Search results for " data analysis"

showing 10 items of 231 documents

Kullback-Leibler distance as a measure of the information filtered from multivariate data

2007

We show that the Kullback-Leibler distance is a good measure of the statistical uncertainty of correlation matrices estimated by using a finite set of data. For correlation matrices of multivariate Gaussian variables we analytically determine the expected values of the Kullback-Leibler distance of a sample correlation matrix from a reference model and we show that the expected values are known also when the specific model is unknown. We propose to make use of the Kullback-Leibler distance to estimate the information extracted from a correlation matrix by correlation filtering procedures. We also show how to use this distance to measure the stability of filtering procedures with respect to s…

Physics - Physics and SocietyKullback–Leibler divergenceStatistical Finance (q-fin.ST)Covariance matrixEXPRESSION DATAFOS: Physical sciencesQuantitative Finance - Statistical FinanceMultivariate normal distributionPhysics and Society (physics.soc-ph)Measure (mathematics)Stability (probability)Hierarchical clusteringDistance correlationFOS: Economics and businessPhysics - Data Analysis Statistics and ProbabilityStatisticsTime seriesAlgorithmData Analysis Statistics and Probability (physics.data-an)MATRICESMathematics
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How does the market react to your order flow?

2012

We present an empirical study of the intertwined behaviour of members in a financial market. Exploiting a database where the broker that initiates an order book event can be identified, we decompose the correlation and response functions into contributions coming from different market participants and study how their behaviour is interconnected. We find evidence that (1) brokers are very heterogeneous in liquidity provision -- some are consistently liquidity providers while others are consistently liquidity takers. (2) The behaviour of brokers is strongly conditioned on the actions of {\it other} brokers. In contrast brokers are only weakly influenced by the impact of their own previous ord…

Physics - Physics and SocietyQuantitative Finance - Trading and Market MicrostructureMarket microstructureLimit order marketFinancial marketFOS: Physical sciencesBehavioural financePhysics and Society (physics.soc-ph)Market microstructureMonetary economicsMarket dynamicsFinancial marketFinancial markets microstructure Econophysics stochasti processesTrading and Market Microstructure (q-fin.TR)Market liquidityFOS: Economics and businessCompetition (economics)Empirical researchOrder (exchange)Physics - Data Analysis Statistics and ProbabilityOrder bookBusinessGeneral Economics Econometrics and FinanceData Analysis Statistics and Probability (physics.data-an)FinanceQuantitative Finance
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Spanning Trees and bootstrap reliability estimation in correlation based networks

2007

We introduce a new technique to associate a spanning tree to the average linkage cluster analysis. We term this tree as the Average Linkage Minimum Spanning Tree. We also introduce a technique to associate a value of reliability to links of correlation based graphs by using bootstrap replicas of data. Both techniques are applied to the portfolio of the 300 most capitalized stocks traded at New York Stock Exchange during the time period 2001-2003. We show that the Average Linkage Minimum Spanning Tree recognizes economic sectors and sub-sectors as communities in the network slightly better than the Minimum Spanning Tree does. We also show that the average reliability of links in the Minimum …

Physics - Physics and SocietySpanning treecorrelation analysiApplied MathematicsReliability (computer networking)FOS: Physical sciencesPhysics and Society (physics.soc-ph)Minimum spanning treeTerm (time)CorrelationTree (data structure)complex networkStock exchangeModeling and SimulationPhysics - Data Analysis Statistics and ProbabilityStatisticsAverage Linkage Cluster AnalysisbootstrapEngineering (miscellaneous)Data Analysis Statistics and Probability (physics.data-an)Mathematicscluster analysis
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Economic Sector Identification in a Set of Stocks Traded at the New York Stock Exchange: A Comparative Analysis

2006

We review some methods recently used in the literature to detect the existence of a certain degree of common behavior of stock returns belonging to the same economic sector. Specifically, we discuss methods based on random matrix theory and hierarchical clustering techniques. We apply these methods to a set of stocks traded at the New York Stock Exchange. The investigated time series are recorded at a daily time horizon. All the considered methods are able to detect economic information and the presence of clusters characterized by the economic sector of stocks. However, different methodologies provide different information about the considered set. Our comparative analysis suggests that th…

Physics - Physics and SocietyStatistical Finance (q-fin.ST)Correlation coefficientEconomic sectorEconophysicsFOS: Physical sciencesQuantitative Finance - Statistical FinanceTime horizonPhysics and Society (physics.soc-ph)minimum spanning treeSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Hierarchical clusteringFOS: Economics and businessEconomic informationStock exchangePhysics - Data Analysis Statistics and ProbabilityEconomicsEconometricsfinancial marketRandom matrixData Analysis Statistics and Probability (physics.data-an)Stock (geology)
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Shrinkage and spectral filtering of correlation matrices: A comparison via the Kullback-Leibler distance

2007

The problem of filtering information from large correlation matrices is of great importance in many applications. We have recently proposed the use of the Kullback-Leibler distance to measure the performance of filtering algorithms in recovering the underlying correlation matrix when the variables are described by a multivariate Gaussian distribution. Here we use the Kullback-Leibler distance to investigate the performance of filtering methods based on Random Matrix Theory and on the shrinkage technique. We also present some results on the application of the Kullback-Leibler distance to multivariate data which are non Gaussian distributed.

Physics - Physics and SocietyStatistics::TheoryStatistical Finance (q-fin.ST)MathematicsofComputing_NUMERICALANALYSISFOS: Physical sciencesQuantitative Finance - Statistical FinancePhysics and Society (physics.soc-ph)Statistics::ComputationFOS: Economics and businessStatistics::Machine LearningComputingMethodologies_PATTERNRECOGNITIONPhysics - Data Analysis Statistics and ProbabilityStatistics::MethodologyCOVARIANCE-MATRIXData Analysis Statistics and Probability (physics.data-an)
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Correlation based networks of equity returns sampled at different time horizons

2006

We investigate the planar maximally filtered graphs of the portfolio of the 300 most capitalized stocks traded at the New York Stock Exchange during the time period 2001-2003. Topological properties such as the average length of shortest paths, the betweenness and the degree are computed on different planar maximally filtered graphs generated by sampling the returns at different time horizons ranging from 5 min up to one trading day. This analysis confirms that the selected stocks compose a hierarchical system progressively structuring as the sampling time horizon increases. Finally, a cluster formation, associated to economic sectors, is quantitatively investigated.

Physics - Physics and Societynetworks of equity different time horizonsStatistical Finance (q-fin.ST)Equity (finance)Quantitative Finance - Statistical FinanceFOS: Physical sciencesRangingPhysics and Society (physics.soc-ph)Condensed Matter PhysicsElectronic Optical and Magnetic MaterialsCorrelationFOS: Economics and businessBetweenness centralityStock exchangePhysics - Data Analysis Statistics and ProbabilityStatisticsHierarchical control systemPortfolioSampling timeData Analysis Statistics and Probability (physics.data-an)Mathematics
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A method for approximating optimal statistical significances with machine-learned likelihoods

2022

The European physical journal / C 82(11), 993 (2022). doi:10.1140/epjc/s10052-022-10944-3

Physics and Astronomy (miscellaneous)Gluonsboosted particleFOS: Physical sciencesTop Quark530High Energy Physics - ExperimentHigh Energy Physics - Experiment (hep-ex)High Energy Physics - Phenomenology (hep-ph)statistical analysisddc:530numerical calculationsEngineering (miscellaneous)Monte CarloInstrumentation and Methods for Astrophysics (astro-ph.IM)new physicsFísicadijet: final statefinal state [dijet]sensitivityHigh Energy Physics - Phenomenologymachine learningCERN LHC CollPhysics - Data Analysis Statistics and ProbabilitySubstructureAstrophysics - Instrumentation and Methods for AstrophysicsData Analysis Statistics and Probability (physics.data-an)
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An iterative method in a probabilistic approach to the spectral inverse problem - Differential emission measure from line spectra and broadband data

2010

Inverse problems are of great importance in astrophysics for deriving information about the physical characteristics of hot optically thin plasma sources from their EUV and X-ray spectra. We describe and test an iterative method developed within the framework of a probabilistic approach to the spectral inverse problem for determining the thermal structures of the emitting plasma. We also demonstrate applications of this method to both high resolution line spectra and broadband imaging data. Our so-called Bayesian iterative method (BIM) is an iterative procedure based on Bayes' theorem and is used to reconstruct differential emission measure (DEM) distributions. To demonstrate the abilities …

Physics010504 meteorology & atmospheric sciencesIterative methodProbabilistic logicFOS: Physical sciencesAstronomy and AstrophysicsObservableAstrophysicsInverse problem01 natural sciencesMeasure (mathematics)Spectral lineComputational physicsSettore FIS/05 - Astronomia E AstrofisicaAstrophysics - Solar and Stellar AstrophysicsSpace and Planetary ScienceRobustness (computer science)Sun: corona / Sun: UV radiation / Sun: X-rays gamma rays / atomic data / methods: data analysis / techniques: spectroscopic0103 physical sciencesBroadbandPhysics::Space PhysicsAstrophysics::Solar and Stellar Astrophysics010303 astronomy & astrophysicsSolar and Stellar Astrophysics (astro-ph.SR)0105 earth and related environmental sciences
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On the importance of background subtraction in the analysis of coronal loops observed with TRACE

2010

In the framework of TRACE coronal observations, we compare the analysis and diagnostics of a loop after subtracting the background with two different and independent methods. The dataset includes sequences of images in the 171 A, 195 A filter bands of TRACE. One background subtraction method consists in taking as background values those obtained from interpolation between concentric strips around the analyzed loop. The other method is a pixel-to-pixel subtraction of the final image when the loop had completely faded out, already used by Reale & Ciaravella 2006. We compare the emission distributions along the loop obtained with the two methods and find that they are considerably differen…

PhysicsBackground subtractionTrace (linear algebra)Subtractionastrofisica Fisica solare Sun: corona Sun: X-rays gamma rays method: data analysisFOS: Physical sciencesAstronomy and AstrophysicsAstrophysicsSTRIPSCoronal loopFilter (signal processing)law.inventionComputational physicsLoop (topology)Settore FIS/05 - Astronomia E AstrofisicaAstrophysics - Solar and Stellar AstrophysicsSpace and Planetary SciencelawSolar and Stellar Astrophysics (astro-ph.SR)Interpolation
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A New Look at Spitzer Primary Transit Observations of the Exoplanet HD 189733b

2014

Blind source separation techniques are used to reanalyse two exoplanetary transit lightcurves of the exoplanet HD189733b recorded with the IR camera IRAC on board the Spitzer Space Telescope at 3.6$\mu$m during the "cold" era. These observations, together with observations at other IR wavelengths, are crucial to characterise the atmosphere of the planet HD189733b. Previous analyses of the same datasets reported discrepant results, hence the necessity of the reanalyses. The method we used here is based on the Independent Component Analysis (ICA) statistical technique, which ensures a high degree of objectivity. The use of ICA to detrend single photometric observations in a self-consistent wa…

PhysicsEarth and Planetary Astrophysics (astro-ph.EP)AstronomyFOS: Physical sciencesAstronomy and AstrophysicsLight curveBlind signal separationIndependent component analysisExoplanetdata analysis planets and satellites: atmospheres planets and satellites: individual: HD 189733b techniques: photometric [methods]Settore FIS/05 - Astronomia E AstrofisicaSpitzer Space TelescopeSpace and Planetary SciencePlanetPrimary (astronomy)methods: data analysis planets and satellites: atmospheres planets and satellites: individual: HD 189733b techniques: photometricTransit (astronomy)Astrophysics - Earth and Planetary Astrophysics
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