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Chunhua Ma
Researcher at Nankai University
Publications - 29
Citations - 438
Chunhua Ma is an academic researcher from Nankai University. The author has contributed to research in topics: Branching process & Cox–Ingersoll–Ross model. The author has an hindex of 11, co-authored 29 publications receiving 343 citations. Previous affiliations of Chunhua Ma include Pierre-and-Marie-Curie University.
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Asymptotic properties of estimators in a stable Cox–Ingersoll–Ross model
Zenghu Li,Chunhua Ma +1 more
TL;DR: In this article, the authors study the estimation of a stable Cox-Ingersoll-Ross model, which is a special subcritical continuous-state branching process with immigration, and prove the exponential ergodicity and strong mixing property of the process by a coupling method.
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A branching process approach to power markets
TL;DR: A market model for power prices is investigated, including most basic features exhibited by previous models and taking into account self-exciting properties, and a Random Field approach is proposed, extending Hawkes-type models by introducing a twofold integral representation property.
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On the hitting times of continuous-state branching processes with immigration
TL;DR: In this paper, a two-dimensional joint distribution related to the first passage time below a level for a continuous-state branching process with immigration was studied and a necessary and sufficient criterion for transience or recurrence was obtained.
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Alpha-CIR Model with Branching Processes in Sovereign Interest Rate Modelling
TL;DR: The α-CIR model as mentioned in this paper is an extension of the standard CIR model by adopting the α-stable Levy process and preserving the branching property, which allows to describe in a unified and parsimonious way several recent observations on the sovereign bond market together with the presence of large jumps at local extent.
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Least squares estimators for stochastic differential equations driven by small Lévy noises
TL;DR: In this article, the authors study parameter estimation for discretely observed stochastic differential equations driven by small Levy noises and obtain consistency and rate of convergence of the least squares estimator (LSE) of parameter when e → 0 and n → ∞ simultaneously.