Search results for "FINANCIAL MARKET"

showing 10 items of 198 documents

How to control stock markets

1994

This paper provides a different approach to the analysis of imperfect stock markets. The model we are concerned with is described by the interaction of three institutional classes of agents (the specialist trader, the professional trader and the non-professional trader), sharing different information. The dynamical discrete-time system obtained can be changed into a second-order linear difference equation forced by the fundamental value of the specialist trader. Using typical tools of control theory, we study the behaviour of the professional trader’s fundamental value influenced by the specialist’s one. © 1994 Taylor & Francis Group, LLC.

MicroeconomicsControl theory dynamic systems difference equationsControl and Systems EngineeringStock exchangeFinancial marketBusinessImperfectMathematical economicsStock (geology)Computer Science ApplicationsTheoretical Computer Science
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Market Timing with Moving Averages: Anatomy and Performance of Trading Rules

2015

The underlying concept behind the technical trading indicators based on moving averages of prices has remained unaltered for more than half of a century. The development in this field has consisted in proposing new ad-hoc rules and using more elaborate types of moving averages in the existing rules, without any deeper analysis of commonalities and differences between miscellaneous choices for trading rules and moving averages. The first contribution of this paper is to uncover the anatomy of market timing rules with moving averages. Our analysis offers a new and very insightful reinterpretation of the existing rules and demonstrates that the computation of every trading indicator can equiva…

Moving averageComputationTechnical analysisFinancial marketEconomicsPairs tradeTrading strategyAnatomyMarket timingWeightingSSRN Electronic Journal
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Turbulence and financial markets

1996

MultidisciplinaryMarket depthIndirect financeFinancial marketFinancial intermediaryMarket dataEconomicsFinancial systemCapital marketFinancial market efficiencyFinancial market participantsNature
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Role of noise in a market model with stochastic volatility

2006

We study a generalization of the Heston model, which consists of two coupled stochastic differential equations, one for the stock price and the other one for the volatility. We consider a cubic nonlinearity in the first equation and a correlation between the two Wiener processes, which model the two white noise sources. This model can be useful to describe the market dynamics characterized by different regimes corresponding to normal and extreme days. We analyze the effect of the noise on the statistical properties of the escape time with reference to the noise enhanced stability (NES) phenomenon, that is the noise induced enhancement of the lifetime of a metastable state. We observe NES ef…

Noise inducedProbability theory stochastic processes and statisticFOS: Physical sciencesEconomicFOS: Economics and businessStochastic differential equationStatistical physicsMarket modelCondensed Matter - Statistical MechanicsEconomics; econophysics financial markets business and management; Probability theory stochastic processes and statistics; Fluctuation phenomena random processes noise and Brownian motion; Complex SystemsMathematicsFluctuation phenomena random processes noise and Brownian motionStatistical Finance (q-fin.ST)Stochastic volatilityStatistical Mechanics (cond-mat.stat-mech)Cubic nonlinearityQuantitative Finance - Statistical FinanceComplex SystemsWhite noiseDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksCondensed Matter PhysicsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Electronic Optical and Magnetic MaterialsHeston modelVolatility (finance)econophysics financial markets business and management
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How do normalization schemes affect net spillovers? A replication of the Diebold and Yilmaz (2012) study

2019

Abstract This paper replicates the Diebold and Yilmaz (2012) study on the connectedness of the commodity market and three other financial markets: the stock market, the bond market, and the FX market, based on the Generalized Forecast Error Variance Decomposition, GEFVD. We show that the net spillover indices (of directional connectedness), used to assess the net contribution of one market to overall risk in the system, are sensitive to the normalization scheme applied to the GEFVD. We show that, considering data generating processes characterized by different degrees of persistence and covariance, a scalar-based normalization of the Generalized Forecast Error Variance Decomposition is pref…

Normalization (statistics)Economics and EconometricsSocial connectedness020209 energySettore SECS-P/05 - Econometria02 engineering and technologyNormalization schemeconnectednessSpillover effect0502 economics and business0202 electrical engineering electronic engineering information engineeringEconometrics050207 economicsMathematicsspillover normalization connectednessVector autoregression models05 social sciencesFinancial marketCovarianceCausalitySpilloverGeneral EnergynormalizationGeneralized forecast error variance decompositionCommodity price fluctuations Driving forces Nonparametric additive regression modelsVariance decomposition of forecast errorsBond marketStock marketSimulationNormalization schemes
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Testing for non-linearity in an artificial financial market: a recurrence quantification approach

2004

Abstract In this paper, earlier work on testing for non-linear dynamics on realizations from an artificial financial market is extended in two ways. On the one hand, Hinich’s bispectral test and White’s neural network test are computed. On the other hand, a recently developed methodology to test for hidden structures in data, inherited from Physics, is successfully applied on the realizations of the artificial market. Results among alternative tests are compared.

Organizational Behavior and Human Resource ManagementEconomics and EconometricsActuarial scienceArtificial neural networkbusiness.industryFinancial marketNon linearityMachine learningcomputer.software_genreArtificial marketTest (assessment)Nonlinear systemEconomicsArtificial intelligencebusinesscomputerJournal of Economic Behavior & Organization
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Unemployment and Vacancy Dynamics with Imperfect Financial Markets

2018

This paper proposes a simple general equilibrium model with labour market frictions and an imperfect financial market. The aim of the paper is to analyse the transitional dynamics of unemployment and vacancies when financial constraints are in place. We model the financial sector as a monopolistically competitive banking sector that intermediates financial capital between firms. This structure implies a per period financial resource constraint which has a closed form solution and describes the transition path of unemployment and vacancies to their steady state values. We show that the transition path crucially depends on the degree of wage flexibility. When wages do not depend on the unempl…

Organizational Behavior and Human Resource ManagementEconomics and EconometricsLabour economicsGeneral equilibrium theorymedia_common.quotation_subject05 social sciencesFinancial marketWageFinancial capitalIndirect finance0502 economics and businessUnemploymentEconomicsImperfect050207 economicsBeveridge curve050205 econometrics media_commonSSRN Electronic Journal
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There's more to volatility than volume

2006

It is widely believed that fluctuations in transaction volume, as reflected in the number of transactions and to a lesser extent their size, are the main cause of clustered volatility. Under this view bursts of rapid or slow price diffusion reflect bursts of frequent or less frequent trading, which cause both clustered volatility and heavy tails in price returns. We investigate this hypothesis using tick by tick data from the New York and London Stock Exchanges and show that only a small fraction of volatility fluctuations are explained in this manner. Clustered volatility is still very strong even if price changes are recorded on intervals in which the total transaction volume or number of…

Physics - Physics and SocietyEconomicsvolatilityFOS: Physical sciencessubordinated processesPhysics and Society (physics.soc-ph)FOS: Economics and businessStock exchangeddc:330EconometricsEconomicsVolatility Modelling; Transaction Frequency; Trading Volume; Market StructurevolumeStatistical Finance (q-fin.ST)Financial marketVolume (computing)WirtschaftQuantitative Finance - Statistical FinancePolitical EconomyVolkswirtschaftslehrefinancial marketVolatility (finance)Constant (mathematics)General Economics Econometrics and FinanceDatabase transactionFinance
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Limit order placement as an utility maximization problem and the origin of power law distribution of limit order prices

2006

I consider the problem of the optimal limit order price of a financial asset in the framework of the maximization of the utility function of the investor. The analytical solution of the problem gives insight on the origin of the recently empirically observed power law distribution of limit order prices. In the framework of the model, the most likely proximate cause of this power law is a power law heterogeneity of traders' investment time horizons .

Physics - Physics and SocietyQuantitative Finance - Trading and Market MicrostructureFinancial assetFOS: Physical sciencesFunction (mathematics)MaximizationPhysics and Society (physics.soc-ph)Condensed Matter PhysicsInvestment (macroeconomics)Power lawElectronic Optical and Magnetic MaterialsTrading and Market Microstructure (q-fin.TR)FOS: Economics and businesssymbols.namesakeProximate and ultimate causationUtility maximization problemsymbolsEconometricsEconomicsPareto distributioneconophysics financial markets business and management
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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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