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Predicion of the Baltic Capesize Index
Author: JiangLi
Tutor: YangZhongZhen
School: Dalian Maritime University
Course: Transportation Planning and Management
Keywords: Wavelet transform ARMA model forecasting Baltic Capesize Index (BCI)
CLC: F551
Type: Master's thesis
Year: 2010
Downloads: 208
Quote: 1
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Abstract
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International dry bulk shipping market is an important component of international shipping market. Its cargo volume accounts for a large proportion of the whole cargo volume in the world. The baltic dry bulk index reflects the international dry bulk shipping market. From an external point of view, it is affected by many factors. And it is a complex nonlinear system. However, in fact, it is determined by demand and supply, like other markets. There is a time difference between demand and supply, so baltic dry bulk index is always in constant fluctuation. Recently, because of the economy crisis, there is a sharp decline in the world trade, BDI is influenced heavily. In a short time, BDI went down by 11130 point. It bring a great loss to shipping companies and investors. Therefore, it is very necessary to grasp the trend of dry bulk index. It can help the managers and investors to make a decision, in order to reduce the risk.During the three components of BDI, only the caculation of BCI include two shipping route relevent to China. At the same time, because the capesize ships are mainly used to import iron ore, the fluctuation of BCI has a direct effect to the transport cost of some iron and steel enterprises. Therefore, BCI are selected to be researched. Firstly, wavelet analysize is used to denoise the BCI sequence, in order to eliminate the effect caused by the irregular incidents. Secondly, db3 wavelet fuction is used to decompose the sequence. And a low frequency time series and three high frequency time series are obtained. Thirdly, ARMA model is used to predict the four denoised time series. Then, the four parts are sumed to get the results. At last, according to the case study, we find that wavelet analysize-ARMA model has a higher prediction accuracy. It can be used to predict the trend of BCI.
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CLC: > Economic > Transportation and economic > Sea transport and economic > World waterway transport economics
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