificant. The main exceptions are GDP growth, and to some extent stock returns and stock return volatilities. Their economic significance appears low, however. This raises the puzzle of what macro-economic fundamentals explain default and rating dynamics. JEL Classification: G11, G2

Risk aversion under preference uncertainty

We show that if an agent is uncertain about the precise form of his utility function, his actual relative risk aversion may depend on wealth even if he knows his utility function lies in the class of constant relative risk aversion (CRRA) utility functions. We illustrate the consequences of this result for asset allocation: poor agents that are uncertain about their risk aversion parameter invest less in risky assets than wealthy investors with identical risk aversion uncertainty. Keywords: Risk Aversion , Preference Uncertainty , Risk-taking , Asset Allocation JEL Classification: D81, D84, G11 This Version: November 25, 201

Credit Cycles and Macro Fundamentals

We study the relation between the credit cycle and macro economic fundamentals in an intensity based framework. Using rating transition and default data of U.S. corporates from Standard and Poor’s over the period 1980–2005 we directly estimate the credit cycle from the micro rating data. We relate this cycle to the business cycle, bank lending conditions, and financial market variables. In line with earlier studies, these variables appear to explain part of the credit cycle. As our main contribution, we test for the correct dynamic specification of these models. In all cases, the hypothesis of correct dynamic specification is strongly rejected. Moreover, accounting for dynamic mis-specification, many of the variables thought to explain the credit cycle, turn out to be insignificant. The main exceptions are GDP growth, and to some extent stock returns and stock return volatilities. Their economic significance appears low, however. This raises the puzzle of what macro-economic fundamentals explain default and rating dynamics.Credit Cycles, Business Cycles, Bank Lending Conditions, Unobserved Component Models, Intensity Models, Monte Carlo Likelihood

Le rôle des chiasmes dans la naissance et la formation de la langue arabe

Le système syllabique Σ, de l’arabe, qui comprend les seules syllabes {Consonne-Voyelle} et {Consonne-Voyelle-Consonne}, a déterminé l’impossibilité, dans le fonctionnement de la langue, de l’opposition d’une consonne à une voyelle. Ce chiasme est à l’origine de l’organisation ancienne des langues sémitiques, régissant, jusqu’à récemment, la langue arabe. Ainsi, la langue arabe a construit son système de nomination sur des arrangements de consonnes, les racines de ses unités de nomination, et elle a fait de ses voyelles désinentielles les signifiants de ses fonctionnels primitifs, ses cas. On relève, parmi d’autres, le chiasme organisant le verbe en deux paradigmes, achevé et non achevé. D’autres encore ont dans la langue l’apparence d’un ornement. Ces quelques cas exceptés, c’est, dans le discours, hors langue – la systématique des langues est une systématique fermée – que la rhétorique trouve la liberté qui lui est nécessaire.The syllabic system, Σ, of the Arabic language is made up of no more than two patterns {Consonant-Vowel} and {Consonant-Vowel-Consonant}. Therefore two given strings of syllables CV and CVC cannot form a pair. There is, inevitably, a double opposition {C vs V}. In that chiasmus lies the organization of all Semitic languages. In the Arabic language that chiastic organization has been maintained until recently. Therefore the Arabic language constructed its system of nomination on combinations of consonants that constitute the roots of its units of nomination. And it used the end vowels of those units as the signifiants of its primitive function words. Another example of a chiasmus is the chiasmus that distinguishes the perfective aspect of Arabic verbs from their imperfective aspect. Some chiasmi occurring in the language seem rhetorical, but such cases are rare. In fact, the systematic organization of the language is a closed one, while the discourse is open. And it is in the discourse that rhetoric finds the liberty that it requires

Why do investors sell losers? How adaptation to losses affects future capitulation decisions

According to disposition effect theory, people hold losing investments too long. However, many investors eventually sell at a loss, and little is known about which psychological factors contribute to these capitulation decisions. This study integrates prospect theory, utility maximization theory, and theory on reference point adaptation to argue that the combination of a negative expectation about an investment’s future performance and a low level of adaptation to previous losses leads to a greater capitulation probability. The test of this hypothesis in a dynamic experimental setting reveals that a larger total loss and longer time spent in a losing position lead to downward adaptations of the reference point. Negative expectations about future investment performance lead to a greater capitulation probability. Consistent with the theoretical framework, empirical evidence supports the relevance of the interaction between adaptation and expectation as a determinant of capitulation decisions. Keywords: Investments , Adaptation , Reference Point , Capitulation , Selling Decisions , Disposition Effect , Financial Markets JEL Classification: D91, D03, D8