Newbuilding ship price forecasting by parsimonious intelligent model search engine
Asset prices play a significant role in the financial survival and profitability of ship-owning firms. In a highly volatile shipping market, prices of newbuilding ships must be predicted to detect security shortfalls as well as opportunities for temporal arbitration (gaining on high–low pricing). Ac...
Saved in:
Main Authors: | Gao, Ruobin, Liu, Jiahui, Zhou, Qin, Duru, Okan, Yuen, Kum Fai |
---|---|
Other Authors: | School of Civil and Environmental Engineering |
Format: | Article |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/162086 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Annual dilated convolution neural network for newbuilding ship prices forecasting
by: Gao, Ruobin, et al.
Published: (2022) -
Ship order book forecasting by an ensemble deep parsimonious random vector functional link network
by: Cheng, Ruke, et al.
Published: (2024) -
Shipping market forecasting by forecast combination mechanism
by: Gao, Ruobin, et al.
Published: (2022) -
Abatement of atmospheric pollutant emissions with autonomous shipping in maritime transportation using Bayesian probabilistic forecasting
by: Liu, Jiahui, et al.
Published: (2022) -
A human-centred review on maritime autonomous surfaces ships: impacts, responses, and future directions
by: Li, Xue, et al.
Published: (2024)