Search results for "geometric Brownian motion"

showing 5 items of 15 documents

Efficient or Fractal Market Hypothesis? A Stock Indexes Modelling Using Geometric Brownian Motion and Geometric Fractional Brownian Motion

2021

In this article, we propose a test of the dynamics of stock market indexes typical of the US and EU capital markets in order to determine which of the two fundamental hypotheses, efficient market hypothesis (EMH) or fractal market hypothesis (FMH), best describes market behavior. The article’s major goal is to show how to appropriately model return distributions for financial market indexes, specifically which geometric Brownian motion (GBM) and geometric fractional Brownian motion (GFBM) dynamic equations best define the evolution of the S&P 500 and Stoxx Europe 600 stock indexes. Daily stock index data were acquired from the Thomson Reuters Eikon database during a ten-year period, fro…

Rescaled rangeHurst exponentefficient market hypothesisGeometric Brownian motionFractional Brownian motionGeneral MathematicsFinancial marketgeometric fractional Brownian motionStock market indexFractalgeometric Brownian motion; geometric fractional Brownian motion; efficient market hypothesis; fractal market hypothesisfractal market hypothesisOrder (exchange)QA1-939Computer Science (miscellaneous)Econometricsgeometric Brownian motionEngineering (miscellaneous)MathematicsMathematicsMathematics
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Fractional Brownian motion and Martingale-differences

2004

Abstract We generalize a result of Sottinen (Finance Stochastics 5 (2001) 343) by proving an approximation theorem for the fractional Brownian motion, with H> 1 2 , using martingale-differences.

Statistics and ProbabilityGeometric Brownian motionFractional Brownian motionMathematics::ProbabilityDiffusion processReflected Brownian motionMathematical analysisBrownian excursionStatistics Probability and UncertaintyHeavy traffic approximationMartingale (probability theory)Martingale representation theoremMathematicsStatistics & Probability Letters
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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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A new stochastic representation for the decay from a metastable state

2002

Abstract We show that a stochastic process on a complex plane can simulate decay from a metastable state. The simplest application of the method to a model in which the approach to equilibrium occurs through transitions over a potential barrier is discussed. The results are compared with direct numerical simulations of the stochastic differential equations describing system's evolution. We have found that the new method is much more efficient from computational point of view than the direct simulations.

Statistics and ProbabilityStochastic partial differential equationGeometric Brownian motionStochastic differential equationContinuous-time stochastic processQuantum stochastic calculusStochastic processLocal timeDiscrete-time stochastic processStatistical physicsCondensed Matter PhysicsMathematicsPhysica A: Statistical Mechanics and its Applications
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Geometric Brownian Motion (GBM) of Stock Indexes and Financial Market Uncertainty in the Context of Non-Crisis and Financial Crisis Scenarios

2022

The present article proposes a methodology for modeling the evolution of stock market indexes for 2020 using geometric Brownian motion (GBM), but in which drift and diffusion are determined considering two states of economic conjunctures (states of the economy), i.e., non-crisis and financial crisis. Based on this approach, we have found that the GBM proved to be a suitable model for making forecasts of stock market index values, as it describes quite well their future evolution. However, the model proposed by us, modified geometric Brownian motion (mGBM), brings some contributions that better describe the future evolution of stock indexes. Evidence in this regard was provided by analyzing …

geometric Brownian motion; Monte Carlo simulation; entropy; financial crisis; financial marketsGeneral Mathematicsfinancial crisisComputer Science (miscellaneous)QA1-939geometric Brownian motionfinancial marketsentropyEngineering (miscellaneous)Monte Carlo simulationMathematicsMathematics
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