TY - JOUR
T1 - DIFFUSION LIMITS FOR A MARKOV MODULATED BINOMIAL COUNTING PROCESS
AU - Spreij, Peter
AU - Storm, P.J.
PY - 2019/1/30
Y1 - 2019/1/30
N2 - In this paper, we study limit behavior for a Markov-modulated binomial counting process, also called a binomial counting process under regime switching. Such a process naturally appears in the context of credit risk when multiple obligors are present. Markov-modulation takes place when the failure/default rate of each individual obligor depends on an underlying Markov chain. The limit behavior under consideration occurs when the number of obligors increases unboundedly, and/or by accelerating the modulating Markov process, called rapid switching. We establish diffusion approximations, obtained by application of (semi)martingale central limit theorems. Depending on the specific circumstances, different approximations are found.
AB - In this paper, we study limit behavior for a Markov-modulated binomial counting process, also called a binomial counting process under regime switching. Such a process naturally appears in the context of credit risk when multiple obligors are present. Markov-modulation takes place when the failure/default rate of each individual obligor depends on an underlying Markov chain. The limit behavior under consideration occurs when the number of obligors increases unboundedly, and/or by accelerating the modulating Markov process, called rapid switching. We establish diffusion approximations, obtained by application of (semi)martingale central limit theorems. Depending on the specific circumstances, different approximations are found.
KW - Markov-modulated process
KW - central limit theorems
KW - counting process
KW - functional limit theorems
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U2 - https://doi.org/10.1017/S0269964818000578
DO - https://doi.org/10.1017/S0269964818000578
M3 - Article
SN - 0269-9648
JO - Probability in the Engineering and Informational Sciences
JF - Probability in the Engineering and Informational Sciences
ER -