Open AccessThe Euler-Maruyama approximations for the CEV model
Author(s) -
Vyacheslav M. Abramov,
Fima C. Klebaner,
R. Lipster
Publication year - 2011
Publication title -
discrete and continuous dynamical systems - b
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.864
H-Index - 53
eISSN - 1553-524X
pISSN - 1531-3492
DOI - 10.3934/dcdsb.2011.16.1
Subject(s) - mathematics , lipschitz continuity , zero (linguistics) , weak convergence , stochastic differential equation , metric (unit) , mathematical analysis , distribution (mathematics) , combinatorics , computer science , philosophy , linguistics , operations management , computer security , economics , asset (computer security)
The CEV model is given by the stochastic differential equation $X_t=X_0+\int_0^t\mu X_sds+\int_0^t\sigma (X^+_s)^pdW_s$, $\frac{1}{2}\le p
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