Results 251 to 260 of about 233,260 (285)
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Financial modeling with heavy‐tailed stable distributions
WIREs Computational Statistics, 2013The aim of this article was to give an accessible introduction to stable distributions for financial modeling. There is a real need to use better models for financial returns because the normal (or bell curve/Gaussian) model does not capture the large fluctuations seen in real assets.
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Analyzing Real Data by a New Heavy-Tailed Statistical Model
Modern Journal of StatisticsThis study presents the power Mira distribution, an innovative three-parameter probability model that improves baseline distributions by including an extra shaping parameter. The suggested distribution has exceptional adaptability in representing various
Ahmed M. Gemeay +4 more
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When Do Heavy-Tail Distributions Help?
2006We examine the evidence for the widespread belief that heavy tail distributions enhance the search for minima on multimodal objective functions. We analyze isotropic and anisotropic heavy-tail Cauchy distributions and investigate the probability to sample a better solution, depending on the step length and the dimensionality of the search space.
Nikolaus Hansen +3 more
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Heavy-Tailed Distributions and Their Properties
2013We define the heavy-tailed distribution as distribution with infinite mathematical expectation. For such distributions the standard statistical tools—sample mean and sample standard deviation—exhibit a high instability. Some examples illustrating this conclusion are presented.
V. F. Pisarenko, M. V. Rodkin
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arXiv.org
Diffusion models achieve state-of-the-art generation quality across many applications, but their ability to capture rare or extreme events in heavy-tailed distributions remains unclear.
Kushagra Pandey +6 more
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Diffusion models achieve state-of-the-art generation quality across many applications, but their ability to capture rare or extreme events in heavy-tailed distributions remains unclear.
Kushagra Pandey +6 more
semanticscholar +1 more source
Heavy-Tailed and Long-Tailed Distributions
2011In this chapter we are interested in (right-) tail properties of distributions, i.e. in properties of a distribution which, for any x, depend only on the restriction of the distribution to (x, ∞). More generally it is helpful to consider tail properties of functions.
Sergey Foss +2 more
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Transformation of distributions into heavy tailed
SPIE Proceedings, 2016We consider the transformation of the Raleigh distribution into a new distribution so that the new distribution behaves approximately the same as the Rayleigh for small values of the argument but becomes heavy tailed for large values.
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Communications in Statistics Part B: Simulation and Computation, 2022
Zubair Ahmad, Eisa Muhmoudi, Sanku Dey
exaly
Zubair Ahmad, Eisa Muhmoudi, Sanku Dey
exaly
Portfolio selection with heavy tailed distributions
2005This paper analyzes portfolio selection models with heavy tailed return distributions. Firstly, we examine investor’s optimal choices when we assume respectively either Gaussian or stable non-Gaussian unconditional distributed index returns. Then, we approximate discrete time optimal allocations assuming returns following an ARMA process.
ORTOBELLI LOZZA, Sergio +4 more
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