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VRSTA GRADIVAanalitična raven (sestavni del), tekstovno gradivo, tiskano, 1.01 - izvirni znanstveni članek
DRŽAVA IZIDASlovenija
LETO IZIDA2013
JEZIK BESEDILA/IZVIRNIKAangleški
PISAVAlatinica
DELO IMAilustracije
ODGOVORNOSTLyridis, Dimitrios - avtor // Zacharioudakis, Panayotis - avtor // Iordanis, Stylianos - avtor // Daleziou, Sophia - avtor
NASLOVFreight forward agreement timeseries modeling based on artificial neural network models
V PUBLIKACIJIStrojniški vestnik. - ISSN 0039-2480. - ǂVol. ǂ59, ǂno. ǂ9 (Sep. 2013), str. 511-516, SI 100.
KRATKA VSEBINADuring 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 individualresults. 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).
OPOMBEBibliografija: str. 516 // Povzetek v angl. inslov.
OSTALI NASLOVIModeliranje časovnih vrst terminskih pogodb naprevozne stroške z uporabo umetnih nevronskih mrež
PREDMETNE OZNAKE// stroški prevoza // strategija trgovanja //umetne nevronske mreže // modeliranje trga ladijskega prevoza // napovedovanje stroškov prevoza // freight rates // trading strategy // artificial neural networks // shipping market modeling // freight rate forecasting
UDK004.032.26:339:629:656.03
DOI10.5545/sv-jme.2013.947

izvedba, lastnina in pravice: NUK 2010