Title :
Long memory on dry bulk volatility in shipping market
Author :
Gong, Xiaoxing ; Jing Lv
Author_Institution :
Transp. Manage. Coll., Dalian Maritime Univ., Dalian, China
Abstract :
The purpose of this paper is to investigate the long memory on dry bulk volatility in shipping market. This paper applies the long memory stochastic volatility (LMSV) model studying the volatility and long memory in shipping industry. The parameters of LMSV model are estimated via the software package WINBUGS (Bayesian inference using Gibbs Sampling). According to analyze the Baltic Capesize Index and Baltic Panamax Index, it is found that there is strong long memory on dry bulk volatility in shipping market.
Keywords :
Monte Carlo methods; belief networks; inference mechanisms; logistics data processing; marketing; Baltic capesize index; Baltic panamax index; Bayesian inference; Gibbs sampling; WTNBUGS; dry bulk volatility; long memory stochastic volatility model; shipping market; software package; Econometrics; Investments; Marine transportation; Marine vehicles; Mathematical model; Memory management; Portfolios; Road transportation; Shipbuilding industry; Stochastic processes; Dry Bulk; Long Memory; Volatility;
Conference_Titel :
Service Operations, Logistics and Informatics, 2009. SOLI '09. IEEE/INFORMS International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4244-3540-1
Electronic_ISBN :
978-1-4244-3541-8
DOI :
10.1109/SOLI.2009.5204016
