An optimal double stopping rule for a buying-selling problem

Georgy Yu Sofronov

doi:10.1007/s11009-018-9684-6

An optimal double stopping rule for a buying-selling problem

Georgy Yu Sofronov^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

Abstract

We consider a buying-selling problem with a finite time horizon when two stops of a sequence of dependent observations can be made. The aim is to find an optimal sequential procedure which maximizes the total expected revenue. In this paper, we obtain an optimal double stopping rule and apply it for a geometric random walk and an autoregressive sequence.

Original language	English
Pages (from-to)	1-12
Number of pages	12
Journal	Methodology and Computing in Applied Probability
Volume	22
Issue number	1
Early online date	3 Nov 2018
DOIs	https://doi.org/10.1007/s11009-018-9684-6
Publication status	Published - Mar 2020

Keywords

Sequential decision analysis
Optimal stopping rules
Buying-selling problem
Geometric random walk
Autoregressive sequence

Access to Document

10.1007/s11009-018-9684-6

Cite this

@article{a882fb48a2fd4b8d90f0bed715bd2116,

title = "An optimal double stopping rule for a buying-selling problem",

abstract = "We consider a buying-selling problem with a finite time horizon when two stops of a sequence of dependent observations can be made. The aim is to find an optimal sequential procedure which maximizes the total expected revenue. In this paper, we obtain an optimal double stopping rule and apply it for a geometric random walk and an autoregressive sequence.",

keywords = "Sequential decision analysis, Optimal stopping rules, Buying-selling problem, Geometric random walk, Autoregressive sequence",

author = "Sofronov, {Georgy Yu}",

year = "2020",

month = mar,

doi = "10.1007/s11009-018-9684-6",

language = "English",

volume = "22",

pages = "1--12",

journal = "Methodology and Computing in Applied Probability",

issn = "1387-5841",

publisher = "Springer, Springer Nature",

number = "1",

}

TY - JOUR

T1 - An optimal double stopping rule for a buying-selling problem

AU - Sofronov, Georgy Yu

PY - 2020/3

Y1 - 2020/3

N2 - We consider a buying-selling problem with a finite time horizon when two stops of a sequence of dependent observations can be made. The aim is to find an optimal sequential procedure which maximizes the total expected revenue. In this paper, we obtain an optimal double stopping rule and apply it for a geometric random walk and an autoregressive sequence.

AB - We consider a buying-selling problem with a finite time horizon when two stops of a sequence of dependent observations can be made. The aim is to find an optimal sequential procedure which maximizes the total expected revenue. In this paper, we obtain an optimal double stopping rule and apply it for a geometric random walk and an autoregressive sequence.

KW - Sequential decision analysis

KW - Optimal stopping rules

KW - Buying-selling problem

KW - Geometric random walk

KW - Autoregressive sequence

UR - http://www.scopus.com/inward/record.url?scp=85056115953&partnerID=8YFLogxK

U2 - 10.1007/s11009-018-9684-6

DO - 10.1007/s11009-018-9684-6

M3 - Article

AN - SCOPUS:85056115953

SN - 1387-5841

VL - 22

SP - 1

EP - 12

JO - Methodology and Computing in Applied Probability

JF - Methodology and Computing in Applied Probability

IS - 1

ER -

An optimal double stopping rule for a buying-selling problem

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this