{"title":"马尔可夫环境中的波动建模:两种与奥恩斯坦-乌伦贝克相关的方法","authors":"Anita Behme","doi":"arxiv-2407.05866","DOIUrl":null,"url":null,"abstract":"We introduce generalizations of the COGARCH model of Kl\\\"uppelberg et al.\nfrom 2004 and the volatility and price model of Barndorff-Nielsen and Shephard\nfrom 2001 to a Markov-switching environment. These generalizations allow for\nexogeneous jumps of the volatility at times of a regime switch. Both models are\nstudied within the framework of Markov-modulated generalized Ornstein-Uhlenbeck\nprocesses which allows to derive conditions for stationarity, formulas for\nmoments, as well as the autocovariance structure of volatility and price\nprocess. It turns out that both models inherit various properties of the\noriginal models and therefore are able to capture basic stylized facts of\nfinancial time-series such as uncorrelated log-returns, correlated squared\nlog-returns and non-existence of higher moments in the COGARCH case.","PeriodicalId":501355,"journal":{"name":"arXiv - QuantFin - Pricing of Securities","volume":"62 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Volatility modeling in a Markovian environment: Two Ornstein-Uhlenbeck-related approaches\",\"authors\":\"Anita Behme\",\"doi\":\"arxiv-2407.05866\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce generalizations of the COGARCH model of Kl\\\\\\\"uppelberg et al.\\nfrom 2004 and the volatility and price model of Barndorff-Nielsen and Shephard\\nfrom 2001 to a Markov-switching environment. These generalizations allow for\\nexogeneous jumps of the volatility at times of a regime switch. Both models are\\nstudied within the framework of Markov-modulated generalized Ornstein-Uhlenbeck\\nprocesses which allows to derive conditions for stationarity, formulas for\\nmoments, as well as the autocovariance structure of volatility and price\\nprocess. It turns out that both models inherit various properties of the\\noriginal models and therefore are able to capture basic stylized facts of\\nfinancial time-series such as uncorrelated log-returns, correlated squared\\nlog-returns and non-existence of higher moments in the COGARCH case.\",\"PeriodicalId\":501355,\"journal\":{\"name\":\"arXiv - QuantFin - Pricing of Securities\",\"volume\":\"62 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuantFin - Pricing of Securities\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2407.05866\",\"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 - Pricing of Securities","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.05866","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Volatility modeling in a Markovian environment: Two Ornstein-Uhlenbeck-related approaches
We introduce generalizations of the COGARCH model of Kl\"uppelberg et al.
from 2004 and the volatility and price model of Barndorff-Nielsen and Shephard
from 2001 to a Markov-switching environment. These generalizations allow for
exogeneous jumps of the volatility at times of a regime switch. Both models are
studied within the framework of Markov-modulated generalized Ornstein-Uhlenbeck
processes which allows to derive conditions for stationarity, formulas for
moments, as well as the autocovariance structure of volatility and price
process. It turns out that both models inherit various properties of the
original models and therefore are able to capture basic stylized facts of
financial time-series such as uncorrelated log-returns, correlated squared
log-returns and non-existence of higher moments in the COGARCH case.