Details
| Original language | English |
|---|---|
| Title of host publication | Engineering Applications of Neural Networks - 13th International Conference, EANN 2012, Proceedings |
| Editors | Shigang Yue, Lazaros Iliadis |
| Pages | 443-452 |
| Number of pages | 10 |
| Publication status | Published - 2012 |
| Event | 2012 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2012 - Chengdu, China Duration: 26 Oct 2012 → 28 Oct 2012 |
Publication series
| Name | Communications in Computer and Information Science |
|---|---|
| Volume | 311 |
| ISSN (Print) | 1865-0929 |
Abstract
In this paper we investigate the forecasting and trading performance of linear and non-linear methods, in order to generate short-term forecasts in the dirty tanker shipping market. We attempt to uncover the benefits of using several time series models and the potential of neural networks. Maritime forecasting studies using neural networks are rare and only focus on spot rates. We build on this kind of investigation, but we extend our study on freight rates derivatives or Forward Freight Agreements (FFA) in a simple trading simulation. Our conclusion is, that non-linear methods like neural networks are suitable for short-term forecasting and trading freight rates, as their results match or improve on those of other models. Nevertheless, we think that further research with freight rates and corresponding derivatives is developable for decision and trading applications with enhanced forecasting models.
Keywords
- Forecasting Performance, Neural Network, Shipping Freight Market, Trading Performance
ASJC Scopus subject areas
- Computer Science(all)
- General Computer Science
- Mathematics(all)
- General Mathematics
Cite this
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Engineering Applications of Neural Networks - 13th International Conference, EANN 2012, Proceedings. ed. / Shigang Yue; Lazaros Iliadis. 2012. p. 443-452 (Communications in Computer and Information Science; Vol. 311).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Short-Term Trading Performance of Spot Freight Rates and Derivatives in the Tanker Shipping Market
T2 - 2012 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2012
AU - von Spreckelsen, Christian
AU - von Mettenheim, Hans Jörg
AU - Breitner, Michael H.
N1 - Copyright: Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2012
Y1 - 2012
N2 - In this paper we investigate the forecasting and trading performance of linear and non-linear methods, in order to generate short-term forecasts in the dirty tanker shipping market. We attempt to uncover the benefits of using several time series models and the potential of neural networks. Maritime forecasting studies using neural networks are rare and only focus on spot rates. We build on this kind of investigation, but we extend our study on freight rates derivatives or Forward Freight Agreements (FFA) in a simple trading simulation. Our conclusion is, that non-linear methods like neural networks are suitable for short-term forecasting and trading freight rates, as their results match or improve on those of other models. Nevertheless, we think that further research with freight rates and corresponding derivatives is developable for decision and trading applications with enhanced forecasting models.
AB - In this paper we investigate the forecasting and trading performance of linear and non-linear methods, in order to generate short-term forecasts in the dirty tanker shipping market. We attempt to uncover the benefits of using several time series models and the potential of neural networks. Maritime forecasting studies using neural networks are rare and only focus on spot rates. We build on this kind of investigation, but we extend our study on freight rates derivatives or Forward Freight Agreements (FFA) in a simple trading simulation. Our conclusion is, that non-linear methods like neural networks are suitable for short-term forecasting and trading freight rates, as their results match or improve on those of other models. Nevertheless, we think that further research with freight rates and corresponding derivatives is developable for decision and trading applications with enhanced forecasting models.
KW - Forecasting Performance
KW - Neural Network
KW - Shipping Freight Market
KW - Trading Performance
UR - http://www.scopus.com/inward/record.url?scp=84880645369&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-32909-8_45
DO - 10.1007/978-3-642-32909-8_45
M3 - Conference contribution
AN - SCOPUS:84880645369
SN - 9783642329081
T3 - Communications in Computer and Information Science
SP - 443
EP - 452
BT - Engineering Applications of Neural Networks - 13th International Conference, EANN 2012, Proceedings
A2 - Yue, Shigang
A2 - Iliadis, Lazaros
Y2 - 26 October 2012 through 28 October 2012
ER -