0000000000254363

AUTHOR

T. Di Matteo

showing 8 related works from this author

Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development

2005

The scaling properties encompass in a simple analysis many of the volatility characteristics of financial markets. That is why we use them to probe the different degree of markets development. We empirically study the scaling properties of daily Foreign Exchange rates, Stock Market indices and fixed income instruments by using the generalized Hurst approach. We show that the scaling exponents are associated with characteristics of the specific markets and can be used to differentiate markets in their stage of development. The robustness of the results is tested by both Monte-Carlo studies and a computation of the scaling in the frequency-domain.

jel:G1jel:C1jel:C00jel:G00Scaling exponents; Time series analysis; Multi-fractals
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Correlation filtering in financial time series

2005

We apply a method to filter relevant information from the correlation coefficient matrix by extracting a network of relevant interactions. This method succeeds to generate networks with the same hierarchical structure of the Minimum Spanning Tree but containing a larger amount of links resulting in a richer network topology allowing loops and cliques. In Tumminello et al. \cite{TumminielloPNAS05}, we have shown that this method, applied to a financial portfolio of 100 stocks in the USA equity markets, is pretty efficient in filtering relevant information about the clustering of the system and its hierarchical structure both on the whole system and within each cluster. In particular, we have…

Physics - Physics and SocietynetworksFOS: Physical sciencesPhysics and Society (physics.soc-ph)econophysiccomplex system
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Vaccinazione anti-influenzale dei pediatri nella stagione 2014-2015.

2015

Settore MED/38 - Pediatria Generale E SpecialisticaVaccinazione anti-influenzale pediatria di famiglia pediatria di comunità
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A tool for filtering information in complex systems

2005

We introduce a technique to filter out complex data-sets by extracting a subgraph of representative links. Such a filtering can be tuned up to any desired level by controlling the genus of the resulting graph. We show that this technique is especially suitable for correlation based graphs giving filtered graphs which preserve the hierarchical organization of the minimum spanning tree but containing a larger amount of information in their internal structure. In particular in the case of planar filtered graphs (genus equal to 0) triangular loops and 4 element cliques are formed. The application of this filtering procedure to 100 stocks in the USA equity markets shows that such loops and cliqu…

Physics - Physics and SocietyComputer scienceComplex systemFOS: Physical sciencesPhysics and Society (physics.soc-ph)Minimum spanning treecomputer.software_genrePlanarHierarchical organizationINTERNETCondensed Matter - Statistical MechanicsComplex data typeMultidisciplinarySmall-world networkStatistical Mechanics (cond-mat.stat-mech)SMALL-WORLD NETWORKSFilter (signal processing)Disordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksComplex networkWEBDYNAMIC ASSET TREESPhysical SciencesGRAPHData miningAlgorithmcomputerMathematicsofComputing_DISCRETEMATHEMATICS
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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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An interest rates cluster analysis

2004

An empirical analysis of interest rates in money and capital markets is performed. We investigate a set of 34 different weekly interest rate time series during a time period of 16 years between 1982 and 1997. Our study is focused on the collective behavior of the stochastic fluctuations of these time-series which is investigated by using a clustering linkage procedure. Without any a priori assumption, we individuate a meaningful separation in 6 main clusters organized in a hierarchical structure.

Statistics and ProbabilityCollective behaviormedia_common.quotation_subjectFOS: Physical sciencesLinkage (mechanical)computer.software_genrelaw.inventionFOS: Economics and businesslawEconometricsCluster (physics)Cluster analysisCondensed Matter - Statistical Mechanicsmedia_commonStatistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)EconophysicsSeries (mathematics)Quantitative Finance - Statistical FinanceCondensed Matter PhysicsInterest rateCondensed Matter - Other Condensed MatterData miningCapital marketcomputerOther Condensed Matter (cond-mat.other)
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Using the Scaling Analysis to Characterize Financial Markets

2003

We empirically analyze the scaling properties of daily Foreign Exchange rates, Stock Market indices and Bond futures across different financial markets. We study the scaling behaviour of the time series by using a generalized Hurst exponent approach. We verify the robustness of this approach and we compare the results with the scaling properties in the frequency-domain. We find evidence of deviations from the pure Brownian motion behavior. We show that these deviations are associated with characteristics of the specific markets and they can be, therefore, used to distinguish the different degrees of development of the markets.

FOS: Economics and businessStatistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)jel:G1Quantitative Finance - Statistical FinanceFOS: Physical sciencesCondensed Matter - Statistical Mechanicsscaling exponents time series analysis multi-fractals financial market
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On the interplay between multiscaling and stocks dependence

2019

We find a nonlinear dependence between an indicator of the degree of multiscaling of log-price time series of a stock and the average correlation of the stock with respect to the other stocks traded in the same market. This result is a robust stylized fact holding for different financial markets. We investigate this result conditional on the stocks' capitalization and on the kurtosis of stocks' log-returns in order to search for possible confounding effects. We show that a linear dependence with the logarithm of the capitalization and the logarithm of kurtosis does not explain the observed stylized fact, which we interpret as being originated from a deeper relationship.

Multivariate propertiePhysics::Physics and SocietyStatistical Finance (q-fin.ST)050208 financeUnivariate properties05 social sciencesQuantitative Finance - Statistical FinanceFOS: Economics and businessMultiscalingNonlinear systemUnivariate propertieComputer Science::Computational Engineering Finance and Science0502 economics and businessEconometrics050207 economicsDependenceGeneral Economics Econometrics and FinanceFinanceStock (geology)Mathematics
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