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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, G21
We test whether asymmetric preferences for losses versus gains as in Ang, Chen, and Xing (2006) also affect the pricing of cash flow versus discount rate news as in Campbell and Vuolteenaho (2004). We construct a new four-fold beta decomposition, distinguishing cash flow and discount rate betas in up and down markets. Using CRSP data over 1963–2008, we find that the downside cash flow beta and downside discount rate beta carry the largest premia. We subject our result to an extensive number of robustness checks. Overall, downside cash flow risk is priced most consistently across different samples, periods, and return decomposition methods, and is the only component of beta that has significant out-of-sample predictive ability. The downside cash flow risk premium is mainly attributable to small stocks. The risk premium for large stocks appears much more driven by a compensation for symmetric, cash flow related risk. Finally, we multiply our premia estimates by average betas to compute the contribution of the different risk components to realized average returns. We find that up and down discount rate components dominate the contribution to average returns of downside cash flow risk. Keywords: Asset Pricing, Beta, Downside Risk, Upside Risk, Cash Flow Risk, Discount Rate Risk JEL Classification: G11, G12, G14
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, D81
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, 2010
We show that average excess returns during the last two years of the presidential cycle are significantly higher than during the first two years: 9.8 percent over the period 1948 – 2008. This pattern in returns cannot be explained by business-cycle variables capturing time-varying risk premia, differences in risk levels, or by consumer and investor sentiment. In this paper, we formally test the presidential election cycle (PEC) hypothesis as the alternative explanation found in the literature for explaining the presidential cycle anomaly. PEC states that incumbent parties and presidents have an incentive to manipulate the economy (via budget expansions and taxes) to remain in power. We formulate eight empirically testable propositions relating to the fiscal, monetary, tax, unexpected inflation and political implications of the PEC hypothesis. We do not find statistically significant evidence confirming the PEC hypothesis as a plausible explanation for the presidential cycle effect. The existence of the presidential cycle effect in U.S. financial markets thus remains a puzzle that cannot be easily explained by politicians employing their economic influence to remain in power. JEL Classification: E32; G14; P16 Keywords: Political Economy, Market Efficiency, Anomalies, Calendar Effects
This paper analyzes the impact of blockownership dispersion on firm value. Blockholdings by multiple blockholders is a widespread phenomenon in the U.S. market. It is not clear, however, whether dispersion among blockholder is preferable to having a more concentrated ownership structure. To test for the direction of the effect, we use a large dataset of U.S. firms that combines blockholder information, shareholder rights information, debt ratings, accounting information, and financial markets information. We find that a large fraction of aggregated block ownership negatively affects Tobin’s Q. The negative impact is larger if blockowners are more dispersed, suggesting that a concentrated ownership structure is to be preferred on average. Results are robust to controlling for blockholder type as well as proxies for shareholder rights. Our empirical findings are also confirmed if we study the impact of ownership dispersion on firm debt ratings rather than Tobin’s Q. JEL Classification: G3, G32
Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species’ threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.