Variation Of Skewness Research Articles

Modeling high power light-emitting diode spectra and their variation with junction temperature

Spectral radiant flux is the primary optical characteristic of a light source, determining the luminous flux and color. Much research is dedicated to the modeling of light-emitting diode (LED) spectra and their temperature dependence, allowing for the simulation of optical properties in various applications. Most of the spectral radiant flux models that have been published so far are purely mathematical. For this paper, spectral radiant fluxes of commercial single color LED packages have been measured in a custom made integrating sphere at several junction temperatures by active cooling and heating with a Peltier element. A spectrum model at 300 K is constructed where the Boltzmann free carrier distribution and carrier temperature are included. Subsequently, the model is extended with the carrier temperature variation, the band gap energy shift, and the nonradiative recombination rate decrease with junction temperature. As a result, the skewness variation, peak frequency shift, and peak value change in the spectrum with temperature can be predicted. The model has been validated by comparing flux and color coordinates of measured and simulated spectra at 340 K junction temperature. In practice, only two spectral flux measurements at different junction temperatures are needed to accurately simulate a single color spectrum at any temperature.

Probability Density Functions of Liquid Water Path and Cloud Amount of Marine Boundary Layer Clouds: Geographical and Seasonal Variations and Controlling Meteorological Factors

Abstract The subgrid-scale variability of the liquid water path (LWP) of marine boundary layer clouds in areas that correspond to the typical grid size of large-scale (global climate and weather prediction) atmospheric models (200 km × 200 km) is investigated using geostationary satellite visible data. Geographical and seasonal variations of homogeneity, skewness, and kurtosis of probability density functions (PDFs) of LWP are discussed, in addition to cloud amount. It is clear that not only cloud amount but also these subgrid-scale statistics have well-defined geographical patterns and seasonal variations. Furthermore, the meteorological factors that control subgrid-scale statistics of LWP that are related to boundary layer clouds are investigated using reanalysis data and PDFs of LWP data from satellites. Meteorological factors related to stability between 850 and 1000 hPa show high correlations with cloud amount and with the homogeneity, skewness, and kurtosis of PDFs of LWP of marine boundary layer clouds. The corrected gap of low-level moist static energy (CGLMSE) index, which is related to cloud-top entrainment instability, shows the highest correlation with the shape of LWP PDFs.

Nonintrusive characterization of fluidized bed hydrodynamics using vibration signature analysis

AbstractThere are many techniques to characterize the hydrodynamics of fluidized beds, but new techniques are still needed for more reliable measurement. Bed vibrations were measured by an accelerometer in a gas–solid fluidized bed to characterize the hydrodynamics of the fluidized bed in a nonintrusive manner. Measurements were carried out at different superficial gas velocities and particle sizes. Pressure fluctuations were measured simultaneously. Vibration signals were processed using statistical analysis. For the sake of the evaluation, the vibration technique was used to calculate minimum fluidization velocity. It was shown that minimum fluidization velocity can be determined from the variation of standard deviation, skewness, and kurtosis of vibration signals against superficial gas velocity of the bed. Kurtosis was proved to be a new method of analyzing vibration signals. Results indicate that analyzing the vibration signals can be an effective nonintrusive technique to characterize the hydrodynamics of fluidized beds. © 2009 American Institute of Chemical Engineers AIChE J, 2010

Modelling skewness and elongation in financial returns: the case of exchange-traded funds

Recent studies have documented the importance of asymmetry and tail-fatness of returns on portfolio-choice, asset-pricing, value-at-risk and option-valuation models. This article explores the nature of skewness and elongation in daily Exchange-traded Fund (ETF) return distributions using g, h and (g × h) distributions. These exploratory data analytic techniques of Tukey (1977) reveal patterns that are hidden from a cursory glance at conventional measures for skewness and elongation. The g, h and (g × h) distributions provide parameter estimates that indicate substantial variation in skewness and elongation for individual ETFs; nonetheless, some trends are discovered when the funds are grouped by fund size and style of investing. Monte Carlo simulations suggest that these exploratory techniques are able to capture patterns found in commonly used Generalized Autoregressive Conditional Heteroskedasticity (GARCH) family of models.

Determination of hydrodynamic behavior of gas–solid fluidized beds using statistical analysis of acoustic emissions

In the processes involving the movement of solid particles, acoustic emissions are caused by particle friction, collision and fluid turbulence. Particle behavior can therefore be monitored and characterized by assessing the acoustic emission signals. Herein, extensive measurements were carried out by microphone at different superficial gas velocities with different particle sizes. Acoustic emission signals were processed using statistical analysis from which the minimum fluidization velocity was determined from the variation of standard deviation, skewness and kurtosis of acoustic emission signals against superficial gas velocity. Initial minimum fluidization velocity, corresponding to onset of fluidization of finer particles in the solids mixture, at which isolated bubbles occur, was also detected by this method. It was shown that the acoustic emission measurement is highly feasible as a practical method for monitoring the hydrodynamics of gas–solid fluidized beds.

A look at the links between drainage density and flood statistics

Abstract. We investigate the links between the drainage density of a river basin and selected flood statistics, namely, mean, standard deviation, coefficient of variation and coefficient of skewness of annual maximum series of peak flows. The investigation is carried out through a three-stage analysis. First, a numerical simulation is performed by using a spatially distributed hydrological model in order to highlight how flood statistics change with varying drainage density. Second, a conceptual hydrological model is used in order to analytically derive the dependence of flood statistics on drainage density. Third, real world data from 44 watersheds located in northern Italy were analysed. The three-level analysis seems to suggest that a critical value of the drainage density exists for which a minimum is attained in both the coefficient of variation and the absolute value of the skewness coefficient. Such minima in the flood statistics correspond to a minimum of the flood quantile for a given exceedance probability (i.e., recurrence interval). Therefore, the results of this study may provide useful indications for flood risk assessment in ungauged basins.

Skewness variations of switching-current distributions in moderately damped Josephson junctions due to thermally induced multiple escape and retrapping

A crossover at a temperature T* in the temperature dependence of the width σ of the distribution of switching currents of moderately damped Josephson junctions has been reported in a number of recent publications. For T < T*, dσ/dT is positive and the IV characteristics are associated with underdamped behaviour; for T > T*, dσ/dT is negative and the IV characteristics resemble overdamped behaviour. We have investigated in detail the behaviour of Josephson junctions around T* by using Monte Carlo simulations including retrapping from the running state into the supercurrent state as given by a model due to Ben-Jacob et al. Thermally induced multiple escape and retrapping events play an important role for moderate damping. Around T*, not just at lower T < T*, the shape of the distribution and σ(T) are largely determined by the shape of the conventional underdamped thermally activated switching distribution. The behaviour is more fully understood by considering two crossover temperatures. The skewness of the switching distribution parametrises its shape and becomes less negative, then positive, as T increases above the lower crossover temperature.

Data Truncation Bias, Loss Firms, and Accounting Anomalies

After performing a Least Trimmed Square procedure at 1%, Kraft, Leone, and Wasley (2006) find an inverted-U relation between Accruals or net operating assets (NOA) and subsequent one-year abnormal returns. They argue that this opposes behavioral explanations for the Accrual and NOA anomalies. We show that the inverted-U relation is a spurious consequence of the truncation bias noted in Kothari, Sabino, and Zach (2005). LTS trimming for these anomalies effectively trims observations by the value of the dependent variable (returns). We show that because returns skewness varies systematically with the accounting predictor, the LTS trimming induces a truncation bias that varies systematically across the accounting predictors. The variation in returns skewness is related to the variation in the incidence of loss firms across the accounting predictors. Among profit firms, which have less skewed returns and so are less subject to the truncation bias, the negative monotonic relation between accounting predictors and subsequent abnormal returns is robust to trimming. Thus, ex post non-random trimming of returns can spuriously induce evidence against either the efficient market hypothesis or behavioral theories. Additionally, this paper shows that the anomalies survive trimming, despite the truncation bias, when a larger set of asset pricing controls and test methods that control for cross-sectional dependence are used.

A simple model for calculating tsunami flow speed from tsunami deposits

This paper presents a simple model for tsunami sedimentation that can be applied to calculate tsunami flow speed from the thickness and grain size of a tsunami deposit (the inverse problem). For sandy tsunami deposits where grain size and thickness vary gradually in the direction of transport, tsunami sediment transport is modeled as a steady, spatially uniform process. The amount of sediment in suspension is assumed to be in equilibrium with the steady portion of the long period, slowing varying uprush portion of the tsunami. Spatial flow deceleration is assumed to be small and not to contribute significantly to the tsunami deposit. Tsunami deposits are formed from sediment settling from the water column when flow speeds on land go to zero everywhere at the time of maximum tsunami inundation. There is little erosion of the deposit by return flow because it is a slow flow and is concentrated in topographic lows. Variations in grain size of the deposit are found to have more effect on calculated tsunami flow speed than deposit thickness. The model is tested using field data collected at Arop, Papua New Guinea soon after the 1998 tsunami. Speed estimates of 14 m/s at 200 m inland from the shoreline compare favorably with those from a 1-D inundation model and from application of Bernoulli's principle to water levels on buildings left standing after the tsunami. As evidence that the model is applicable to some sandy tsunami deposits, the model reproduces the observed normal grading and vertical variation in sorting and skewness of a deposit formed by the 1998 tsunami.

Climate change, migratory connctivity and changes in laying date and clutch size of the pied flycatcher

We examined long‐term (1943–2003) variability in laying dates and clutch sizes in a Finnish population of the pied flycatcher Ficedula hypoleuca Pallas, and analysed whether potential changes were explained by changes in climatic factors at the wintering area in Africa, at migration route or at breeding grounds. Among‐year variation in both mean and skewness of laying dates increased, which for mean laying date appeared to be explained by variability of temperatures at the breeding grounds and for skewness by variable temperature trends along the migration route. Pied flycatchers bred earlier in warm springs, but despite a warming trend in pre‐laying temperatures, the laying dates tended to delay. Laying dates became continuously later in relation to the phenology of the environment. Mean clutch size decreased with time when mean laying date was controlled for, but the climatic factors did not appear to explain the decrease. The advancement of spring phenology may have shifted some food sources needed for egg‐laying, thus leading to later laying and smaller clutches. Variation in clutch size increased when wintering conditions were favourable so that clutch size distribution was skewed with a tail of small clutches when there had been lot of rainfall (more vegetation and insects) in the wintering area. We suggest that when ecological conditions during winter were good, the tail of small clutches represented low‐quality individuals that were not able to breed after bad winters. Our analyses demonstrate that measures of spread and symmetry give different information about population level changes than means, and thus complement the understanding of the potential influences of climate change on populations.

Normal mixture GARCH(1,1): applications to exchange rate modelling

AbstractSome recent specifications for GARCH error processes explicitly assume a conditional variance that is generated by a mixture of normal components, albeit with some parameter restrictions. This paper analyses the general normal mixture GARCH(1,1) model which can capture time variation in both conditional skewness and kurtosis. A main focus of the paper is to provide evidence that, for modelling exchange rates, generalized two‐component normal mixture GARCH(1,1) models perform better than those with three or more components, and better than symmetric and skewed Student'st‐GARCH models. In addition to the extensive empirical results based on simulation and on historical data on three US dollar foreign exchange rates (British pound, euro and Japanese yen), we derive: expressions for the conditional and unconditional moments of all models; parameter conditions to ensure that the second and fourth conditional and unconditional moments are positive and finite; and analytic derivatives for the maximum likelihood estimation of the model parameters and standard errors of the estimates. Copyright © 2006 John Wiley &amp; Sons, Ltd.

Statistical Analysis of Clock Skew Variation in H-Tree Structure

This paper discusses clock skew due to manufacturing variability and environmental change. In clock tree design, transition time constraint is an important design parameter that controls clock skew and power dissipation. In this paper, we evaluate clock skew under several variability models, and demonstrate relationship among clock skew, transition time constraint and power dissipation. Experimental results show that constraint of small transition time reduces clock skew under manufacturing and supply voltage variabilities, whereas there is an optimum constraint value for temperature gradient. Our experiments in a 0.18 μm technology indicate that clock skew is minimized when clock buffer is sized such that the ratio of output and input capacitance is four.

Sunspot cycle-dependent changes in the distribution of GSE latitudinal angles of IMF observed near 1 AU

[1] The solar cycle variations in the characteristics of the GSE latitudinal angles of the Interplanetary Magnetic Field (θGSE) observed near 1 AU have been studied for the period 1967–2000. It is observed that the statistical parameters mean, standard deviation, skewness and kurtosis vary with sunspot cycle. The θGSE distribution resembles the Gaussian curve during sunspot maximum and is clearly non-Gaussian during sunspot minimum. The width of the θGSE distribution is found to increase with sunspot activity, which is likely to depend on the occurrence of solar transients. Solar cycle variations in skewness are ordered by the solar polar magnetic field changes. This can be explained in terms of the dependence of the dominant polarity of the north-south component of IMF in the GSE system near 1 AU on the IMF sector polarity and the structure of the heliospheric current sheet.

Mean/Variance Relation and the Conditional Distribution

This paper examines the relation between the expected return and the conditional variance using three conditional error distributions 1) the conditional normal error distribution, 2) the Generalized Error Distribution, and 3) the skewed student's t-distribution. Using a GARCH-M model modified by allowing skewness in mean, we find support for a significant and positive mean/variance relation when the skewed student's t-distribution is used. Our results show that the time variations in conditional skewness influence the dynamics of the conditional mean and conditional variance, as reflected by the reduced volatility persistence and a significant mean/variance relationship. This further stresses the point that there is an intimate relation between return, volatility and skewness; within the GARCH-M framework, conditional skewness plays a role analogous to heteroskedasticity by smoothing out the conditional mean and conditional variance process.

Stock Return Characteristics, Skew Laws, and the Differential Pricing of Individual Equity Options

This article provides several new insights into the economic sources of skewness. First, we document the differential pricing of individual equity options versus the market index and relate it to variations in return skewness. Second, we show how risk aversion introduces skewness in the risk-neutral density. Third, we derive laws that decompose individual return skewness into a systematic component and an idiosyncratic component. Empirical analysis of OEX options and 30 stocks demonstrates that individual risk-neutral distributions differ from that of the market index by being far less negatively skewed. This article explains the presence and evolution of risk-neutral skewness over time and in the cross section of individual stocks.

Stock Return Characteristics, Skew Laws, and the Differential Pricing of Individual Equity Options

and relate it to variations in return skewness. Second, we show how risk aversion introduces skewness in the risk-neutral density. Third, we derive laws that decompose individual return skewness into a systematic component and an idiosyncratic component. Empirical analysis of OEX options and 30 stocks demonstrates that individual riskneutral distributions differ from that of the market index by being far less negatively skewed. This article explains the presence and evolution of risk-neutral skewness over time and in the cross section of individual stocks.

Risk-Neutral Skewness: Evidence from Stock Options

We investigate the relative importance of various factors in explaining the volatility skew observed in the prices of stock options traded on the Chicago Board Options Exchange. The skewness of the risk-neutral density implied by individual stock option prices tends to be more negative for stocks that have larger betas, suggesting that market risk is important in pricing individual stock options. Also, implied skewness tends to be more negative in periods of high market volatility, and when the risk-neutral density for index options is more negatively skewed. Other firm-specific factors, including firm size and trading volume a so help explain cross-sectional variation in skewness. However, we find no robust relationship between skewness and the firm's leverage. Nor do we find evidence that skewness is related to the put/call ratio, which may be viewed as a proxy for trading pressure or market sentiment. Overall, firm-specific factors seem to be more important than systematic factors in explaining the variation in the skew for individual firms.

Dependence of Supergranular Length-Scales on Network Magnetic Fields

In an earlier paper by Raju, Srikanth, and Singh (1998), the average size of chromospheric network cells has been shown to have a dependence on the solar latitude. This was presumed to be due to the reduction of supergranular length-scales by network magnetic field enhancements. It has been found that the network brightness enhancements over solar latitude support this finding. Significant negative correlations have been found between the average cell size and the network brightness enhancements. Since the brightness enhancements are essentially due to the magnetic field concentrations, it is suggested that the network magnetic fields reduce the network cell sizes. We have also obtained the variations of skewness of network brightness distributions over solar latitude, which follow the network field variations. This complements the findings of Caccin et al. (1998) that skewness of brightness distribution follows the solar cycle. The findings suggest that the dependence of supergranular sizes, network brightness, and skewness of network brightness distribution on solar latitude or on the phase of the solar cycle is due to the associated variation of network magnetic fields.

Stock Return Characteristics, Skew Laws, and the Differential Pricing of Individual Equity Options

This article provides several new insights into the economic sources of skewness. First, we document the differential pricing of individual equity options versus the market index, and relate it to variations in return skewness. Second, we show how risk aversion introduces skewness in the risk-neutral density. Third, we derive laws that decompose individual return skewness into a systematic component and an idiosyncratic component. Empirical analysis of OEX options and 30 stocks demonstrates that individual risk-neutral distributions differ from that of the market index by being far less negatively skewed. This paper explains the presence and evolution of risk-neutral skewness over time and in the cross-section of individual stocks.

On The Influence Of The Eulerian Velocity PDF Closure On The Eddy Diffusion Coefficient

The flux-gradient model, often used to describe turbulent dispersion, implicitly defines an eddy diffusion coefficient K that is known to be related to the Eulerian probability density function (pdf) of the turbulent velocity field. In the strict limit of applicability of Fick's law, the relationship between K and the pdf is used to investigate the influence of non-Gaussianity on dispersion in homogeneous turbulence. A bi-Gaussian pdf is used as a closure model that allows for separate studies of skewness and kurtosis variations. The choice of model parameters can have a significant influence on K, especially when the pdf is bimodal. Both arbitrariness of the closure and bimodality are then reduced using the maximum entropy criterion for the selection of the free parameter of the closure scheme, together with the assumption that the model is valid only for those values of the parameters for which a unimodal pdf is possible. The variations of K are found to be sensitive to both skewness and kurtosis showing a more complex behaviour than that found in literature.