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169
Modeling and Forecasting Realized Volatility
, 2002
"... this paper is built. First, although raw returns are clearly leptokurtic, returns standardized by realized volatilities are approximately Gaussian. Second, although the distributions of realized volatilities are clearly rightskewed, the distributions of the logarithms of realized volatilities are a ..."
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Cited by 549 (50 self)
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frequency models, we find that our simple Gaussian VAR forecasts generally produce superior forecasts. Furthermore, we show that, given the theoretically motivated and empirically plausible assumption of normally distributed returns conditional on the realized volatilities, the resulting lognormalnormal mixture
Lognormal distribution based EMOS models for probabilistic wind speed forecasting
"... Ensembles of forecasts are obtained from multiple runs of numerical weather forecasting models with different initial conditions and typically employed to account for forecast uncertainties. However, biases and dispersion errors often occur in forecast ensembles, they are usually underdispersive a ..."
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dispersive and uncalibrated and require statistical postprocessing. We present an Ensemble Model Output Statistics (EMOS) method for calibration of wind speed forecasts based on the lognormal (LN) distribution, and we also show a regimeswitching extension of the model which combines the previously studied truncated normal
Parameter estimation of the hybrid censored lognormal distribution
 Journal of Statistical Computation and Simulation
, 2011
"... The two most common censoring schemes used in life testing experiments are TypeI and TypeII censoring schemes. Hybrid censoring scheme is mixture of TypeI and TypeII censoring scheme. In this work we consider the estimation of parameters of lognormal distribution based on hybrid censored data. ..."
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Cited by 1 (0 self)
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The two most common censoring schemes used in life testing experiments are TypeI and TypeII censoring schemes. Hybrid censoring scheme is mixture of TypeI and TypeII censoring scheme. In this work we consider the estimation of parameters of lognormal distribution based on hybrid censored data
LogNormal Merging for Distributed System Identification
"... Abstract Growing interest in applications of distributed systems, such as multiagent systems, increases demands on identification of distributed systems from partial information sources collected by local agents. We are concerned with fully distributed scenario where system is identified by multipl ..."
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by multiple agents, which do not estimate state of the whole system but only its local ‘state’. The resulting estimate is obtained by merging of marginal and conditional posterior probability density functions (pdf) on such local states. We investigate the use of recently proposed nonparametric lognormal
Approximating the Distribution of a Sum of a Lognormal Random Variables
 Statistics and Computing
, 2012
"... Abstract This paper introduces a process for estimating the distribution of a sum of independent and identically distributed lognormal random variables (RVs). The procedure involves using the FentonWilkinson method to estimate the parameters for a single lognormal distribution that approximates ..."
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Cited by 1 (0 self)
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the sum of lognormal RVs. Once these parameters are determined, a mixture of truncated exponentials (MTE) function is determined to approximate this distribution. The MTE parameters are stated as polynomial functions of the lognormal scale parameter. Applications to inventory management are presented
Mixtures of tdistributions for Finance and Forecasting
, 2007
"... We explore convenient analytic properties of distributions constructed as mixtures of scaled and shifted tdistributions. A particularly desirable feature for econometric applications are closedform expressions for antiderivatives (e.g., the cumulative density function). We illustrate the usefulnes ..."
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the usefulness of these distributions in two applications. In the first application, we produce density forecasts of U.S. inflation and show that these forecasts are more accurate, outofsample, than density forecasts obtained using normal or standard tdistributions. In the second application, we replicate
Mixtures of tdistributions for Finance and Forecasting
, 2007
"... institution for postgraduate education and research in economics and the social sciences in Austria. ..."
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institution for postgraduate education and research in economics and the social sciences in Austria.
MODELING AND FORECASTING REALIZED VOLATILITY *
, 1999
"... This paper provides a general framework for integration of highfrequency intraday data into the measurement, modeling, and forecasting of daily and lower frequency volatility and return distributions. Most procedures for modeling and forecasting financial asset return volatilities, correlations, an ..."
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autoregressive volatility forecast, coupled with a parametric lognormalnormal mixture distribution implied by the theoretically and empirically grounded assumption of normally distributed standardized returns, gives rise to wellcalibrated density forecasts of future returns, and correspondingly accurate
Lognormal intensity distribution of the quietSun FUV continuum observed by SUMER
, 2007
"... We analyse observations of the quietSun far ultraviolet (FUV) continuum at various wavelengths near 1430 Å obtained by the SUMER instrument on SOHO. According to semiempirical atmospheric models this continuum originates from the layers in the chromosphere where the temperature rises from low valu ..."
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values at nearradiative equilibrium to a plateau of about 6000 K. We study raster images and intensity distribution histograms and find that a single lognormal distribution matches these observations very well, and that the spatial structure observed corresponds to a mixture of features
Evaluating Density Forecasts: Forecast Combinations, Model Mixtures, Calibration and Sharpness
, 2008
"... In a recent article Gneiting, Balabdaoui and Raftery (JRSSB, 2007) propose the criterion of sharpness for the evaluation of predictive distributions or density forecasts. They motivate their proposal by an example in which standard evaluation procedures based on probability integral transforms cann ..."
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Cited by 22 (5 self)
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In a recent article Gneiting, Balabdaoui and Raftery (JRSSB, 2007) propose the criterion of sharpness for the evaluation of predictive distributions or density forecasts. They motivate their proposal by an example in which standard evaluation procedures based on probability integral transforms
Results 1  10
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169