Search results for "Econophysic"

showing 10 items of 51 documents

First results on applying a non-linear effect formalism to alliances between political parties and buy and sell dynamics

2016

We discuss a non linear extension of a model of alliances in politics, recently proposed by one of us. The model is constructed in terms of operators, describing the \emph{interest} of three parties to form, or not, some political alliance with the other parties. The time evolution of what we call \emph{the decision functions} is deduced by introducing a suitable hamiltonian, which describes the main effects of the interactions of the parties amongst themselves and with their \emph{environments}, {which are }generated by their electors and by people who still have no clear {idea }for which party to vote (or even if to vote). The hamiltonian contains some non-linear effects, which takes into…

Statistics and ProbabilityPhysics - Physics and SocietyFormal structureFOS: Physical sciencesPhysics and Society (physics.soc-ph)01 natural sciences010305 fluids & plasmassymbols.namesakePolitics0103 physical sciencesQuantum models in macroscopic system010306 general physicsSettore MAT/07 - Fisica MatematicaMathematical PhysicsMathematicsEconophysicsEconophysicMathematical Physics (math-ph)Condensed Matter PhysicsNonlinear systemFormalism (philosophy of mathematics)AlliancesymbolsDecision processHamiltonian (quantum mechanics)Mathematical economicsPhysica A: Statistical Mechanics and its Applications
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The adaptive nature of liquidity taking in limit order books

2014

In financial markets, the order flow, defined as the process assuming value one for buy market orders and minus one for sell market orders, displays a very slowly decaying autocorrelation function. Since orders impact prices, reconciling the persistence of the order flow with market efficiency is a subtle issue. A possible solution is provided by asymmetric liquidity, which states that the impact of a buy or sell order is inversely related to the probability of its occurrence. We empirically find that when the order flow predictability increases in one direction, the liquidity in the opposite side decreases, but the probability that a trade moves the price decreases significantly. While the…

Statistics and ProbabilityQuantitative Finance - Trading and Market MicrostructureStatistical Finance (q-fin.ST)Limit order book econophysics market efficiencyfinancial instruments and regulationAutocorrelationFinancial marketQuantitative Finance - Statistical FinanceStatistical and Nonlinear PhysicsProbability and statisticsTrading and Market Microstructure (q-fin.TR)Market liquidityFOS: Economics and businessFlow (mathematics)Order (exchange)risk measure and managementOrder bookEconomicsEconometricsmodels of financial marketStatistics Probability and UncertaintyPredictabilityStatistical and Nonlinear Physic
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Value-at-Risk and Tsallis statistics: risk analysis of the aerospace sector

2004

In this study, we analyze the aerospace stocks prices in order to characterize the sector behavior. The data analyzed cover the period from January 1987 to April 1999. We present a new index for the aerospace sector and we investigate the statistical characteristics of this index. Our results show that this index is well described by Tsallis distribution. We explore this result and modify the standard Value-at-Risk (VaR), financial risk assessment methodology in order to reflect an asset which obeys Tsallis non-extensive statistics.

Statistics and ProbabilityRisk analysisIndex (economics)Actuarial scienceStatistical Finance (q-fin.ST)EconophysicsStatistical Mechanics (cond-mat.stat-mech)Financial riskTsallis statisticsFOS: Physical sciencesQuantitative Finance - Statistical FinanceDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksCondensed Matter PhysicsFOS: Economics and businessEconomicsEconometricsTsallis distributionAsset (economics)Value at riskCondensed Matter - Statistical Mechanics
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Dynamics of a financial market index after a crash

2002

We discuss the statistical properties of index returns in a financial market just after a major market crash. The observed non-stationary behavior of index returns is characterized in terms of the exceedances over a given threshold. This characterization is analogous to the Omori law originally observed in geophysics. By performing numerical simulations and theoretical modelling, we show that the nonlinear behavior observed in real market crashes cannot be described by a GARCH(1,1) model. We also show that the time evolution of the Value at Risk observed just after a major crash is described by a power-law function lacking a typical scale.

Statistics and ProbabilityStatistical Finance (q-fin.ST)Index (economics)Actuarial scienceStatistical Mechanics (cond-mat.stat-mech)EconophysicsScale (ratio)Autoregressive conditional heteroskedasticityFinancial marketFOS: Physical sciencesQuantitative Finance - Statistical FinanceCrashFunction (mathematics)Condensed Matter PhysicsFOS: Economics and businessEconophysicsFinancial marketsCrashesValue at RiskEconometricsEconomicsCondensed Matter - Statistical MechanicsValue at riskPhysica A: Statistical Mechanics and its Applications
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Volatility in Financial Markets: Stochastic Models and Empirical Results

2002

We investigate the historical volatility of the 100 most capitalized stocks traded in US equity markets. An empirical probability density function (pdf) of volatility is obtained and compared with the theoretical predictions of a lognormal model and of the Hull and White model. The lognormal model well describes the pdf in the region of low values of volatility whereas the Hull and White model better approximates the empirical pdf for large values of volatility. Both models fails in describing the empirical pdf over a moderately large volatility range.

Statistics and ProbabilityStatistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)Stochastic modellingEconophysicFinancial marketFOS: Physical sciencesQuantitative Finance - Statistical FinanceStatistical and Nonlinear PhysicsProbability density functionStochastic processeCondensed Matter PhysicsEmpirical probabilitySettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)FOS: Economics and businessVolatilityLognormal modelHullEconomicsEconometricsMathematical PhysicVolatility (finance)Condensed Matter - Statistical Mechanics
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Monte Carlo simulations of a trader-based market model

2002

Abstract We present a detailed analysis of the stationary state and the parameter sensitivity of a trader-based market model suggested in Bak et al. (Physica A 246 (1997) 430). The model in question takes only so-called noise-traders into account and its properties are determined by mutual imitation of the traders and volatility feedback. We show that the stationary state of the model can be characterized by a log-normal distribution of the bid and ask prices relative to the current market price. In the stationary state the model is able to reproduce the so-called stylized facts of real markets. This property is stable under variation of the essential parameters of the model, number of trad…

Statistics and ProbabilityStylized factEconophysicsmedia_common.quotation_subjectMonte Carlo methodCondensed Matter PhysicsAsymmetryMarket priceEconomicsEconometricsVolatility (finance)Bid priceStationary statemedia_commonPhysica A: Statistical Mechanics and its Applications
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Understanding the determinants of volatility clustering in terms of stationary Markovian processes

2016

Abstract Volatility is a key variable in the modeling of financial markets. The most striking feature of volatility is that it is a long-range correlated stochastic variable, i.e. its autocorrelation function decays like a power-law τ − β for large time lags. In the present work we investigate the determinants of such feature, starting from the empirical observation that the exponent β of a certain stock’s volatility is a linear function of the average correlation of such stock’s volatility with all other volatilities. We propose a simple approach consisting in diagonalizing the cross-correlation matrix of volatilities and investigating whether or not the diagonalized volatilities still kee…

Statistics and ProbabilityVolatility clusteringVolatility Econophysics Long-range correlation Stochastic processes First passage timeStochastic volatilityProbability density functionCondensed Matter PhysicsSABR volatility model01 natural sciencesSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)010305 fluids & plasmasHeston modelFinancial models with long-tailed distributions and volatility clustering0103 physical sciencesForward volatilityEconometricsVolatility (finance)010306 general physicsMathematics
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Univariate and multivariate statistical aspects of equity volatility

2004

We discuss univariate and multivariate statistical properties of volatility time series of equities traded in a financial market. Specifically, (i) we introduce a two-region stochastic volatility model able to well describe the unconditional pdf of volatility in a wide range of values and (ii) we quantify the stability of the results of a correlation-based clustering procedure applied to synchronous time evolution of a set of volatility time series.

Stochastic volatilityFinancial models with long-tailed distributions and volatility clusteringVolatility smileUnivariateEconometricsForward volatilityEconomicsVolatility (finance)Implied volatilitySettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)volatility financial markets econophysics log range correlated processes stochastic processesHeston model
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Some past and present challenges of econophysics

2016

We discuss the cultural background that was shared by some of the first econophysicists when they started to work on economic and financial problems with methods and tools of statistical physics. In particular we discuss about the role of stylized facts and statistical physical laws in economics and statistical physics respectively. As an example of the problems and potentials associated with the interaction of different communities of scholars dealing with problems observed in economic and financial systems we briefly discuss the development and the perspectives of the use of tools and concepts of networks in econophysics, economics and finance.

Stylized factEconophysicsGeneral Physics and AstronomyStatistical finance01 natural sciences010305 fluids & plasmasCultural backgroundPhysics and Astronomy (all)Work (electrical)0103 physical sciencesEconomicsGeneral Materials ScienceMaterials Science (all)Positive economicsPhysical and Theoretical Chemistry010306 general physicsPhysical law
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Statistics of order flow

2010

market microstructureeconophysicsfinancial marketOrder flow market microstructure financial markets econophysicsOrder flow
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