{"title":"On the cross-variation of a class of stochastic processes","authors":"Soufiane Moussaten","doi":"10.1016/j.rinam.2024.100509","DOIUrl":null,"url":null,"abstract":"<div><div>The present paper deals with the study of the cross-variation of two-dimensional stochastic process defined using the Young integral with respect to a continuous, <span><math><mi>α</mi></math></span>-self-similar Gaussian process that does not necessarily have stationary increments, with increment exponent some <span><math><mrow><mi>β</mi><mo>></mo><mn>0</mn></mrow></math></span>. We analyze the limit, in probability, of the so-called cross-variation when <span><math><mi>β</mi></math></span> in <span><math><mfenced><mrow><mn>0</mn><mo>,</mo><mn>2</mn><mi>α</mi></mrow></mfenced></math></span>, and we finish by providing some examples of known processes that satisfy the required assumptions.</div></div>","PeriodicalId":36918,"journal":{"name":"Results in Applied Mathematics","volume":"24 ","pages":"Article 100509"},"PeriodicalIF":1.4000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Results in Applied Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590037424000797","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
The present paper deals with the study of the cross-variation of two-dimensional stochastic process defined using the Young integral with respect to a continuous, -self-similar Gaussian process that does not necessarily have stationary increments, with increment exponent some . We analyze the limit, in probability, of the so-called cross-variation when in , and we finish by providing some examples of known processes that satisfy the required assumptions.