{"title":"用自由度概括阿尔法稳定分布","authors":"Stephen H. Lihn","doi":"arxiv-2405.04693","DOIUrl":null,"url":null,"abstract":"A Wright function based framework is proposed to combine and extend several\ndistribution families. The $\\alpha$-stable distribution is generalized by\nadding the degree of freedom parameter. The PDF of this two-sided super\ndistribution family subsumes those of the original $\\alpha$-stable, Student's t\ndistributions, as well as the exponential power distribution and the modified\nBessel function of the second kind. Its CDF leads to a fractional extension of\nthe Gauss hypergeometric function. The degree of freedom makes possible for\nvalid variance, skewness, and kurtosis, just like Student's t. The original\n$\\alpha$-stable distribution is viewed as having one degree of freedom, that\nexplains why it lacks most of the moments. A skew-Gaussian kernel is derived\nfrom the characteristic function of the $\\alpha$-stable law, which maximally\npreserves the law in the new framework. To facilitate such framework, the\nstable count distribution is generalized as the fractional extension of the\ngeneralized gamma distribution. It provides rich subordination capabilities,\none of which is the fractional $\\chi$ distribution that supplies the needed\n'degree of freedom' parameter. Hence, the \"new\" $\\alpha$-stable distribution is\na \"ratio distribution\" of the skew-Gaussian kernel and the fractional $\\chi$\ndistribution. Mathematically, it is a new form of higher transcendental\nfunction under the Wright function family. Last, the new univariate symmetric\ndistribution is extended to the multivariate elliptical distribution\nsuccessfully.","PeriodicalId":501139,"journal":{"name":"arXiv - QuantFin - Statistical Finance","volume":"12 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Generalization of the Alpha-Stable Distribution with the Degree of Freedom\",\"authors\":\"Stephen H. Lihn\",\"doi\":\"arxiv-2405.04693\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A Wright function based framework is proposed to combine and extend several\\ndistribution families. The $\\\\alpha$-stable distribution is generalized by\\nadding the degree of freedom parameter. The PDF of this two-sided super\\ndistribution family subsumes those of the original $\\\\alpha$-stable, Student's t\\ndistributions, as well as the exponential power distribution and the modified\\nBessel function of the second kind. Its CDF leads to a fractional extension of\\nthe Gauss hypergeometric function. The degree of freedom makes possible for\\nvalid variance, skewness, and kurtosis, just like Student's t. The original\\n$\\\\alpha$-stable distribution is viewed as having one degree of freedom, that\\nexplains why it lacks most of the moments. A skew-Gaussian kernel is derived\\nfrom the characteristic function of the $\\\\alpha$-stable law, which maximally\\npreserves the law in the new framework. To facilitate such framework, the\\nstable count distribution is generalized as the fractional extension of the\\ngeneralized gamma distribution. It provides rich subordination capabilities,\\none of which is the fractional $\\\\chi$ distribution that supplies the needed\\n'degree of freedom' parameter. Hence, the \\\"new\\\" $\\\\alpha$-stable distribution is\\na \\\"ratio distribution\\\" of the skew-Gaussian kernel and the fractional $\\\\chi$\\ndistribution. Mathematically, it is a new form of higher transcendental\\nfunction under the Wright function family. Last, the new univariate symmetric\\ndistribution is extended to the multivariate elliptical distribution\\nsuccessfully.\",\"PeriodicalId\":501139,\"journal\":{\"name\":\"arXiv - QuantFin - Statistical Finance\",\"volume\":\"12 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuantFin - Statistical Finance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2405.04693\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Statistical Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2405.04693","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
本文提出了一个基于赖特函数的框架来组合和扩展几个分布族。通过添加自由度参数,对 $\alpha$ 稳定分布进行了泛化。这个双面超分布族的 PDF 包含了原始的 $\alpha$-稳定分布、Student's t 分布、指数幂分布和修正的第二类贝塞尔函数的 PDF。它的 CDF 导致高斯超几何函数的分数扩展。自由度使得方差、偏斜度和峰度成为可能,就像 Student's t 分布一样。从 $\alpha$ 稳定规律的特征函数中导出了一个偏高斯核,它在新框架中最大限度地保留了该规律。为了促进这种框架,稳定计数分布被概括为广义伽马分布的分数扩展。它提供了丰富的从属能力,其中之一就是分数 $\chi$ 分布,它提供了所需的 "自由度 "参数。因此,"新的"$α$稳定分布是偏高斯核与分数$\chi$分布的 "比率分布"。在数学上,它是赖特函数族下的一种新的高超越函数形式。最后,新的单变量对称分布成功地扩展到了多变量椭圆分布。
Generalization of the Alpha-Stable Distribution with the Degree of Freedom
A Wright function based framework is proposed to combine and extend several
distribution families. The $\alpha$-stable distribution is generalized by
adding the degree of freedom parameter. The PDF of this two-sided super
distribution family subsumes those of the original $\alpha$-stable, Student's t
distributions, as well as the exponential power distribution and the modified
Bessel function of the second kind. Its CDF leads to a fractional extension of
the Gauss hypergeometric function. The degree of freedom makes possible for
valid variance, skewness, and kurtosis, just like Student's t. The original
$\alpha$-stable distribution is viewed as having one degree of freedom, that
explains why it lacks most of the moments. A skew-Gaussian kernel is derived
from the characteristic function of the $\alpha$-stable law, which maximally
preserves the law in the new framework. To facilitate such framework, the
stable count distribution is generalized as the fractional extension of the
generalized gamma distribution. It provides rich subordination capabilities,
one of which is the fractional $\chi$ distribution that supplies the needed
'degree of freedom' parameter. Hence, the "new" $\alpha$-stable distribution is
a "ratio distribution" of the skew-Gaussian kernel and the fractional $\chi$
distribution. Mathematically, it is a new form of higher transcendental
function under the Wright function family. Last, the new univariate symmetric
distribution is extended to the multivariate elliptical distribution
successfully.