TY - JOUR
T1 - Dynamic optimality in optimal variance stopping problems
AU - Buonaguidi, Bruno
PY - 2018
Y1 - 2018
N2 - In an optimal variance stopping (O.V.S.) problem one seeks to determine the stopping time that maximizes the variance of an observed process. As originally shown by Pedersen (2011), the variance criterion leads to optimal stopping boundaries that depend explicitly on the initial point of the process. Then, following the lines of Pedersen and Peskir (2016), we introduce the concept of dynamic optimality for an O.V.S. problem, a type of optimality that disregards the starting point of the process. We examine when an O.V.S. problem admits a dynamically optimal stopping time and we illustrate our findings through several examples.
AB - In an optimal variance stopping (O.V.S.) problem one seeks to determine the stopping time that maximizes the variance of an observed process. As originally shown by Pedersen (2011), the variance criterion leads to optimal stopping boundaries that depend explicitly on the initial point of the process. Then, following the lines of Pedersen and Peskir (2016), we introduce the concept of dynamic optimality for an O.V.S. problem, a type of optimality that disregards the starting point of the process. We examine when an O.V.S. problem admits a dynamically optimal stopping time and we illustrate our findings through several examples.
KW - Dynamic and static optimality
KW - Markov processes
KW - Optimal variance stopping problems
KW - Statistics and Probability
KW - Statistics, Probability and Uncertainty
KW - Dynamic and static optimality
KW - Markov processes
KW - Optimal variance stopping problems
KW - Statistics and Probability
KW - Statistics, Probability and Uncertainty
UR - http://hdl.handle.net/10807/133215
UR - http://www.elsevier.com/locate/issn/01677152
U2 - 10.1016/j.spl.2018.05.030
DO - 10.1016/j.spl.2018.05.030
M3 - Article
SN - 0167-7152
VL - 141
SP - 103
EP - 108
JO - STATISTICS & PROBABILITY LETTERS
JF - STATISTICS & PROBABILITY LETTERS
ER -