0000000000353816

AUTHOR

János Kertész

showing 6 related works from this author

The limit order book on different time scales

2007

Financial markets can be described on several time scales. We use data from the limit order book of the London Stock Exchange (LSE) to compare how the fluctuation dominated microstructure crosses over to a more systematic global behavior.

FOS: Economics and businessPhysics - Physics and SocietyQuantitative Finance - Trading and Market MicrostructureStock exchangePhysics - Data Analysis Statistics and ProbabilityFinancial marketEconomicsEconometricsFOS: Physical sciencesPhysics and Society (physics.soc-ph)Data Analysis Statistics and Probability (physics.data-an)Trading and Market Microstructure (q-fin.TR)
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Focus on statistical physics modeling in economics and finance

2011

This focus issue presents a collection of papers on recent results in statistical physics modeling in economics and finance, commonly known as econophysics. We touch briefly on the history of this relatively new multi-disciplinary field, summarize the motivations behind its emergence and try to characterize its specific features. We point out some research aspects that must be improved and briefly discuss the topics the research field is moving toward. Finally, we give a short account of the papers collected in this issue.

PhysicsFocus (computing)EconophysicsPoint (typography)Financial economicsECONOPHYSICSGeneral Physics and AstronomyStatistical physicsField (geography)
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Statistically validated mobile communication networks: the evolution of motifs in European and Chinese data

2014

Big data open up unprecedented opportunities to investigate complex systems including the society. In particular, communication data serve as major sources for computational social sciences but they have to be cleaned and filtered as they may contain spurious information due to recording errors as well as interactions, like commercial and marketing activities, not directly related to the social network. The network constructed from communication data can only be considered as a proxy for the network of social relationships. Here we apply a systematic method, based on multiple hypothesis testing, to statistically validate the links and then construct the corresponding Bonferroni network, gen…

FOS: Computer and information sciencesPhysics - Physics and SocietyBig dataFOS: Physical sciencesGeneral Physics and AstronomyPhysics and Society (physics.soc-ph)computer.software_genre01 natural sciences010305 fluids & plasmassymbols.namesake0103 physical sciences010306 general physicsProxy (statistics)Social and Information Networks (cs.SI)PhysicsSocial networkbusiness.industryComputer Science - Social and Information NetworksComplex networkcomplex networks social systems statistically validated networks mobile call records 3-motifsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Bonferroni correctionMobile phonesymbolsMobile telephonyData miningRaw databusinesscomputer
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Identification of clusters of companies in stock indices via Potts super-paramagnetic transitions

2000

The clustering of companies within a specific stock market index is studied by means of super-paramagnetic transitions of an appropriate q-state Potts model where the spins correspond to companies and the interactions are functions of the correlation coefficients determined from the time dependence of the companies' individual stock prices. The method is a generalization of the clustering algorithm by Domany et. al. to the case of anti-ferromagnetic interactions corresponding to anti-correlations. For the Dow Jones Industrial Average where no anti-correlations were observed in the investigated time period, the previous results obtained by different tools were well reproduced. For the Standa…

Statistics and ProbabilityStatistical Mechanics (cond-mat.stat-mech)SpinsFOS: Physical sciencesCondensed Matter PhysicsStock market indexParamagnetismCluster (physics)Statistical physicsCluster analysisStock (geology)Condensed Matter - Statistical MechanicsPotts modelMathematics
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Diffusive behavior and the modeling of characteristic times in limit order executions

2007

We present an empirical study of the first passage time (FPT) of order book prices needed to observe a prescribed price change Delta, the time to fill (TTF) for executed limit orders and the time to cancel (TTC) for canceled ones in a double auction market. We find that the distribution of all three quantities decays asymptotically as a power law, but that of FPT has significantly fatter tails than that of TTF. Thus a simple first passage time model cannot account for the observed TTF of limit orders. We propose that the origin of this difference is the presence of cancellations. We outline a simple model, which assumes that prices are characterized by the empirically observed distribution …

Physics - Physics and SocietyFOS: Physical sciencesPhysics and Society (physics.soc-ph)Power lawFOS: Economics and businessOrder bookTime to fillLimit (mathematics)Statistical physicsMicrostructureMathematicsQuantitative Finance - Trading and Market MicrostructureEconophysicsLimit order marketEconophysicProbability and statisticsFirst passage timeTrading and Market Microstructure (q-fin.TR)Distribution (mathematics)Physics - Data Analysis Statistics and ProbabilityExponentCensored dataFirst-hitting-time modelGeneral Economics Econometrics and FinanceFinanceData Analysis Statistics and Probability (physics.data-an)
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Diffusive Behavior and the Modeling of Characteristic Times in Limit Order Executions

2007

We present a study of the order book data of the London Stock Exchange for five highly liquid stocks traded during the calendar year 2002. Specifically, we study the first passage time of order book prices needed to observe a prescribed price change Delta, the time to fill (TTF) for executed limit orders and the time to cancel (TTC) for canceled ones. We find that the distribution of the first passage time decays asymptotically in time as a power law with an exponent L_FPT ~ 1.5. The median of the same quantity scales as Delta^1.6, which is different from the Delta^2 behavior expected for Brownian motion. The quantities TTF, and TTC are also asymptotically power law distributed with exponen…

StatisticsOrder bookExponentStatistical physicsLimit (mathematics)First-hitting-time modelRandom walkPower lawScalingBrownian motionMathematicsSSRN Electronic Journal
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