34 research outputs found
Do Heterogeneous Beliefs Matter for Asset Pricing?
We study how heterogeneous beliefs affect returns and examine whether heterogeneous beliefs are a priced factor in traditional asset pricing models. To accomplish this task, we suggest new empirical measures based on the disagreement among analysts about expected (short-term and long-term) earnings are good proxies. Having established that heterogeneity of beliefs matters for asset pricing we turn our attention to estimating a structural model in which we use the forecasts of financial analysts to proxy for the beliefs of agents. Finally, we investigate if the amount of heterogeneity in analysts' forecasts can help explain asset pricing puzzlesHeterogeneous Beliefs, Asset pricing
The impact of risk and uncertainty on expected returns☆
We study asset pricing when agents face risk and uncertainty and empirically demonstrate that uncertainty has a substantial effect on asset prices. We measure risk with past volatility and uncertainty with the degree of disagreement of professional forecasters, attributing different weights to each forecaster. We run regressions representing the typical risk-return trade-off and augment these regressions with a measure of uncertainty. We find stronger empirical evidence for a uncertainty-return trade-off than for the traditional risk-return trade-off. We investigate the performance of a two-factor model with risk and uncertainty in the cross-section
A theoretical foundation for multi-scale regular vegetation patterns
Self-organized regular vegetation patterns are widespread and thought to mediate ecosystem functions such as productivity and robustness, but the mechanisms underlying their origin and maintenance remain disputed. Particularly controversial are landscapes of overdispersed (evenly spaced) elements, such as North American Mima mounds, Brazilian murundus, South African heuweltjies, and, famously, Namibian fairy circles. Two competing hypotheses are currently debated. On the one hand, models of scale-dependent feedbacks, whereby plants facilitate neighbours while competing with distant individuals, can reproduce various regular patterns identified in satellite imagery. Owing to deep theoretical roots and apparent generality, scale-dependent feedbacks are widely viewed as a unifying and near-universal principle of regular-pattern formation despite scant empirical evidence. On the other hand, many overdispersed vegetation patterns worldwide have been attributed to subterranean ecosystem engineers such as termites, ants, and rodents. Although potentially consistent with territorial competition, this interpretation has been challenged theoretically and empirically and (unlike scale-dependent feedbacks) lacks a unifying dynamical theory, fuelling scepticism about its plausibility and generality. Here we provide a general theoretical foundation for self-organization of social-insect colonies, validated using data from four continents, which demonstrates that intraspecific competition between territorial animals can generate the large-scale hexagonal regularity of these patterns. However, this mechanism is not mutually exclusive with scale-dependent feedbacks. Using Namib Desert fairy circles as a case study, we present field data showing that these landscapes exhibit multi-scale patterning-previously undocumented in this system-that cannot be explained by either mechanism in isolation. These multi-scale patterns and other emergent properties, such as enhanced resistance to and recovery from drought, instead arise from dynamic interactions in our theoretical framework, which couples both mechanisms. The potentially global extent of animal-induced regularity in vegetation-which can modulate other patterning processes in functionally important ways-emphasizes the need to integrate multiple mechanisms of ecological self-organization
Somatic mutations affect key pathways in lung adenocarcinoma
Determining the genetic basis of cancer requires comprehensive analyses of large collections of histopathologically well- classified primary tumours. Here we report the results of a collaborative study to discover somatic mutations in 188 human lung adenocarcinomas. DNA sequencing of 623 genes with known or potential relationships to cancer revealed more than 1,000 somatic mutations across the samples. Our analysis identified 26 genes that are mutated at significantly high frequencies and thus are probably involved in carcinogenesis. The frequently mutated genes include tyrosine kinases, among them the EGFR homologue ERBB4; multiple ephrin receptor genes, notably EPHA3; vascular endothelial growth factor receptor KDR; and NTRK genes. These data provide evidence of somatic mutations in primary lung adenocarcinoma for several tumour suppressor genes involved in other cancers - including NF1, APC, RB1 and ATM - and for sequence changes in PTPRD as well as the frequently deleted gene LRP1B. The observed mutational profiles correlate with clinical features, smoking status and DNA repair defects. These results are reinforced by data integration including single nucleotide polymorphism array and gene expression array. Our findings shed further light on several important signalling pathways involved in lung adenocarcinoma, and suggest new molecular targets for treatment.National Human Genome Research InstituteWe thank A. Lash, M.F. Zakowski, M.G. Kris and V. Rusch for intellectual contributions, and many members of the Baylor Human Genome Sequencing Center, the Broad Institute of Harvard and MIT, and the Genome Center at Washington University for support. This work was funded by grants from the National Human Genome Research Institute to E.S.L., R.A.G. and R.K.W.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62885/1/nature07423.pd
Do Heterogeneous Beliefs Matter for Asset Pricing?
We study how heterogeneous beliefs affect returns and examine whether they are a priced factor in traditional asset pricing models. To accomplish this task, we suggest new empirical measures based on the disagreement among analysts about expected earnings (short-term and long-term) and show they are good proxies. We first establish that the heterogeneity of beliefs matters for asset pricing and then turn our attention to estimating a structural model in which we use the forecasts of financial analysts to proxy for agents' beliefs. Finally, we investigate whether the amount of heterogeneity in analysts' forecasts can help explain asset pricing puzzles. Copyright 2005, Oxford University Press.
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