Dominating clasp of the financial sector revealed by partial correlation analysis of the stock market

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.     

A general class of correlation coefficients for the 2 x 2 crossover design

The Pearson correlation coefficient and the Kendall correlation coefficient are two popular statistics for assessing the correlation between two variables in a bivariate sample. We indicate how both of these statistics are special cases of a general class of correlation statistics that is parameterized by gamma element of [0, 1]. The Pearson correlation coefficient is characterized by gamma = 1 and the Kendall correlation coefficient by gamma = 0, so they yield the upper and lower extremes of the class, respectively. The correlation coefficient characterized by gamma = 0.5 is of special interest because it only requires that first-order moments exist for the underlying bivariate distribution, whereas the Pearson correlation coefficient requires that second-order moments exist. We derive the asymptotic theory for the general class of sample correlation coefficients and then describe the use of this class of correlation statistics within the 2 x 2 crossover design. We illustrate the methodology using data from the CLIC trial of the Childhood Asthma Research and Education (CARE) Network.     

Note on the estimation of the correlation function of neural spike trains

The use of time-bins in the estimation of the correlation function of neural spike trains has a filtering effect on the estimate and results in distortion and aliasing. Prior low-pass filtering of the spike trains, on the other hand, and computation of the correlation function of the emerging waveforms in the standard way result in an estimate that is also a filtered version of the original function but distortion- and alias-free. In addition, the correlation function so computed can be normalized. An analogous definition of the correlation coefficient for the first technique enables the comparison of these various correlation estimates and clarifies their properties.     

长江三角洲地区城市化与植被活动之间的时空相关性

利用时间序列NDVI数据和统计资料,以长江三角洲地区为例,研究城市化与植被生长活力之间的时空相关性。在总体上,NDVI与人口和GDP之间均呈显著的负相关性;空间相关场进一步表明,在人口和GDP分布较高的地区,植被的生长活力越低,相关系数均在-1.0～0.5之间。选择地市行政单元为研究粒度,使用面板数据分析方法,研究单位面积NDVI与城市化率之间相关性的演变,结果表明,在时间序列上负相关性越来越强,两者之间有明显线性关系,这在一定程度上反映了区域社会发展与生态环境之间未达到双赢。     

Chain length is the main determinant of the folding rate for proteins with three-state folding kinetics

We demonstrate that chain length is the main determinant of the folding rate for proteins with the three-state folding kinetics. The logarithm of their folding rate in water (k(f)) strongly anticorrelates with their chain length L (the correlation coefficient being -0.80). At the same time, the chain length has no correlation with the folding rate for two-state folding proteins (the correlation coefficient is -0.07). Another significant difference of these two groups of proteins is a strong anticorrelation between the folding rate and Baker's "relative contact order" for the two-state folders and the complete absence of such correlation for the three-state folders.     

Separation of the rotational contribution in fluorescence correlation experiments

The theory of fluorescence correlation spectroscopy is reexamined with the aim of separating the contribution of rotational diffusion. Under constant excitation, fluorescence correlation experiments are characterized by three polarizations: one of the incident beam and two of the two photon detectors. A set of experiments of different polarizations is proposed for study. From the results of the experiments the isotropic factor of the fluorescence intensity correlation functions can be determined, which is independent of the rotational motion of the sample molecule. This function can be used to represent each fluorescence intensity correlation function as the product of the isotropic and the rotational factors. The theory is illustrated by an experiment in which rotational diffusion of porcine pancreatic lipase labeled with Texas Red was observed Texas Red is a label that allows precise fluorescence correlation experiments even in the nanosecond time range.     

Covariation of GC content and the silent site substitution rate in rodents: implications for methodology and for the evolution of isochores

Many attempts to test selectionist and neutralist models employ estimates of synonymous (Ks) and non-synonymous (Ka) substitution rates of orthologous genes. For example, a stronger Ka-Ks correlation than expected under neutrality has been argued to indicate a role for selection and the absence of a Ks-GC4 correlation has been argued to be inconsistent with neutral models for isochore evolution. However, both of these results, we have shown previously, are sensitive to the method by which Ka and Ks are estimated. Using a maximum likelihood (ML) estimator (GY94) we found a positive correlation between Ks and GC4 and only a weak correlation between Ka and Ks, lower than expected under neutral expectations. This ML method is computationally slow. Recently, a new ad hoc approximation of this ML method has been provided (YN00). This is effectively an extension of Li's protocol but that also allows for codon usage bias. This method is computationally near-instantaneous and therefore potentially of great utility for analysis of large datasets. Here we ask whether this method might have such applicability. To this end we ask whether it too recovers the two unusual results. We report that when the ML and earlier ad hoc methods disagree, YN00 recovers the results described by the ML methods, i.e. a positive correlation between GC4 and Ks and only a weak correlation between Ks and Ka. If the ML method can be trusted, then YN00 can also be considered an adequately reliable method for analysis of large datasets. Assuming this to be so we also analyze further the patterns. We show, for example, that the positive correlation between GC4 and Ks is probably in part a mutational bias, there being more methyl induced CpG-->TpG mutations in GC rich regions. As regards the evolution of isochores, it seems inappropriate to use the claimed lack of a correlation between GC and Ks as definitive evidence either against or for any model. If the positive correlation is real then, we argue, this is hard to reconcile with the biased gene conversion model for isochore formation as this predicts a negative correlation.     

Correlation between the synthetic activity of lymphocytes and the intensity of neutron radiation near the Earth surface

The synthetic activity of lymphocytes from rat and ground squirrel was assessed for correlation with the rate of neutron radiation about the Earth surface. In the periods 1999–2002 for rats and 2002–2003 for ground squirrels, significant positive correlation was obtained with the neutron flux incident on Earth and the overall “terrestrial neutron field” but not with the neutron efflux from Earth. No correlation was observed in 2005–2006 when the solar activity and the variation in neutron count were minimal. It is concluded that low-energy neutrons may be bioeffective in periods of substantial variation in flux intensity.     

Physico-chemical constraints connected with the coding properties of the genetic system

New insights on the origin of the genetic code, based on the analysis of the physico-chemical properties of its molecular constituents (RNA and amino acids), are reported in this paper. We point out a symmetry in the genetic code table and show that it can be explained by the nature of the anticodon-codon interaction. The importance of the strength of this interaction is examined and a correlation is found between the free-energy change (DeltaG(0)) of anticodon-codon association and the volume of the corresponding amino acids. This correlation is investigated in conjunction with the well-known one linking the hydrophobicity of the anticodons with that of the amino acids. We show that they can be considerated separately and that the energy vs. volume correlation may be explained by the process implicating the peptide bond formation between two successive amino acids during translation. This interpretation is supported by a statistical pattern of bases (purines or pyrimidines), observed in present coding genes, and by considerations involving the availability of the different kinds of amino acids. Finally, we try to explain the hydrophobicity correlation when reconstructing the events at the time of the so-called "RNA World". The whole of our investigation shows that the genetic code might be sufficiently robust to exist without the participation of pre-existing proteins, and that this robustness is a consequence of the physico-chemical properties of the four bases of the genetic system.     

Patterns of size variation and correlation in the dentition of the red colobus monkey (Colobus badius)

There have been numerous studies on variability and correlation in dental crown size, but the significance of the resulting patterns remains unclear. Regions of low variation and high correlation have been hypothesized to represent the poles of Butler's morphological fields, to be related to absolute tooth size, or to be related to morphological complexity of the teeth and functional efficiency. Variation and correlation of tooth lengths and breadths were investigated in 138 red colobus monkeys to further assess the relations among size associations, crown morphology, and absolute tooth size. In the maxilla and mandible, the postcanine teeth are the most highly correlated and least variable, followed by the incisors, then the canines. There are also lower correlations between premolars and molars than within either group. While there appears to be a relation between degree of morphological differentiation and levels of correlation and variation, there are no notable differences in the correlation of opponents along the dental arcade, which is the most important functional consideration. This suggests that different levels of correlation and variation within upper or lower teeth are “artifacts” of tooth dimensions that contribute to different geometric designs in different tooth groups as the germs develop. This morphological effect is coupled with the influence of integration fields, indicated by higher variability and lower correlations of the third molar, the largest or most molarized tooth. It is concluded that there are wide functional tolerances in occlusion with respect to the gross dimensions of dental crowns and their interrelationships.     

The relationship between the pleiotropic phenotypic effects of a mutation fixed by selection

A pleiotropic model of mutation is presented that allows for correlations between the effects of a new mutation and for the distribution of mutational effects to vary from being leptokurtic to normally distributed. Using this model I quantify how selection transforms the correlation between the effects of a new (random) mutation into the correlation between the effects of a mutation that is fixed by selection and contributes to an adaptation. Results suggest that under most conditions the correlation between the effects of a fixed mutation is less than the correlation between the effects of a new mutation. I also generalize previous results that quantified the expected size of a fixed mutation's effect on a character given an observed effect of that mutation on another character. In agreement with previous results, work here suggests that as the observed effect becomes large and beneficial the expected effect on another character approaches the expected effect of a new (random) mutation given the observed effect. Lastly, these theoretical results are related to recent empirical work that found beneficial mutations had a positive correlation in their pleiotropic effects.     

Hierarchical clustering of the correlation patterns: new method of domain identification in proteins

New method of identification of dynamical domains in proteins - Hierarchical Clustering of the Correlation Patterns (HCCP) is proposed. HCCP allows to identify the domains using single three-dimensional structure of the studied proteins and does not require any adjustable parameters that can influence the results. The method is based on hierarchical clustering performed on the matrices of correlation patterns, which are obtained by the transformation of ordinary pairwise correlation matrices. This approach allows to extract additional information from the correlation matrices, which increases reliability of domain identification. It is shown that HCCP is insensitive to small variations of the pairwise correlation matrices. Particularly it produces identical results if the data obtained for the same protein crystallized with different spatial positions of domains are used for analysis. HCCP can utilize correlation matrices obtained by any method such as normal mode or essential dynamics analysis, Gaussian network or anisotropic network models, etc. These features make HCCP an attractive method for domain identification in proteins.     

Genetic correlations and the evolution of photoperiodic time measurement within a local population of the pitcher-plant mosquito, Wyeomyia smithii

The genetic relationship between the daily circadian clock and the seasonal photoperiodic timer remains a subject of intense controversy. In Wyeomyia smithii, the critical photoperiod (an overt expression of the photoperiodic timer) evolves independently of the rhythmic response to the Nanda-Hamner protocol (an overt expression of the daily circadian clock) over a wide geographical range in North America. Herein, we focus on these two processes within a single local population in which there is a negative genetic correlation between them. We show that antagonistic selection against this genetic correlation rapidly breaks it down and, in fact, reverses its sign, showing that the genetic correlation is due primarily to linkage and not to pleiotropy. This rapid reversal of the genetic correlation within a small, single population means that it is difficult to argue that circadian rhythmicity forms the necessary, causal basis for the adaptive divergence of photoperiodic time measurement within populations or for the evolution of photoperiodic time measurement among populations over a broad geographical gradient of seasonal selection.     

Role of genetic and environmental factors in the realization of the hereditary potential of record-holding cows' longevity

A positive correlation is found between the level of record productivity of record-holding cows and duration of their farm use. A positive correlation is found to exist between the value of the record milk-yield and repetition of milk-yields similar to the record. It is stated that the overwhelming majority of record-holding cows are well developed, have solid sound constitution, better adaptability to living conditions, higher viability.     

Scaling analysis of the concentration dependence on elasticity of agarose gel

Since the critical exponent of the elastic modulus is related to the spatial dimension and the critical exponent of the correlation length, depending on the characteristics of elasticity, we experimentally evaluated both the elastic modulus of a sol-gel transition system and also the correlation length. We could determine the correlation length of agarose gel by the dynamic light scattering method; it was well described by the power law as a function of the deviation from the sol-gel transition point. Three scaling laws between the critical exponent of the correlation length (v) and that of the elastic shear modulus (t) were compared, and the critical exponent of the elastic modulus was described by the equation of de Gennes expression (t=1+v(d-2), where d is the spatial dimension). This result suggests that agarose fibers are stiff enough to show scalar elasticity.     

Stimulus dependent neural correlations in the auditory midbrain of the grassfrog (Rana temporaria L.)

Few-unit recordings were obtained using metal microelectrodes. Separation into single-unit spike trains was based on differences in spike amplitude and spike waveform. For that purpose a hardware microprocessor based spike waveform analyser was designed and built. Spikes are filtered by four matched filters and filter outputs at the moments of spike occurrence are read by a computer and used for off-line separation and spike waveform reconstruction. Thirty-one double unit recordings were obtained and correlation between the separated spike trains was determined. After stimulus correction correlation remained in only 8 of the double unit records. It appeared that in most cases this neural correlation was stimulus dependent. Continuous noise stimulation resulted in the strongest neural correlation remaining after correction for stimulus coupling, stimulation with 48 ms duration tonepips presented once per second generally did not result in a significant neural correlation after the correction procedure for stimulus lock. The usefulness of the additive model for neural correlation and the correction procedure based thereupon is discussed.     

Statistical analysis of fluorescence correlation spectroscopy: the standard deviation and bias

We present a detailed statistical analysis of fluorescence correlation spectroscopy for a wide range of timescales. The derivation is completely analytical and can provide an excellent tool for planning and analysis of FCS experiments. The dependence of the signal-to-noise ratio on different measurement conditions is extensively studied. We find that in addition to the shot noise and the noise associated with correlated molecular dynamics there is another source of noise that appears at very large lag times. We call this the "particle noise," as its behavior is governed by the number of particles that have entered and left the laser beam sample volume during large dwell times. The standard deviations of all the points on the correlation function are calculated analytically and shown to be in good agreement with experiments. We have also investigated the bias associated with experimental correlation function measurements. A "phase diagram" for FCS experiments is constructed that demonstrates the significance of the bias for any given experiment. We demonstrate that the value of the bias can be calculated and added back as a first-order correction to the experimental correlation function.     

Predicting the shapes of bones at a joint: application to the shoulder

This paper presents a novel method to explore the intrinsic morphological correlation between the bones of a shoulder joint (humerus and scapula). To model this correlation, canonical correlation analysis (CCA) is used. We also propose a technique to predict a three-dimensional (3D) bone shape from its adjoining segment at a joint based on partial least squares regression (PLS). The high dimensional 3D surface information of a bone is represented by a few variables using principal component analysis, which also captures the pattern of variability of the shapes in our datasets. Our results show that the humerus set and scapula set have highly linear morphological relationship and that the correlation information can be used as a classifier. In this study, primate shoulder bone datasets were categorised into two clusters: great apes (including humans) and monkeys. A leave one out experiment was performed to test the robustness of this prediction method. The prediction behaviour using this method shows statistically significantly better results than using the mean shape from the training set.     

Parameter dependence of correlation between the Shannon index and members of parametric diversity index family

We present detailed data on correlation of the Shannon diversity index with members of Hill's and Hurlbert's parametric index family. The correlation reaches its maximum in both cases at a definite parameter value. These specified data on correlation are exploitable when applying the above diversity indices. Namely, in case of their parallel use with the Shannon index a strong correlation between the indices should be avoided. The investigations were carried out on sets of moth and fly collections.Moreover, we hypothesized that a smaller distance between so-called sensitivity profiles of diversity indices predicts a larger correlation between the indices concerned. Based on investigations of the sensitivity profile distance between the Shannon index and members of parametric diversity index family as a function of index parameter, we point out that on the whole the above hypothesis is true. This makes possible to estimate the correlation of two diversity indices omitting troublesome index calculations on a large set of abundance lists.