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.
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