Spurious trend switching phenomena in financial markets

The observation of power laws in the time to extrema of volatility, volume and intertrade times, from milliseconds to years, are shown to result straightforwardly from the selection of biased statistical subsets of realizations in otherwise featureless processes such as random walks. The bias stems from the selection of price peaks that imposes a condition on the statistics of price change and of trade volumes that skew their distributions. For the intertrade times, the extrema and power laws results from the format of transaction data

Coupling of intrinsic Josephson oscillations in layered superconductors by charge fluctuations

The coupling of Josephson oscillations in layered superconductors is studied with help of a tunneling Hamiltonian formalism. The general form of the current density across the barriers between the superconducting layers is derived. The induced charge fluctuations on the superconducting layers lead to a coupling of the Josephson oscillations in different junctions. A simplified set of equations is then used to study the non-linear dynamics of the system. In particular the influence of the coupling on the current-voltage characteristics is investigated and upper limits for the coupling strength are estimated from a comparison with experiments on cuprate superconductors.Comment: To be published in proceedings of SPIE conference San Diego 199

Quantifying trading behavior in financial markets using Google Trends

Crises in financial markets affect humans worldwide. Detailed market data on trading decisions reflect some of the complex human behavior that has led to these crises. We suggest that massive new data sources resulting from human interaction with the Internet may offer a new perspective on the behavior of market participants in periods of large market movements. By analyzing changes in Google query volumes for search terms related to finance, we find patterns that may be interpreted as “early warning signs” of stock market moves. Our results illustrate the potential that combining extensive behavioral data sets offers for a better understanding of collective human behavior

Scanning Raman spectroscopy of graphene antidot lattices: Evidence for systematic p-type doping

We have investigated antidot lattices, which were prepared on exfoliated graphene single layers via electron-beam lithography and ion etching, by means of scanning Raman spectroscopy. The peak positions, peak widths and intensities of the characteristic phonon modes of the carbon lattice have been studied systematically in a series of samples. In the patterned samples, we found a systematic stiffening of the G band mode, accompanied by a line narrowing, while the 2D mode energies are found to be linearly correlated with the G mode energies. We interpret this as evidence for p-type doping of the nanostructured graphene

Information sharing promotes prosocial behaviour

More often than not, bad decisions are bad regardless of where and when they are made. Information sharing might thus be utilized to mitigate them. Here we show that sharing information about strategy choice between players residing on two different networks reinforces the evolution of cooperation. In evolutionary games, the strategy reflects the action of each individual that warrants the highest utility in a competitive setting. We therefore assume that identical strategies on the two networks reinforce themselves by lessening their propensity to change. Besides network reciprocity working in favour of cooperation on each individual network, we observe the spontaneous emergence of correlated behaviour between the two networks, which further deters defection. If information is shared not just between individuals but also between groups, the positive effect is even stronger, and this despite the fact that information sharing is implemented without any assumptions with regard to content

Crowdsourcing Dialect Characterization through Twitter

We perform a large-scale analysis of language diatopic variation using geotagged microblogging datasets. By collecting all Twitter messages written in Spanish over more than two years, we build a corpus from which a carefully selected list of concepts allows us to characterize Spanish varieties on a global scale. A cluster analysis proves the existence of well defined macroregions sharing common lexical properties. Remarkably enough, we find that Spanish language is split into two superdialects, namely, an urban speech used across major American and Spanish citites and a diverse form that encompasses rural areas and small towns. The latter can be further clustered into smaller varieties with a stronger regional character.Comment: 10 pages, 5 figure

Microscopic theory of the coupling of intrinsic Josephson oscillations and phonons

A microscopic theory for the coupling of intrinsic Josephson oscillations and dispersive phonon branches in layered superconductors is developed. Thereby the effect of phonons on the electronic c-axis transport enters through an effective longitudinal dielectric function. This coupling provides an explanation of recently observed subgap resonances in the $I_{dc}$-$V_{dc}$- curve of anisotropic cuprate superconductors forming a stack of short Josephson junctions. Due to the finite dispersion these resonances can appear at van-Hove-singularities of both optical and acoustical phonon branches, explaining low-voltage structures in the I-V-characteristic, which are not understood in phonon models without dispersion. In long junctions the dispersion of collective electron-phonon modes parallel to the layers is investigated.Comment: 4 pages, 3 figures, 1 table, espcrc2.sty, invited contribution to "Materials and Mechanisms of Superconductivity and High Temperature Superconductors VI - M2S-HTSC-VI", Houston, Texas, 20-25 Feb 2000, to appear in Physica

Linear Programming in the Semi-streaming Model with Application to the Maximum Matching Problem

In this paper, we study linear programming based approaches to the maximum matching problem in the semi-streaming model. The semi-streaming model has gained attention as a model for processing massive graphs as the importance of such graphs has increased. This is a model where edges are streamed-in in an adversarial order and we are allowed a space proportional to the number of vertices in a graph. In recent years, there has been several new results in this semi-streaming model. However broad techniques such as linear programming have not been adapted to this model. We present several techniques to adapt and optimize linear programming based approaches in the semi-streaming model with an application to the maximum matching problem. As a consequence, we improve (almost) all previous results on this problem, and also prove new results on interesting variants