Search results for "Stock"

showing 10 items of 878 documents

The Heisenberg picture in the analysis of stock markets and in other sociological contexts

2007

We review some recent results concerning some toy models of stock markets. Our models are suggested by the discrete nature of the number of shares and of the cash which are exchanged in a real market, and by the existence of conserved quantities, like the total number of shares or some linear combination of the cash and the shares. This suggests to use the same tools used in quantum mechanics and, in particular, the Heisenberg picture to describe the time behavior of the portfolio of each trader. We finally propose the use of this same framework in other sociological contexts.

Statistics and ProbabilityFinancial economicsmedia_common.quotation_subjectGeneral Social SciencesShareholder valueConserved quantityComputer Science::Computational Engineering Finance and ScienceCashEconomicsPortfolioStock marketLinear combinationHeisenberg pictureStock (geology)media_commonQuality & Quantity
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Empirical investigation of stock price dynamics in an emerging market

1999

Abstract We study the development of an emerging market – the Budapest Stock Exchange – by investigating the time evolution of some statistical properties of heavily traded stocks. Moving quarter by quarter over a period of two and a half years we analyze the scaling properties of the standard deviation of intra-day log-price changes. We observe scaling using both seconds and ticks as units of time. For the investigated stocks a Levy shape is a good approximation to the probability density function of tick-by-tick log-price changes in each quarter: the index of the distribution follows an increasing trend, suggesting it could be used as a measure of market efficiency.

Statistics and ProbabilityIndex (economics)EconophysicsStock exchangeEconometricsEconomicsCapitalization-weighted indexProbability density functionCondensed Matter PhysicsQuarter (United States coin)Emerging marketsStandard deviationPhysica A: Statistical Mechanics and its Applications
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Stock market dynamics and turbulence: parallel analysis of fluctuation phenomena

1997

Abstract We report analogies and differences between the fluctuations in an economic index and the fluctuations in velocity of a fluid in a fully turbulent state. Specifically, we systematically compare (i) the statistical properties of the S&P 500 cash index recorded during the period January 84–December 89 with (ii) the statistical properties of the velocity of turbulent air measured in the atmospheric surface layer about 6 m above a wheat canopy in the Connecticut Agricultural Research Station. We find non-Gaussian statistics, and intermittency, for both processes (i) and (ii) but the deviation from a Gaussian probability density function are different for stock market dynamics and turbu…

Statistics and ProbabilityIndex (economics)MeteorologyTurbulenceGaussianDynamics (mechanics)Probability density functionCondensed Matter Physicslaw.inventionPhysics::Fluid Dynamicssymbols.namesakelawIntermittencysymbolsStock marketSurface layerStatistical physicsMathematicsPhysica A: Statistical Mechanics and its Applications
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Hitting Time Distributions in Financial Markets

2006

We analyze the hitting time distributions of stock price returns in different time windows, characterized by different levels of noise present in the market. The study has been performed on two sets of data from US markets. The first one is composed by daily price of 1071 stocks trade for the 12-year period 1987-1998, the second one is composed by high frequency data for 100 stocks for the 4-year period 1995-1998. We compare the probability distribution obtained by our empirical analysis with those obtained from different models for stock market evolution. Specifically by focusing on the statistical properties of the hitting times to reach a barrier or a given threshold, we compare the prob…

Statistics and ProbabilityPhysics - Physics and SocietyAutoregressive conditional heteroskedasticityStock market modelFOS: Physical sciencesPhysics and Society (physics.soc-ph)Langevin-type equationHeston modelEconophysics; Stock market model; Langevin-type equation; Heston model; Complex SystemsFOS: Economics and businessEconometricsMathematicsGeometric Brownian motionStatistical Finance (q-fin.ST)Actuarial scienceEconophysicFinancial marketHitting timeQuantitative Finance - Statistical FinanceComplex SystemsProbability and statisticsCondensed Matter PhysicsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Heston modelPhysics - Data Analysis Statistics and ProbabilityProbability distributionStock marketData Analysis Statistics and Probability (physics.data-an)
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Degree stability of a minimum spanning tree of price return and volatility

2002

We investigate the time series of the degree of minimum spanning trees obtained by using a correlation based clustering procedure which is starting from (i) asset return and (ii) volatility time series. The minimum spanning tree is obtained at different times by computing correlation among time series over a time window of fixed length $T$. We find that the minimum spanning tree of asset return is characterized by stock degree values, which are more stable in time than the ones obtained by analyzing a minimum spanning tree computed starting from volatility time series. Our analysis also shows that the degree of stocks has a very slow dynamics with a time-scale of several years in both cases.

Statistics and ProbabilityPhysics - Physics and SocietyFOS: Physical sciencesPhysics and Society (physics.soc-ph)Minimum spanning treeFOS: Economics and businessTime windowsStatisticsMathematical PhysicCluster analysisStock (geology)Condensed Matter - Statistical MechanicsMathematicsSpanning treeStatistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)EconophysicQuantitative Finance - Statistical FinanceStatistical and Nonlinear PhysicsAsset returnCondensed Matter PhysicsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)VolatilityCorrelation-based clusteringPrice returnVolatility (finance)
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Damping in quantum love affairs

2011

In a series of recent papers we have used an operatorial technique to describe stock markets and, in a different context, {\em love affairs} and their time evolutions. The strategy proposed so far does not allow any dumping effect. In this short note we show how, within the same framework, a strictly non periodic or quasi-periodic effect can be introduced in the model by describing in some details a linear Alice-Bob love relation with damping.

Statistics and ProbabilityPhysics - Physics and SocietyQuantum PhysicsQuantum tools for classical systemsFOS: Physical sciencesPhysics and Society (physics.soc-ph)Nonlinear Sciences - Chaotic DynamicsCondensed Matter PhysicsSocial systemDumpingEconomicsChaotic Dynamics (nlin.CD)Quantum Physics (quant-ph)Settore MAT/07 - Fisica MatematicaMathematical economicsQuantumStock (geology)Physica A: Statistical Mechanics and its Applications
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Dynamics of the Number of Trades of Financial Securities

1999

We perform a parallel analysis of the spectral density of (i) the logarithm of price and (ii) the daily number of trades of a set of stocks traded in the New York Stock Exchange. The stocks are selected to be representative of a wide range of stock capitalization. The observed spectral densities show a different power-law behavior. We confirm the $1/f^2$ behavior for the spectral density of the logarithm of stock price whereas we detect a $1/f$-like behavior for the spectral density of the daily number of trades.

Statistics and ProbabilityPhysics::Physics and SocietyStatistical Finance (q-fin.ST)LogarithmStatistical Mechanics (cond-mat.stat-mech)Spectral densityFOS: Physical sciencesQuantitative Finance - Statistical FinanceCondensed Matter PhysicsStock priceFOS: Economics and businessStock exchangeComputer Science::Computational Engineering Finance and ScienceEconometricsStock (geology)Condensed Matter - Statistical MechanicsMathematics
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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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A quantum statistical approach to simplified stock markets

2009

We use standard perturbation techniques originally formulated in quantum (statistical) mechanics in the analysis of a toy model of a stock market which is given in terms of bosonic operators. In particular we discuss the probability of transition from a given value of the {\em portfolio} of a certain trader to a different one. This computation can also be carried out using some kind of {\em Feynman graphs} adapted to the present context.

Statistics and ProbabilityToy modelComputationCondensed Matter Physicsstock marketFOS: Economics and businesssymbols.namesakeQuantum probabilitysymbolsFeynman diagramPortfolioApplied mathematicsnumber operatorsStock marketQuantitative Finance - General FinanceGeneral Finance (q-fin.GN)QuantumMathematical economicsSettore MAT/07 - Fisica MatematicaStock (geology)Mathematics
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The role of information in a two-traders market

2014

In a very simple stock market, made by only two \emph{initially equivalent} traders, we discuss how the information can affect the performance of the traders. More in detail, we first consider how the portfolios of the traders evolve in time when the market is \emph{closed}. After that, we discuss two models in which an interaction with the outer world is allowed. We show that, in this case, the two traders behave differently, depending on \textbf{i)} the amount of information which they receive from outside; and \textbf{ii)}the quality of this information.

Statistics and Probabilitymedia_common.quotation_subjectComputational Finance (q-fin.CP)Stock marketsCondensed Matter PhysicsAffect (psychology)MicroeconomicsFOS: Economics and businessQuantitative Finance - Computational FinanceOpen systemInformationStock marketQuality (business)BusinessSettore MAT/07 - Fisica MatematicaSimple (philosophy)media_common
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