Replicating financial market dynamics with a simple self-organized critical lattice model

We explore a simple lattice field model intended to describe statistical properties of high frequency financial markets. The model is relevant in the cross-disciplinary area of econophysics. Its signature feature is the emergence of a self-organized critical state. This implies scale invariance of the model, without tuning parameters. Prominent results of our simulation are time series of gains, prices, volatility, and gains frequency distributions, which all compare favorably to features of historical market data. Applying a standard GARCH(1,1) fit to the lattice model gives results that are almost indistinguishable from historical NASDAQ data.Comment: 20 pages, 33 figure

PROBABILISTIC INFERENCE FOR INTERVAL PROBABILITIES IN DECISION-MAKING PROCESSES

The present paper considers one approach to Bayes’ formula based probabilistic inference under interval values of relevant probabilities; the necessity of it is caused by the impossibility to obtain reliable deterministic values of the required probabilistic evaluations. The paper shows that the approach proves to be the best from the viewpoint of the required amount of calculations and visual representation of the results. The execution of the algorithm of probabilistic inference is illustrated using a classical task of decision making related to oil mining. For visualisation purposes, the state of initial and target information is modelled using probability trees.

SYMBIOSIS: Development, Implementation, and Assessment of a Model Curriculum across Biology and Mathematics at the Introductory Level

“It takes a lot of courage to release the familiar and seemingly secure, to embrace the new. But there is no real security in what is no longer meaningful. There is more security in the adventurous and exciting, for in movement there is life, and in change there is power.”Alan Cohen (Used by permission. All rights reserved. For more information on Alan Cohen's books and programs, see (www.alancohen.com.

Complex Networks and Symmetry II: Reciprocity and Evolution of World Trade

We exploit the symmetry concepts developed in the companion review of this article to introduce a stochastic version of link reversal symmetry, which leads to an improved understanding of the reciprocity of directed networks. We apply our formalism to the international trade network and show that a strong embedding in economic space determines particular symmetries of the network, while the observed evolution of reciprocity is consistent with a symmetry breaking taking place in production space. Our results show that networks can be strongly affected by symmetry-breaking phenomena occurring in embedding spaces, and that stochastic network symmetries can successfully suggest, or rule out, possible underlying mechanisms.Comment: Final accepted versio

Identifying Causal Structures from Cyberstalking: Behaviors Severity and Association

This paper presents an etiological cyberstalking study, meaning the use of various technologies and internet in general to harass or to stalk someone. The novelty of the paper is the multivariate empirical approach of cyberstalking victimization that has received less attention from the research community. Also, there is a lack of such studies from the causal perspective. It happens, since in most of the studies, a priority is given on a single causation identification, whereas the data examination used for mining causal relationships in this paper presents a novel and great potential to detect combined or multiple cause factors. The paper focuses in the impact that variables such as age, gender and the fact whether the participant has ever harassed someone, is related to the fact of being victim of cyberstalking. The research aims to find the causes of cyberstalking in high school’s teenagers. Furthermore, an exploratory data analysis has been performed. A weak and moderate correlation between the factors on the dataset is emphasized. The odds ratio among the variables has been calculated, which implies that girls are twice as likely as boys to be cyberstalked. Similarly, concerning outcomes related to cyberstalking frequency recidivism are noticed

The genetic architecture of host response reveals the importance of arbuscular mycorrhizae to maize cultivation.

Arbuscular mycorrhizal fungi (AMF) are ubiquitous in cultivated soils, forming symbiotic relationships with the roots of major crop species. Studies in controlled conditions have demonstrated the potential of AMF to enhance the growth of host plants. However, it is difficult to estimate the actual benefit in the field, not least because of the lack of suitable AMF-free controls. Here we implement a novel strategy using the selective incorporation of AMF-resistance into a genetic mapping population to evaluate maize response to AMF. We found AMF to account for about one-third of the grain production in a medium input field, as well as to affect the relative performance of different plant genotypes. Characterization of the genetic architecture of the host response indicated a trade-off between mycorrhizal dependence and benefit. We identified several QTL linked to host benefit, supporting the feasibility of breeding crops to maximize profit from symbiosis with AMF

Laban Movement Analysis Using a Bayesian Model and Perspective Projections

Human body movements are meant to move a, or some, body parts to a specific location along a certain trajectory. A person observing the movement might be able to recognize it through the spatial pathway alone. Kendon (Kendon, 2004) holds the view that willingly or not, humans, when in co-presence, continuously inform one another about their intentions