2019
DOI: 10.1088/1742-5468/ab2709
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Approximation of the first passage time distribution for the birth–death processes

Abstract: We propose a general method to obtain approximation of the first passage time distribution for the birth-death processes. We rely on the general properties of birth-death processes, Keilson's theorem and the concept of Riemann sum to obtain closed-form expressions. We apply the method to the three selected birth-death processes and the sophisticated order-book model exhibiting long-range memory. We discuss how our approach contributes to the competition between spurious and true long-range memory models.

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Cited by 6 publications
(7 citation statements)
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“…We will call this problem the chemical birth-death process to distinguish it from the many other birthdeath processes that have been considered in the literature, e.g [19,20,21]…”
mentioning
confidence: 99%
“…We will call this problem the chemical birth-death process to distinguish it from the many other birthdeath processes that have been considered in the literature, e.g [19,20,21]…”
mentioning
confidence: 99%
“…Our expectation that burst and inter-burst duration analysis can give an additional value in the estimation of long-range memory property is based on the previous study of the first passage time problem in birth-death processes and the duration PDF in-variance regarding non-linear transformations of the time series [22,24,34,41,43]. This empirical analysis of LOB data strengthens our expectation providing evidence that the definition of Hurst exponent using burst and inter-burst duration analysis can be more reliable in comparison with other widely used methods.…”
Section: Discussionmentioning
confidence: 99%
“…We proposed a test earlier, based on the specific first-passage times, which we refer to as the burst and interburst duration analysis (abbr. BDA) [ 148 , 149 , 150 , 151 ].…”
Section: Searching For the True Long-range Memory Testmentioning
confidence: 99%
“…One has to take into account the interplay of endogenous and exogenous fluctuations in the financial markets to build a comprehensive model of this complex system [ 154 ]. Non-linear SDEs might be applicable in the modeling of other social systems, where models of opinion or population dynamics lead to the macroscopic description by these equations [ 148 , 149 , 150 , 151 ]. The description by SDEs is an alternative to the modeling incorporating fractional dynamics, if power–law statistical properties are observed in the empirical data.…”
Section: Searching For the True Long-range Memory Testmentioning
confidence: 99%
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