A FUZZY NEURAL NETWORK MODEL FOR ANALYZING BALTIC DRY INDEX IN THE BULK MARITIME INDUSTRY

Baltic Dry Index (BDI) is one of the important indexes in the dry bulk shipping market. BDI analysis and forecasting is one of important activities of shipowners, charterers, shipping carriers, importers and exporters, and banks in the dry bulk shipping market. Based on the accurate BDI analysis and forecasting , the shipowners, charterers, shipping carriers, importers and exporters, and banks in the bulk shipping market could make many important decisions of shipping operation, management and financial invest such as building a new bulk carrier, chartering-in or chartering-out a second-hand bulk carrier, demolishing an old bulk carrier, and providing funding for shipowners. Thus, this paper adopts a fuzzy neural network model to analyze the relationship between the BDI in the international bulk shipping market and the major economic indexes in the global financial market. Finally, the proposed fuzzy neural network model is tested by empirical data during the period of 2000-2015. The results show that the fuzzy neural network model has high accuracy of forecasting. The fuzzy neural network model in this study seems to be promising and the model could help the shipowners, charterers, shipping carriers, importers and exporters, and banks forecast future BDI points in the bulk shipping market, and then make important decisions and operation strategies of shipping operation, management and financial invest.

Panamax markets behaviour: explaining volatility and expectations

It is widely accepted that the highly volatile Panamax market has many peculiarities; for example, Panamax vessels transport the major and the minor dry bulk cargoes worldwide. In contrast, the variety of cargoes and the flexibility in various trade routes, which the Panamax vessels follow, create a broad market with a relatively open structure. The importance of the Panamax market has also been highlighted by a recently upgraded contribution of the Baltic Panamax Index (BPI) to the Baltic Dry Index (BDI), affecting the progress of the BDI significantly. This paper investigates the behaviour of the Panamax market focusing on expectations and time lags. Expectations play a critical role in the freight market both for short-term and long-term decision making. In particular, we investigate the relationship between time lags and time-charter, trip and spot market rates, and the average earnings of the Panamax vessels of various ages. Time series analysis is used to reach our conclusions. The Hannan–Quinn criterion has been selected to identify the Panamax freight market’s significant lags for 1989–2020. An autoregressive model (AR) has been constructed to perform the statistical analysis. The findings indicate a strong correlation between time lags and the Panamax freight market, forecasting the behaviour of the market indeed. A better understanding of the Panamax market’s behaviour can improve shipowners and charterers’ planning decisions practically.

Examining the Impact of Movements of the Commodity Price on the Value of the Baltic Dry Index during Covid19 Pandemic

The Baltic Dry Index (BDI) is one of the most well-known indices, as it is perceived as a leading indicator of economic activity. Reductions in the movement of people, commodities, and capital in the conditions of economic crises, such as the one in 2008 and 2009, as well as the current economic crisis generated by the COVID-19 pandemic, were affected by the reduction of economic activities. It is interesting to point out that the analysis of the basic trend of the BDI movements in the period before the economic crisis shows that the index fell to near record lows just before the derivatives and credit crisis hit stocks full force. This is a clear signal that the index can be used as a tool for stock market forecasting. The paper aims to examine whether the changes in these raw materials affect the changes in the value of BDI. For these purposes in the paper was use GMM and 2SLS estimator. The results show that different raw materials have a different impact on the value of the BDI, which indicates that based on individual movements value of raw materials which composes the BDI cannot forecast its movement.

Multilevel Demand For Sea Transportation. Correlation Between Baltic Dry Index (Bdi) And Coaster Shipping Prices For Sea Routes Between Baltic Seaports And Mediterranean Seaports

Baltic Dry Index (BDI) reflects the prices of sea transport performed by Capesize, Panamax, Supramax and Handysize bulk carriers only. The prices of the transport with vessels of smaller tonnage are not considered in the calculation of BDI, therefore principally it should be assumed that BDI does not refer to a tonnage different from the observed. On the other hand, the demand for maritime transport services depends on the state of international trade of goods. Generally, the international market of goods is common for all ship types and tonnages. In the production processes starting from the extraction of raw materials till the sale of finished products to end customers; it can be done by several transport carriages in succession, which provide the intermediate production stages. Transport demand is secondary and depends on international trade, but on the other hand, this demand is multilevel. From an economic point of view, it is important to study the interrelationships between maritime transport providing the intermediate production stages, from the extraction of raw materials till the sale of the final goods.

CO2 emission allowances and their interacion with economic and energy factors in the European Union

Analysis of emission allowances prices has important environmental and political connotations. This article aimed to identifying the possible variables that may influence their behaviour and studied their relationship with fundamental factors: energy (Brent petroleum, Gas, Coal) and economy (Industrial Production Index, Baltic Dry Index, Purchasing Managers Index). With the objective of analyzing possible mutual interactions, Multivariate VAR or Error Correction Models (VECM), were applied. The information analysed derived from different sources (World Bank, Sendeco2 and various financial websites). The results obtained showed, not only the influence of past prices on the emission allowances actual price, but also the interaction with energetic and economic variables. Highlights Estimation of time series interrelations through VAR models. There is relationship of the emission allowances price with their past values. The energy variables are factors important to also explain the behavior of the emission allowances price. The economic variables are hardly significant except for the Dry Baltic Index.