Physics

We present here assessment of the latent market information embedded in the raw, affinity normalized, and partial correlations. We compared the Zipf plot, spectrum, and distribution of the eigenvalues for each matrix with the results of the corresponding random matrix. The analysis was performed on stocks belonging to the New York and Tel Aviv Stock Exchange, for the time period of January 2000 to March 2009. Our results show that in comparison to the raw correlations, the affinity matrices highlight the dominant factors of the system, and the partial correlation matrices contain more information. We propose that significant stock market information, which cannot be captured by the raw correlations, is embedded in the affinity and partial correlations. Our results further demonstrate the differences between NY and TA markets.

What are the dominant stocks which drive the correlations present among stocks traded in a stock market? Can a
correlation analysis provide an answer to this question? In the past, correlation based networks have been proposed as a tool to uncover the underlying backbone of the market. Correlation based networks represent the stocks and their relationships, which are then investigated using different network theory methodologies. Here we introduce a new concept to tackle the above question—the partial correlation network. Partial correlation is a measure of how the correlation between two variables, e.g., stock returns, is affected by a third variable. By using it we define a proxy of stock influence, which is then used to construct partial correlation networks. The empirical part of this study is performed on a specific financial system, namely the set of 300 highly capitalized stocks traded at the New York Stock Exchange, in the time period 2001–2003. By constructing the partial correlation network, unlike the case of standard correlation based networks, we find that stocks belonging to the financial sector and, in particular, to the investment services sub-sector, are the most influential stocks affecting the correlation profile of the system. Using a moving window analysis, we find that the strong influence of the financial stocks is conserved across time for the investigated trading period. Our findings shed a new light on the underlying mechanisms and driving forces controlling the correlation profile observed in a financial market.

Background
The 2007–2009 financial crisis, and its fallout, has strongly emphasized the need to define new ways and measures to study and assess the stock market dynamics.

Methodology/Principal Findings
The S&P500 dynamics during 4/1999–4/2010 is investigated in terms of the index cohesive force (ICF - the balance between the stock correlations and the partial correlations after subtraction of the index contribution), and the Eigenvalue entropy of the stock correlation matrices. We found a rapid market transition at the end of 2001 from a flexible state of low ICF into a stiff (nonflexible) state of high ICF that is prone to market systemic collapses. The stiff state is also marked by strong effect of the market index on the stock-stock correlations as well as bursts of high stock correlations reminiscence of epileptic brain activity.

Conclusions/Significance
The market dynamical states, stability and transition between economic states was studies using new quantitative measures. Doing so shed new light on the origin and nature of the current crisis. The new approach is likely to be applicable to other classes of complex systems from gene networks to the human brain.

Theoretical and empirical investigations of search strategies typically have failed to distinguish the distinct roles played by density versus patchiness of resources. It is well known that motility and diffusivity of organisms often increase in environments with low density of resources, but thus far there has been little progress in understanding the specific role of landscape heterogeneity and disorder on random, non-oriented motility. Here we address the general question of how the landscape heterogeneity affects the efficiency of encounter interactions under global constant density of scarce resources. We unveil the key mechanism coupling the landscape structure with optimal search diffusivity. In particular, our main result leads to an empirically testable prediction: enhanced diffusivity (including superdiffusive searches), with shift in the diffusion exponent, favors the success of target encounters in heterogeneous landscapes.

Background: In the current era of strong worldwide market couplings the global financial village became highly prone to systemic collapses, events that can rapidly sweep throughout the entire village.

Methodology/Principal Findings: We present a new methodology to assess and quantify inter-market relations. The approach is based on the correlations between the market index, the index volatility, the market Index Cohesive Force and the meta-correlations (correlations between the intra-correlations.) We investigated the relations between six important world markets—U.S., U.K., Germany, Japan, China and India—from January 2000 until December 2010. We found that while the developed ‘‘western’’ markets (U.S., U.K., Germany) are highly correlated, the interdependencies between these markets and the developing ‘‘eastern’’ markets (India and China) are volatile and with noticeable maxima at times of global world events. The Japanese market switches ‘‘identity’’—it switches between periods of high meta-correlations with the ‘‘western’’ markets and periods when it behaves more similarly to the ‘‘eastern’’ markets.

Conclusions/Significance: The methodological framework presented here provides a way to quantify the evolvement of interdependencies in the global market, evaluate a world financial network and quantify changes in the world inter market relations. Such changes can be used as precursors to the agitation of the global financial village. Hence, the new approach can help to develop a sensitive ‘‘financial seismograph’’ to detect early signs of global financial crises so they can be treated before they develop into worldwide events.

The 2007-2009 financial crisis, and its fallout, has strongly emphasized the need to define new ways and measures to study and assess the dynamics of financial markets. The S&P500 dynamics during 4/1999-4/2010 is investigated in terms of the index cohesive force (ICF - the balance between the stock correlations and the partial correlations after subtraction of the index contribution). We found a rapid market transition at the end of 2001 from a flexible state of low ICF into a stiff (nonflexible) state of high ICF that is prone to market systemic collapses. The stiff state is also marked by strong effect of the market index on the stock-stock correlations as well as bursts of high stock correlations reminiscence of epileptic brain activity. Finally, we make use of the recently introduced stock dependency networks to uncover changes in the market structure following the transition at the end of 2001. This analysis sheds new light on the origin and nature of the current crisis. The new approach is likely to be applicable to other classes of complex systems from gene networks to the human brain.

Microarray technology has played an important role in promoting the understanding of gene network regulations. Different supervised and unsupervised analysis methods have been devised to extract meaningful information from gene-expression data. In this chapter, we introduce the Genome Holography method (GH) for the analysis of gene-expression data and discuss some of its possible applications, such as clique finding technique and Functional Holography Minimal Spanning Tree (FHMST).

abstract Powerful free electron lasers (FELs) operating in the soft X-ray regime are offering new possibilities for creating and probing materials under extreme conditions. We describe here simulations to model the interaction of a focused FEL pulse with metallic solids (niobium, vanadium, and their deuterides) at 13.5 nm wavelength (92 eV) with peak intensities between 10 15 to 10 18 W/cm 2 and a fixed pulse length of 15 femtoseconds (full width at half maximum).

Ultrashort and extremely intense photon pulses from x-ray free-electron lasers (FELs) have created a revolution in photon science. Breakthrough results have been reported in coherent diffractive imaging [1], femtosecond x-ray holography [2], cluster physics [3], and high-energy density science [4, 5]. Parallel developments with table-top x-ray lasers demonstrate new capabilities at a significantly smaller laboratory scale [6–9].

Abstract Saturable absorption is a phenomenon readily seen in the optical and infrared wavelengths. It has never been observed in core-electron transitions owing to the short lifetime of the excited states involved and the high intensities of the soft X-rays needed. We report saturable absorption of an L-shell transition in aluminium using record intensities over 10 16 W cm-2 at a photon energy of 92 eV.