Scaled Penalization of Brownian Motion with Drift and the Brownian Ascent

被引:1
|
作者
Panzo, Hugo [1 ]
机构
[1] Univ Connecticut, Dept Math, Storrs, CT 06269 USA
来源
SEMINAIRE DE PROBABILITES L | 2019年 / 2252卷
关键词
WEAK-CONVERGENCE; BESSEL PROCESS; RANDOM-WALK; LOCAL TIME; PENALISATION; MEANDER; MAXIMUM;
D O I
10.1007/978-3-030-28535-7_12
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
We study a scaled version of a two-parameter Brownian penalization model introduced by Roynette-Vallois-Yor (Period Math Hungar 50:247-280, 2005). The original model penalizes Brownian motion with drift h is an element of R by the weight process (exp(nu S-t) : t >= 0) where nu is an element of R and (S-t : t >= 0) is the running maximum of the Brownian motion. It was shown there that the resulting penalized process exhibits three distinct phases corresponding to different regions of the (nu, h)-plane. In this paper, we investigate the effect of penalizing the Brownian motion concurrently with scaling and identify the limit process. This extends an existing result for the nu < 0, h = 0 case to the whole parameter plane and reveals two additional "critical" phases occurring at the boundaries between the parameter regions. One of these novel phases is Brownian motion conditioned to end at its maximum, a process we call the Brownian ascent. We then relate the Brownian ascent to some well-known Brownian path fragments and to a random scaling transformation of Brownian motion that has attracted recent interest.
引用
收藏
页码:257 / 300
页数:44
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