Long memory on dry bulk volatility in shipping market

Author

Gong, Xiaoxing ; Jing Lv

Author_Institution

Transp. Manage. Coll., Dalian Maritime Univ., Dalian, China

fYear

2009

fDate

22-24 July 2009

Firstpage

663

Lastpage

668

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/SOLI.2009.5204016

Filename

5204016