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At least 163 records · Page 9Linked to original sources

arXiv2008

Graphene - A rising star in view of scientometrics

We have carried out a scientometric analysis of the literature dealing with graphene, a material which has been identified as a new carbon allotrope. The investigation is based on the CAplus database of Chemical Abstracts Service, the INSPEC database of the Institute of Electrical and Electronics Engineers and the Web of Science (WoS) of Thomson Reuters. The time evolution of the publications shows a dramatic increase since 2004 when graphene has been isolated for the first time. The graphene literature has been analyzed with respect to the most productive authors, research organizations, countries of authors, and the leading journals. Furthermore, the time evolution of the major graphene based research topics and the top 10 most productive research organizations with respect to their specific topics have been analyzed and are shown as heat maps. In addition, the graphene research landscape has been established using the analysis tool STN AnaVist. Finally, a brief citation analysis has been performed. The time evolution of the impact reveals that, rather similar to the output evolution, the impact increase of the graphene papers within the starting period is possibly going to outrun the impact increase of the fullerenes and nanotubes papers.

physics.soc-ph↗

arXiv2008

Criticality Characteristics of Current Oil Price Dynamics

Methodology that recently lead us to predict to an amazing accuracy the date (July 11, 2008) of reverse of the oil price up trend is briefly summarized and some further aspects of the related oil price dynamics elaborated. This methodology is based on the concept of discrete scale invariance whose finance-prediction-oriented variant involves such elements as log-periodic self-similarity, the universal preferred scaling factor lambda=2, and allows a phenomenon of the "super-bubble". From this perspective the present (as of August 22, 2008) violent - but still log-periodically decelerating - decrease of the oil prices is associated with the decay of such a "super- bubble" that has started developing about one year ago on top of the longer-term oil price increasing phase (normal bubble) whose ultimate termination is evaluated to occur in around mid 2010.

q-fin.ST↗

arXiv2009

Weighted-Interaction Nestedness Estimator (WINE): A new estimator to calculate over frequency matrices

We have developed a graphical user interface (GUI) running in Matlab, called Weighted-Interaction Nestedness Estimator, WINE (Fig. 1). WINE is a Matlab application developed to perform the calculation of the new weighted nestedness estimator. This program allows the user to: open a data file, select the range of data to be analysed, and calculate the results, obtaining two graphics and three indices. The indices shown in the graphical interface are: a) weighted nestedness of the frequency matrix, b) average weighted nestedness of 100 random matrices of similar characteristics, and c) the new weighted- interaction nestedness estimator, which compares the two previous results.

physics.bio-ph↗

arXiv2008

Ensembles related to the rich-club coefficient for non-evolving networks

In complex networks the rich nodes are the subset of nodes with high degree. These well connected nodes tend to dominate the organisation of the network's structure. In non-evolving networks, a reference network has been used to detect if the connectivity between the rich nodes is due to chance or caused by an unknown mechanism. Chance is represented as a reference network obtained from an ensemble of networks. When compared with the original network the reference network discounts suggests the existence of a well connected rich club beyond structural constraints. Here we revise some of the properties of the ensemble obtained by conserving only the degree distribution and introduce two new reference networks to study the importance of the rich nodes as organisers of the network structure. The first reference network is obtained from an ensemble of networks where all the members of the ensemble have the same rich--club coefficient. The reference network obtained from the ensemble is assortative. We propose that this reference network can be used to study networks where assortativness is a fundamental property, a common case in many social networks. The second reference network is obtained from an ensemble where the members of the ensemble all have the same probability degree distribution and rich-club coefficient. The reference network obtained from this ensemble has a very similar structure to the original network. This ensemble can be used to quantify correlations between the rich nodes and pinpoint which links are the backbone of the network's structure.

physics.soc-ph↗

arXiv2009

Bayesian Analysis of Value-at-Risk with Product Partition Models

In this paper we propose a novel Bayesian methodology for Value-at-Risk computation based on parametric Product Partition Models. Value-at-Risk is a standard tool to measure and control the market risk of an asset or a portfolio, and it is also required for regulatory purposes. Its popularity is partly due to the fact that it is an easily understood measure of risk. The use of Product Partition Models allows us to remain in a Normal setting even in presence of outlying points, and to obtain a closed-form expression for Value-at-Risk computation. We present and compare two different scenarios: a product partition structure on the vector of means and a product partition structure on the vector of variances. We apply our methodology to an Italian stock market data set from Mib30. The numerical results clearly show that Product Partition Models can be successfully exploited in order to quantify market risk exposure. The obtained Value-at-Risk estimates are in full agreement with Maximum Likelihood approaches, but our methodology provides richer information about the clustering structure of the data and the presence of outlying points.

q-fin.RM↗

arXiv2009

What are scientific leaders? The introduction of a normalized impact factor

We define a normalized impact factor suitable to assess in a simple way both the strength of scientific communities and the research influence of individuals. We define those ones with $NIF \geq 1$ as being scientific leaders since they would influence their peers at least as much as they are influenced by them. The NIF is distinguished because (a) this has a clear and universal meaning being applicable with equal efficiency to individuals belonging to scientific communities with quite different publication and citation traditions and (b) this is robust against self-citation expedient. This is eventually applied to a community derived from the list of outstanding referees recognized by the American Physical Society in 2008.

physics.soc-ph↗

arXiv2008

Minimal Spanning Tree graphs and power like scaling in FOREX networks

Correlation matrices of foreign exchange rate time series are investigated for 60 world currencies. Minimal Spanning Tree (MST) graphs for the gold, silver and platinum are presented. Inverse power like scaling is discussed for these graphs as well as for four distinct currency groups (major, liquid, less liquid and non-tradable). The worst scaling has been found for USD and related currencies.

q-fin.ST↗

arXiv2008

How markets slowly digest changes in supply and demand

In this article we revisit the classic problem of tatonnement in price formation from a microstructure point of view, reviewing a recent body of theoretical and empirical work explaining how fluctuations in supply and demand are slowly incorporated into prices. Because revealed market liquidity is extremely low, large orders to buy or sell can only be traded incrementally, over periods of time as long as months. As a result order flow is a highly persistent long-memory process. Maintaining compatibility with market efficiency has profound consequences on price formation, on the dynamics of liquidity, and on the nature of impact. We review a body of theory that makes detailed quantitative predictions about the volume and time dependence of market impact, the bid-ask spread, order book dynamics, and volatility. Comparisons to data yield some encouraging successes. This framework suggests a novel interpretation of financial information, in which agents are at best only weakly informed and all have a similar and extremely noisy impact on prices. Most of the processed information appears to come from supply and demand itself, rather than from external news. The ideas reviewed here are relevant to market microstructure regulation, agent-based models, cost-optimal execution strategies, and understanding market ecologies.

q-fin.TR↗

arXiv2010

Stability of Maximum likelihood based clustering methods: exploring the backbone of classifications (Who is keeping you in that community?)

Components of complex systems are often classified according to the way they interact with each other. In graph theory such groups are known as clusters or communities. Many different techniques have been recently proposed to detect them, some of which involve inference methods using either Bayesian or Maximum Likelihood approaches. In this article, we study a statistical model designed for detecting clusters based on connection similarity. The basic assumption of the model is that the graph was generated by a certain grouping of the nodes and an Expectation Maximization algorithm is employed to infer that grouping. We show that the method admits further development to yield a stability analysis of the groupings that quantifies the extent to which each node influences its neighbors group membership. Our approach naturally allows for the identification of the key elements responsible for the grouping and their resilience to changes in the network. Given the generality of the assumptions underlying the statistical model, such nodes are likely to play special roles in the original system. We illustrate this point by analyzing several empirical networks for which further information about the properties of the nodes is available. The search and identification of stabilizing nodes constitutes thus a novel technique to characterize the relevance of nodes in complex networks.

physics.soc-ph↗

arXiv2008

Hubs and Clusters in the Evolving U. S. Internal Migration Network

Most nations of the world periodically publish N x N origin-destination tables, recording the number of people who lived in geographic subdivision i at time t and j at t+1. We have developed and widely applied to such national tables and other analogous (weighted, directed) socioeconomic networks, a two-stage--double-standardization and (strong component) hierarchical clustering--procedure. Previous applications of this methodology and related analytical issues are discussed. Its use is illustrated in a large-scale study, employing recorded United States internal migration flows between the 3,000+ county-level units of the nation for the periods 1965-1970 and 1995-2000. Prominent, important features--such as ''cosmopolitan hubs'' and ``functional regions''--are extracted from master dendrograms. The extent to which such characteristics have varied over the intervening thirty years is evaluated.

physics.soc-ph↗

arXiv2008

Finding links and initiators: a graph reconstruction problem

Consider a 0-1 observation matrix M, where rows correspond to entities and columns correspond to signals; a value of 1 (or 0) in cell (i,j) of M indicates that signal j has been observed (or not observed) in entity i. Given such a matrix we study the problem of inferring the underlying directed links between entities (rows) and finding which entries in the matrix are initiators. We formally define this problem and propose an MCMC framework for estimating the links and the initiators given the matrix of observations M. We also show how this framework can be extended to incorporate a temporal aspect; instead of considering a single observation matrix M we consider a sequence of observation matrices M1,..., Mt over time. We show the connection between our problem and several problems studied in the field of social-network analysis. We apply our method to paleontological and ecological data and show that our algorithms work well in practice and give reasonable results.

cs.AI↗

arXiv2012

Climate Science: Is it currently designed to answer questions?

For a variety of inter-related cultural, organizational, and political reasons, progress in climate science and the actual solution of scientific problems in this field have moved at a much slower rate than would normally be possible. Not all these factors are unique to climate science, but the heavy influence of politics has served to amplify the role of the other factors. Such factors as the change in the scientific paradigm from a dialectic opposition between theory and observation to an emphasis on simulation and observational programs, the inordinate growth of administration in universities and the consequent increase in importance of grant overhead, and the hierarchical nature of formal scientific organizations are cosidered. This paper will deal with the origin of the cultural changes and with specific examples of the operation and interaction of these factors. In particular, we will show how political bodies act to control scientific institutions, how scientists adjust both data and even theory to accommodate politically correct positions, and how opposition to these positions is disposed of.

physics.soc-ph↗

arXiv2008

Entropic Geometry of Crowd Dynamics

We propose an entropic geometrical model of psycho-physical crowd dynamics (with dissipative crowd kinematics), using Feynman action-amplitude formalism that operates on three synergetic levels: macro, meso and micro. The intent is to explain the dynamics of crowds simultaneously and consistently across these three levels, in order to characterize their geometrical properties particularly with respect to behavior regimes and the state changes between them. Its most natural statistical descriptor is crowd entropy $S$ that satisfies the Prigogine's extended second law of thermodynamics, $\partial_tS\geq 0$ (for any nonisolated multi-component system). Qualitative similarities and superpositions between individual and crowd configuration manifolds motivate our claim that goal-directed crowd movement operates under entropy conservation, $\partial_tS = 0$, while natural crowd dynamics operates under (monotonically) increasing entropy function, $\partial_tS > 0$. Between these two distinct topological phases lies a phase transition with a chaotic inter-phase. Both inertial crowd dynamics and its dissipative kinematics represent diffusion processes on the crowd manifold governed by the Ricci flow, with the associated Perelman entropy-action. Keywords: Crowd psycho-physical dynamics, action-amplitude formalism, crowd manifold, Ricci flow, Perelman entropy, topological phase transition

nlin.AO↗

arXiv2008

Stock market volatility: An approach based on Tsallis entropy

One of the major issues studied in finance that has always intrigued, both scholars and practitioners, and to which no unified theory has yet been discovered, is the reason why prices move over time. Since there are several well-known traditional techniques in the literature to measure stock market volatility, a central point in this debate that constitutes the actual scope of this paper is to compare this common approach in which we discuss such popular techniques as the standard deviation and an innovative methodology based on Econophysics. In our study, we use the concept of Tsallis entropy to capture the nature of volatility. More precisely, what we want to find out is if Tsallis entropy is able to detect volatility in stock market indexes and to compare its values with the ones obtained from the standard deviation. Also, we shall mention that one of the advantages of this new methodology is its ability to capture nonlinear dynamics. For our purpose, we shall basically focus on the behaviour of stock market indexes and consider the CAC 40, MIB 30, NIKKEI 225, PSI 20, IBEX 35, FTSE 100 and SP 500 for a comparative analysis between the approaches mentioned above.

q-fin.ST↗

arXiv2008

"Fractal Expression" in Chinese Calligraphy

We show that from historical record and mathematic analysis, "fractal expressions" may have been a conscious pursuit at least one thousand years ago as an element of beauty in ancient Chinese calligraphy.

physics.gen-ph↗

arXiv2008

Look-Ahead Benchmark Bias in Portfolio Performance Evaluation

Performance of investment managers are evaluated in comparison with benchmarks, such as financial indices. Due to the operational constraint that most professional databases do not track the change of constitution of benchmark portfolios, standard tests of performance suffer from the "look-ahead benchmark bias," when they use the assets constituting the benchmarks of reference at the end of the testing period, rather than at the beginning of the period. Here, we report that the "look-ahead benchmark bias" can exhibit a surprisingly large amplitude for portfolios of common stocks (up to 8% annum for the S&P500 taken as the benchmark) -- while most studies have emphasized related survival biases in performance of mutual and hedge funds for which the biases can be expected to be even larger. We use the CRSP database from 1926 to 2006 and analyze the running top 500 US capitalizations to demonstrate that this bias can account for a gross overestimation of performance metrics such as the Sharpe ratio as well as an underestimation of risk, as measured for instance by peak-to-valley drawdowns. We demonstrate the presence of a significant bias in the estimation of the survival and look-ahead biases studied in the literature. A general methodology to test the properties of investment strategies is advanced in terms of random strategies with similar investment constraints.

q-fin.PM↗

arXiv2009

Universality in the stock exchange

We analyze the constituents stocks of the Dow Jones Industrial Average (DJIA30) and the Standard & Poor's 100 index (S&P100) of the NYSE stock exchange market. Surprisingly, we discover the data collapse of the histograms of the DJIA30 price fluctuations and of the S&P100 price fluctuations to the universal non-parametric Bramwell-Holdsworth-Pinton (BHP) distribution. Since the BHP probability density function appears in several other dissimilar phenomena, our result reveals an universal feature of the stock exchange market.

q-fin.ST↗

arXiv2009

Blume-Emery-Griffiths dynamics in social networks

We introduce the Blume-Emery-Griffiths (BEG) model in a social networks to describe the three-state dynamics of opinion formation. It shows that the probability distribution function of the time series of opinion is a Gaussian-like distribution. We also study the response of BEG model to the external periodic perturbation. One can observe that both the interior thermo-noise and the external field result in phase transition, which is a split phenomena of the opinion distributions. It is opposite between the effect acted on the opinion systems of the amplitude of the external field and of the thermo-noise.

physics.soc-ph↗