Freight forward agreement timeseries modeling based on artificial neural network models - Lyridis, Dimitrios (Strojniški vestnik, 2013)
During the last thirty years, there has been an extraordinary growth in the market of financial derivatives, in the field of shipping. This can be attributed to the fact that financial derivatives are contracts which allow all players participating in the shipping market to reduce their exposure to the fluctuations in freight rates, bunker prices, interest rates, foreign exchange rates and vessel values. This paper employs Artificial Neural Network (ANN), in order to forecast the future price of freight derivatives. More specifically, drawing on historical data for the period between January 2005 and March 2009, an ANN is built and trained, and its estimates lead to two individual results. The resulting model indicates to the investor which position to take in the derivatives market (short for sale of agreements and long for the purchase of agreements).
Keywords: artificial neural networks; freight rate forecasting; freight rates; modeliranje trga ladijskega prevoza; napovedovanje stroškov prevoza; shipping market modeling; strategija trgovanja; stroški prevoza; trading strategy; umetne nevronske mreže