Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Shaopeng, Hong"'
Autor:
Shaopeng, Hong, Xiangdong, Liu
In this paper, we consider Fredlin-Wentzell type large deviation principle (LDP) of multidimensional reflected stochastic partial differential equations in a convex domain, allowing for oblique direction of reflection. To prove the LDP, a sufficient
Externí odkaz:
http://arxiv.org/abs/2303.17851
Autor:
Xiangdong, Liu, Shaopeng, Hong
In this paper, we study the asymptotic behavior of randomly perturbed path-dependent stochastic differential equations with small parameter $\vartheta_{\varepsilon}$, when $\varepsilon \rightarrow 0$, $\vartheta_\varepsilon$ goes to $0$. When $\varep
Externí odkaz:
http://arxiv.org/abs/2303.17840
Autor:
Shaopeng, Hong
Due to the skessed distribution, high peak and thick tail and asymmetry of financial return data, it is difficult to describe the traditional distribution. In recent years, generalized autoregressive score (GAS) has been used in many fields and achie
Externí odkaz:
http://arxiv.org/abs/2008.01277
Autor:
Xiangdong, Liu, Shaopeng, Hong
In this paper, we investigate a class of mean reflected McKean-Vlasov stochastic differential equation, which extends the equation proposed by \cite{briand2020particles} by allowing the solution's distribution to not only constrain its behavior, but
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::836198368cfc791d092fee2a0e302663
Publikováno v:
Transactions of the Chinese Society of Agricultural Engineering. Jan2024, Vol. 40 Issue 1, p217-226. 10p.
