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This thesis deals with seaborne transport with emphasis on transport of containerized goods, contract terms and conditions of imports of goods to the European Union. It also describes the current situation of maritime transport on the route the EU - Vietnam. The practical part is focused on the import of goods into the Czech Republic using a freight forwarder services.

The diploma thesis describes seaborne transport of goods in general, and furthermore specifies the current dilemma of existing cartels - conferences - in this industry. I also describe containerization, general situation on container transport market with a hint of latest information about this market. Next chapter describes legislative rules of European Union that shape import of goods to Union. As it was not possible to describe all of them, I concentrate only on those rules involving import of containers. The goal of researching EU import legislation was to familiriaze myself with all activities and information, which an importer must take care of and possess, before he gets in touch with a shipping carrier about the transport itself. I managed to mention the most basic and important points, which importers of goods must apply.

Submitted by Patricia Calazans (patmellofranco@gmail.com) on 2011-01-14T12:05:28Z No. of bitstreams: 1 Tese-Patricia-Calazans.pdf: 594538 bytes, checksum: 1945b30641fdf200c49dca14b4422b31 (MD5) / Approved for entry into archive by Vitor Souza(vitor.souza@fgv.br) on 2011-01-14T14:16:14Z (GMT) No. of bitstreams: 1 Tese-Patricia-Calazans.pdf: 594538 bytes, checksum: 1945b30641fdf200c49dca14b4422b31 (MD5) / Made available in DSpace on 2011-02-21T14:28:06Z (GMT). No. of bitstreams: 1 Tese-Patricia-Calazans.pdf: 594538 bytes, checksum: 1945b30641fdf200c49dca14b4422b31 (MD5) Previous issue date: 2008-05-30 / This study presents a forecasting model for prices and volumes traded in the seaborne iron ore market. A VAR model (with endogenous variables with one lag) was developed, using oil prices (Brent) and an industrial production index. After testing for a unit root in the variables and discovering that none of them were stationary, the co-integration test showed that there was a long term relation between them, which was in itself stationary, eliminating the possibility of a spurious regression. As a result, the VAR model was seen to be consistent, with high adherence to forecast prices and volumes for seaborne trade, in spite of some short term imprecision. / O presente estudo apresenta um modelo de previsão do preço e do volume comercializado no mercado transoceânico de minério de ferro. Para tanto, foi desenvolvido um modelo VAR, utilizando, além das variáveis endógenas com um lag de diferença, o preço do petróleo Brent e um índice de produção industrial. Após testar raiz unitária das variáveis e constatar que nenhuma era estacionária, o teste de cointegração atestou que existia relação de longo prazo entre as mesmas que era estacionária, afastando a possibilidade de uma regressão espúria. Como resultado, a modelagem VAR apresentou um modelo consistente, com elevada aderência para a previsão do preço e do volume negociado de minério de ferro no mercado transoceânico, não obstante ele tenha apresentado alguma imprecisão no curto prazo.

In this master thesis multiple time series of shipping industry and financial data are analysed in order to create a forecasting model to forecast freight rate indices. The data of main interest which are predicted are the two freight rate indices, BDI and BDTI, from the Baltic Exchange. The project investigates the possibilities for aggregated Vector Autoregression(VAR) models to outperform simple univariate models, in this case, an Autoregressive Integrated Moving Average(ARIMA) with seasonal components. The other part of this thesis is to model market shocks in the freight rate indices, given impulses in the other underlying VAR-model time series using the impulse response function. The main results are that the VAR-model forecast outperforms the ARIMA-model in forecasting the tanker freight rate index (BDTI), while the the bulk freight rate index(BDI) is better predicted by the simple ARIMA when calculating the forecast mean square error. / I denna avhandling analyseras multipla tidsserier över rederinärings- och finansiell data i syfte att skapa en prognosticerande modell för att prognosticera fraktratsindex. Dataserierna som i huvudsak prognosticeras är fraktratsindexen BDI och BDTI från Baltic exchange. I projektet undersöks om en aggregerad Vektor Autoregressiv(VAR) modell överträffar en univariat modell, i detta fall en Autoregressive Integrated Moving Average(ARIMA) med säsongsvariabel. I andra delen av denna avhandling modelleras chocker i fraktratsindexen givet impulser i de andra underliggande tidsserierna i de aggregerade VAR-modellerna. Huvudresultaten är att VAR-modellens prognos överträffar ARIMA-modellen för tankerraterna (BDTI), medan bulkraterna(BDI) bättre prognosticeras av ARIMA-modellen, i avseende på prognosernas beräknade mean square error.