Fundamentals unknown:momentum, mean-reversion and price-to-earnings trading in an artificial stock market

The use of fundamentalist traders in the stock market models is problematic since fundamental values in the real world are unknown. Yet, in the literature to date, fundamentalists are often required to replicate key stylized facts. The authors present an agent-based model of the stock market in which the fundamental value of the asset is unknown. They start with a zero intelligence stock market model with a limit-order-book. Then, the authors add technical traders which switch between a simple momentum and mean reversion strategy depending on its relative profitability. Technical traders use the price to earnings ratio as a proxy for fundamentals. If price to earnings are either too high or too low, they sell or buy, respectively

Subjective and objective components of resource value additively increase aggression in parasitoid contests

Two major categories of factors are predicted to influence behaviour in dyadic contests; differences in the abilities of the contestants to acquire and retain resources (resource holding potential), and the value of the contested resource (resource value, RV; which comprises objective and subjective components). Recent studies indicate that subjective components affect contest behaviour in several animal taxa but few have simultaneously investigated objective RV components. We find that both an objective (host size) and a subjective (contestant age) component of RV affect contest intensity in the parasitoid wasp Goniozus legneri. These additively influence aggressiveness, with a larger effect from the subjective component than the objective component. The greater influence of subjective RV adds weight to the recent surge of recognition of this RV component's importance in contest behaviour

Property rights and loss aversion in contests

We analyze the effects of property rights and the resulting loss aversion on contest outcomes. We study three situations: in “gain” two players start with no prize and make sunk bids to win a prize; in “loss” both the players start with prizes and whoever loses the contest loses their prize; and in “mixed” only one player starts with a prize that stays with him if he wins, but is transferred to the rival otherwise. Since the differences among the treatments arise only from framing, the expected utility and the standard loss aversion models predict no difference in bids across treatments. We introduce a loss aversion model in which the property rights are made salient, and as a result the reference point varies across treatments. This model predicts average bids in descending order in the loss, the mixed, and the gain treatment; and higher bids by the player with property rights in the mixed treatment. The results from a laboratory experiment broadly support these predictions. There is no significant difference in bids in the loss (gain) treatment and bids by property rights holder (nonholder) in the mixed treatment. A model incorporating both loss aversion and social preferences explains this result

Protein Binding Detection Using On-Chip Silicon Gratings

We demonstrate a silicon gratings-based biosensor to detect functionalized protein binding on its surface. The designed silicon gratings have sensitivities up to 197 nm/RIU in detecting refractive index change and 1.61 nm per nanometer of thickness change of bio-material on the surface of silicon gratings. Functionalizing proteins on gratings surface by eliminating unspecific binding makes this device more selective and efficient. Streptavidin at a concentration of 0.016 μmol/mL was functionalized on silicon substrate and biotin of 12 μmol/mL concentration was used as a target molecule in our detection experiments. Normal transmission measurements of gratings are made in air at different stages of immobilization, bare silicon grating, after attaching streptavidin and after trapping biotin. Total shifts in resonant peak wavelength of ∼15 nm in normal transmission were observed after immobilizing biotin with ∼7 nm of shift in resonant peak wavelength after functionalizing streptavidin to silicon substrate

How does the environment affect fighting? The interaction between extrinsic fighting ability and resource value during contests.

An individual's performance during a fight is influenced by a combination of their capacity and willingness to compete. While willingness to fight is known to be determined by both intrinsic and extrinsic drivers, an individual's capacity to fight is generally thought of as solely intrinsic, being driven by a host of physiological factors. However, evidence indicates that variation in fighting ability can also be generated through exposure to different environmental conditions. Environmental contributions to fighting ability may be particularly important for animals living in spatially and temporally heterogeneous habitats, in which fights can occur between rivals recently exposed to different environmental conditions. The rapidly changing environment experienced within intertidal zones, for example, means that seawater parameters, including dissolved oxygen content and temperature, can vary across small spatial and temporal scales. Here we investigate the relative importance of these extrinsic contributions to fighting ability and resource value on contest dynamics in the beadlet sea anemone Actinia equina We manipulate the extrinsic fighting ability of both opponents (through dissolved oxygen concentration prior to fights) and resource value (through seawater flow rate during the fight). Our results indicate that the extrinsic fighting ability of both opponents can interact with resource value to drive escalation patterns and that extrinsic drivers can be more important in determining contest dynamics than the intrinsic traits commonly studied. Our study highlights the need to combine data on intrinsic state and extrinsic conditions in order to gain a more holistic view of the factors driving contest behaviour

‘Hangry’ Drosophila: food deprivation increases male aggression

Aggressive interactions are costly, such that individuals should display modified aggression in response to environmental stress. Many organisms experience frequent periods of food deprivation, which can influence an individual's capacity and motivation to engage in aggression. However, because food deprivation can simultaneously decrease an individual's resource-holding potential and increase its valuation of food resources, its net impact on aggression is unclear. Here, we tested the influence of increasingly prolonged periods of adult food deprivation on intermale aggression in pairs of fruit flies, Drosophila melanogaster. We found that males displayed increased aggression following periods of food deprivation longer than a day. Increased aggression in food-deprived flies occurred despite their reduced mass. This result is probably explained by an increased attraction to food resources, as food deprivation increased male occupancy of central food patches, and food patch occupancy was positively associated with aggression. Our findings demonstrate that aggressive strategies in male D. melanogaster are influenced by nutritional experience, highlighting the need to consider past nutritional stresses to understand variation in aggression

Comparison calibration of piezoresistive microphones for acoustic power measurements

A calibration of two Endevco piezoresistive microphones was carried out under static and dynamics pressures. The dynamic pressure calibrations were done by comparison with a B&K condenser microphone. The calibration was carried out in a small closed volume in air and helium. In helium, the codes volume was pressurized to atmospheric pressure and then 10 Atm. The dynamic calibration would determine the "flatness" of the calibration curve, as well as determine a sensitivity value over the range of frequencies used. The results showed that the calibration curve for the piezoresistive microphones are flat from static pressures to about 300 Hz and then begin to fall off. The value of the sensitivity of the "flat" region of the calibration curve for one microphone was within 0.4% of the value for sensitivity calculated under the static pressure calibration. For the other microphone the static and dynamic sensitivities were within 1.3% of each other. Then, the static calibration of one microphone may be used under dynamic conditions with a less than 1% error while using the other microphone similarly will produce an error of greater than 1%.http://archive.org/details/comparisoncalibr00stocCaptain, Canadian ForcesApproved for public release; distribution is unlimited