Optimal prediction of the last r-excursion time of Brownian motion models
B. Li,
M.A. Lkabous and
J.M. Pedraza
Stochastic Processes and their Applications, 2026, vol. 194, issue C
Abstract:
This paper investigates the optimal prediction of the last r-excursion time for a Brownian motion model. The last r-excursion time, denoted by lr, refers to the right endpoint of the last negative excursion lasting longer than a constant r > 0. It reduces to the standard last passage time when r↓0. For a Brownian motion with drift μ > 0 and volatility σ > 0, our goal is to identify an optimal stopping time that minimizes the (L1) distance from the last r-excursion time lr. We find that the optimal stopping barrier exhibits two distinct structures: a constant barrier (characterized as a solution of a non-linear equation) or a moving barrier (characterized by the unique solution to an integral equation) depending on the ratio R=μrσ which integrates a firm’s financial profitability, volatility, and risk tolerance to financial distress. To obtain the optimal stopping time, we examine the smooth fit condition, Lipschitz continuity of the barrier, and probability regularity of the boundary points. As an application in risk management, we develop a decision rule that informs the timing of business expansion and contraction.
Keywords: Optimal prediction; Long-term financial distress; Brownian motion models; Parisian ruin (search for similar items in EconPapers)
Date: 2026
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304414925002960
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:spapps:v:194:y:2026:i:c:s0304414925002960
Ordering information: This journal article can be ordered from
http://http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
DOI: 10.1016/j.spa.2025.104852
Access Statistics for this article
Stochastic Processes and their Applications is currently edited by T. Mikosch
More articles in Stochastic Processes and their Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().