Search results for "Return distribution"

showing 4 items of 4 documents

Variety of Stock Returns in Normal and Extreme Market Days: The August 1998 Crisis

2002

We investigate the recently introduced variety of a set of stock returns traded in a financial market. This investigation is done by considering daily and intraday time horizons in a 15-day time period centered at the August 31st, 1998 crash of the S&P500 index. All the stocks traded at the NYSE during that period are considered in the present analysis. We show that the statistical properties of the variety observed in analyses of daily returns also hold for intraday returns. In particular the largest changes of the variety of the return distribution turns out to be most localized at the opening or (to a less degree) at the closing of the market.

Return distributionActuarial scienceFinancial marketEconometricsEconomicsPrice returnTime horizonStock returnStock (geology)
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Tick Size and Price Diffusion

2011

A tick size is the smallest increment of a security price. Tick size is typically regulated by the exchange where the security is traded and it may be modified either because the exchange enforces an overall tick size change or because the price of the security is too low or too high. There is an extensive literature, partially reviewed in Sect. 2 of the present paper, on the role of tick size in the price formation process. However, the role and the importance of tick size has not been yet fully understood, as testified, for example, by a recent document of the Committee of European Securities Regulators (CESR) [1].

Return distributionFinancial economicsSecurity priceTick sizeEconomicsPrice formation
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Multiscale Model Selection for High-Frequency Financial Data of a Large Tick Stock by Means of the Jensen–Shannon Metric

2014

Modeling financial time series at different time scales is still an open challenge. The choice of a suitable indicator quantifying the distance between the model and the data is therefore of fundamental importance for selecting models. In this paper, we propose a multiscale model selection method based on the Jensen–Shannon distance in order to select the model that is able to better reproduce the distribution of price changes at different time scales. Specifically, we consider the problem of modeling the ultra high frequency dynamics of an asset with a large tick-to-price ratio. We study the price process at different time scales and compute the Jensen–Shannon distance between the original…

Return distributionFinancemodel selectionComputer sciencebusiness.industryEntropy High frequency data Financial markets Market microstructureModel selectionGeneral Physics and AstronomyRanginglcsh:Astrophysicsmultiscale analysimultiscale analysisJensen–Shannon divergencelcsh:QC1-999Markov-switching modelinglcsh:QB460-466EconometricsJensen–Shannon divergencelcsh:Qbusinesslcsh:ScienceStock (geology)high frequency financial datalcsh:PhysicsEntropy
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Ensemble properties of securities traded in the NASDAQ market

2001

We study the price dynamics of stocks traded in the NASDAQ market by considering the statistical properties of an ensemble of stocks traded simultaneously. For each trading day of our database, we study the ensemble return distribution by extracting its first two central moments. According to previous results obtained for the NYSE market, we find that the second moment is a long-range correlated variable. We compare time-averaged and ensemble-averaged price returns and we show that the two averaging procedures lead to different statistical results.

FOS: Economics and businessStatistics and ProbabilityReturn distributionVariable (computer science)Statistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)EconometricsQuantitative Finance - Statistical FinanceFOS: Physical sciencesSecond moment of areaCondensed Matter PhysicsCondensed Matter - Statistical MechanicsMathematicsPhysica A: Statistical Mechanics and its Applications
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