227 research outputs found

    Information and ambiguity: herd and contrarian behaviour in financial markets

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    “The final publication is available at Springer via http://dx.doi.org/10.1007/s11238-012-9334-3”The paper studies the impact of informational ambiguity on behalf of informed traders on history-dependent price behaviour in a model of sequential trading in nancial markets. Following Chateauneuf, Eichberger and Grant (2006), we use neo-additive capacities to model ambiguity. Such ambiguity and attitudes to it can engender herd and contrarian behaviour, and also cause the market to break down. The latter, herd and contrarian behaviour, can be reduced by the existence of a bid-ask spread.Research in part funded by ESRC grant RES-000-22-0650

    Photochemistry Of Monochloro Complexes Of Copper(ii) In Methanol Probed By Ultrafast Transient Absorption Spectroscopy

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    Ultrafast transient absorption spectra in the deep to near UV range (212-384 nm) were measured for the [Cu-II(MeOH)(5)Cl](+) complexes in methanol following 255-nm excitation of the complex into the ligand-to-metal charge-transfer excited state. The electronically excited complex undergoes sub-200 fs radiationless decay, predominantly via back electron transfer, to the hot electronic ground state followed by fast vibrational relaxation on a 0.4-4 Ps time scale. A minor photochemical channel is Cu-Cl bond dissociation, leading to the reduction of copper(H) to copper(I) and the formation of MeOH center dot Cl charge-transfer complexes. The depletion of ground-state [Cu-II(MeOH)(5)Cl](+) perturbs the equilibrium between several forms of copper(II) complexes present in solution. Complete re-equilibration between [Cu-II(MeOH)(5)Cl](+) and [Cu-II(MeOH)(4)Cl-2] is established on a 10-500 ps time scale, slower than methanol diffusion, suggesting that the involved ligand exchange mechanism is dissociative

    Asymmetric response of forest and grassy biomes to climate variability across the African Humid Period : influenced by anthropogenic disturbance?

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    A comprehensive understanding of the relationship between land cover, climate change and disturbance dynamics is needed to inform scenarios of vegetation change on the African continent. Although significant advances have been made, large uncertainties exist in projections of future biodiversity and ecosystem change for the world's largest tropical landmass. To better illustrate the effects of climate–disturbance–ecosystem interactions on continental‐scale vegetation change, we apply a novel statistical multivariate envelope approach to subfossil pollen data and climate model outputs (TraCE‐21ka). We target paleoenvironmental records across continental Africa, from the African Humid Period (AHP: ca 14 700–5500 yr BP) – an interval of spatially and temporally variable hydroclimatic conditions – until recent times, to improve our understanding of overarching vegetation trends and to compare changes between forest and grassy biomes (savanna and grassland). Our results suggest that although climate variability was the dominant driver of change, forest and grassy biomes responded asymmetrically: 1) the climatic envelope of grassy biomes expanded, or persisted in increasingly diverse climatic conditions, during the second half of the AHP whilst that of forest did not; 2) forest retreat occurred much more slowly during the mid to late Holocene compared to the early AHP forest expansion; and 3) as forest and grassy biomes diverged during the second half of the AHP, their ecological relationship (envelope overlap) fundamentally changed. Based on these asymmetries and associated changes in human land use, we propose and discuss three hypotheses about the influence of anthropogenic disturbance on continental‐scale vegetation change

    A Revealed Reference Point for Prospect Theory

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    Without an instrument to identify the reference point, prospect theory includes a degree of freedom that makes the model difficult to falsify. To address this issue, we propose a foundation for prospect theory that advances existing approaches with three innovations. First, the reference point is not known a priori; if preferences are reference-dependent, the reference point is revealed from behavior. Second, the key preference axiom is formulated as a consistency property for attitudes towards probabilities; it entails both a revealed preference test for reference-dependence and a tool suitable for empirical measurement. Third, minimal assumptions are imposed for outcomes, thereby extending the model to general settings. By incorporating these three features we deliver general foundations for prospect theory that show how reference points can be identified and how the model can be falsified

    Making the Anscombe-Aumann approach to ambiguity suitable for descriptive applications

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    The Anscombe-Aumann (AA) model, originally introduced to give a normative basis to expected utility, is nowadays mostly used for another purpose: to analyze deviations from expected utility due to ambiguity (unknown probabilities). The AA model makes two ancillary assumptions that do not refer to ambiguity: expected utility for risk and backward induction. These assumptions, even if normatively appropriate, fail descriptively. This paper relaxes these ancillary assumptions to avoid the descriptive violations, while maintaining AA\xe2\x80\x99s convenient mixture operation. Thus, it becomes possible to test and apply all AA-based ambiguity theories descriptively while avoiding confounds due to violated ancillary assumptions. The resulting tests use only simple stimuli, avoiding noise due to complexity. We demonstrate the latter in a simple experiment where we find that three assumptions about ambiguity, commonly made in AA theories, are violated: reference independence, universal ambiguity aversion, and weak certainty independence. The second, theoretical, part of the paper accommodates the violations found for the first ambiguity theory in the AA model\xe2\x80\x94Schmeidler\xe2\x80\x99s CEU theory\xe2\x80\x94by introducing and axiomatizing a reference dependent generalization. That is, we extend the AA ambiguity model to prospect theory
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