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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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8172533 · Oct 202519922001200920172026
48 results for ship finance

AI helps simplify complex ship finance processes.

problem Complexity in ship finance due to data and regulatory requirements.
method Integrates large language models for document comprehension, information extraction, and workflow automation.
result AI-assisted systems can support maritime finance professionals in managing complex information and reporting requirements.

In this work a novel ships dataset is proposed consisting of more than 56k images of marine vessels collected by means of web-scraping and including 12 ship categories. A YOLOv3 single-stage detector based on Keras API is built on top of this dataset. Current results on four categories (cargo ship, naval ship, oil ship…

2020-02-10abs ↗pdf ↗

Transformer learns shipping costs more accurately than traditional methods.

problem Inaccurate shipping cost estimates lead to poor financial decisions.
method Proposes Rate Card Transformer (RCT) using self-attention to encode shipping information.
result Cost predictions made by RCT have 28.82% less error compared to GBDT models.

Marine buoys aid in the battle against Illegal, Unreported and Unregulated (IUU) fishing by detecting fishing vessels in their vicinity. Marine buoys, however, may be disrupted by natural causes and buoy vandalism. In this paper, we formulate marine buoy placement as a clustering problem, and propose dropout k-means an…

2020-01-02abs ↗pdf ↗

A hybrid ML method improves ship response predictions across different sea conditions.

problem Improving accuracy and generalizability of ML methods for ship response predictions.
method A hybrid machine learning method that corrects forces in a low-fidelity equation of motion.
result The hybrid method offers improved prediction accuracy and generalizability compared to benchmarks.

Study reveals trade dynamics in dry bulk shipping networks, highlighting their randomness and periodic changes.

problem Understanding the randomness and periodic changes in dry bulk shipping networks.
method Analysis of micro-level trade flow data from 2015 to 2023, focusing on grain, coal, and iron ore networks.
result Dry bulk shipping networks exhibit small-world phenomena and periodic life cycles, influenced by importing ports and global events.

This research proposes a method to hedge freight rate risk in shipping markets under model uncertainty.

problem Managing freight risk in shipping markets under model uncertainty.
method The approach uses Wasserstein barycenter for modeling freight rates dynamics and optimal hedging strategy selection.
result The proposed method provides robust hedging strategies even in high noise cases.

Having the right assortment of shipping boxes in the fulfillment warehouse to pack and ship customer's online orders is an indispensable and integral part of nowadays eCommerce business, as it will not only help maintain a profitable business but also create great experiences for customers. However, it is an extremely …

2018-09-26abs ↗pdf ↗

Modeling vessel speed to balance efficiency and environmental risks in Arctic shipping.

problem Balancing vessel speed with environmental and ecological risks in Arctic shipping.
method Inverse control constrained optimization framework with risk parameters estimated from AIS data.
result Distinct decision-making patterns across vessel types and navigational statuses, with varying sensitivity to ice and whale risks.

Crypto markets show negative spillovers between chains, not positive co-movements.

problem Negative spillovers in crypto asset returns across different blockchains.
method On-chain data from multiple blockchains (Ethereum, Solana, Binance, Arbitrum, Avalanche) analyzed over 2022-2025.
result Surges on one chain often coincide with declines on others, especially during attention shocks.

We generalize the Zermelo navigation problem and its solution on Riemannian manifolds (M,h)(M, h) admitting a space dependence of a ship's own speed u(x)h1|u(x)|_h\leq1 in the presence of a perturbation WW determined by a mild velocity vector field W(x)h<u(x)h|W(x)|_h<|u(x)|_h, with application of Finsler metric of Randers type.

2016-04-21abs ↗pdf ↗

We study control systems invariant under a Lie group with application to the problem of nonlinear trajectory planning. A theory of symmetry reduction of exterior differential systems is employed to demonstrate how symmetry reduction and reconstruction is effective in the explicit, exact construction of planned system t…

2015-10-20abs ↗pdf ↗

We generalize the Zermelo navigation problem and its solution on Riemannian manifolds (M,h)(M, h) admitting a space dependence of a ship's speed 0<u(x)h10<|u(x)|_h\leq1 in the presence of a perturbation W~\tilde{W} determined by a strong velocity vector field satisfying W~(x)h=u(x)h|\tilde{W}(x)|_h=|u(x)|_h, with application of Finsler m…

2016-06-03abs ↗pdf ↗

We consider the Zermelo navigation problem on the ellipsoid of revolution (spheroid) in the presence of a perturbation WW determined by a mild velocity vector field, W<1|W|<1, with application of Finsler metric of Randers type in the context of the corresponding optimal control represented by a time-efficient ship's he…

2016-01-30abs ↗pdf ↗

Paper develops a neural-fuzzy controller for GPS-intelligent buoys.

problem Optimally track dynamically positioned marine buoys with unknown parameters.
method Dynamic system modeling using neural-fuzzy networks with backstepping technique.
result The controller minimizes position errors and adjusts buoy positions accurately.

Paper proposes a deep learning model for understanding e-commerce addresses.

problem Challenges in parsing shipping addresses with no fixed format.
method Combines NLP techniques with pre-processing steps for addresses, uses RoBERTa for vector representations.
result RoBERTa model achieves 90% accuracy in sub-region classification for North and South Indian cities.

Apache Spark is a popular open-source platform for large-scale data processing that is well-suited for iterative machine learning tasks. In this paper we present MLlib, Spark's open-source distributed machine learning library. MLlib provides efficient functionality for a wide range of learning settings and includes sev…

2015-05-26abs ↗pdf ↗

We generalize and study the Zermelo navigation problem on Hermitian manifolds in the presence of a perturbation WW determined by a mild complex velocity vector field W(z)h<u(z)h||W(z)||_h<||u(z)||_h, with application of complex Finsler metric of complex Randers type. By admitting space-dependence of ship's relative speed $||u(…

2016-11-11abs ↗pdf ↗

Experts predict significant adoption of decentralized finance by 2034, with traditional finance adapting.

problem Adoption and integration of decentralized finance (DeFi) in financial services.
method Survey analysis using New Institutional Economics and Dynamic Capabilities Theory.
result Experts expect adoption of DeFi to rise from negligible to 43% by 2034, with traditional finance likely to embrace it.

The objective of the note is to remind readers on how self-financing works in Quantitative Finance. The authors have observed continuing uncertainty on this issue which may be because it lies exactly at the intersection of stochastic calculus and finance. The concept of a self-financing trading strategy was originally,…

2015-01-12abs ↗pdf ↗

Study shows 'Belt and Road' node cities boost digital finance in China.

problem Impact of 'Belt and Road' node cities on digital inclusive finance.
method Descriptive analysis, literature review, theoretical model, differential differential method.
result Establishment of 'Belt and Road' node cities promotes digital inclusive finance in China, with Internet development as a mediating variable.

Study uses AI to predict changes in international public finances based on US markets.

problem Understanding correlations between US and international public finances.
method Artificial intelligence and neural networks to model and predict changes.
result Neural network model achieved MSE of 2.79, indicating significant correlation and impact of US market volatility on international markets.

Theoretical framework for data augmentation in finance improves portfolio construction.

problem Improving portfolio construction in speculative markets.
method Developed a theoretical framework for data augmentation and regularization in deep learning for finance.
result A simple noise injection algorithm improves portfolio construction over no noise.

Study on women entrepreneurs' access to finance in France.

problem Inequalities in accessing external finance for women entrepreneurs in France.
method Quantitative approach using data from a representative sample of women entrepreneurs.
result Founder status affects access to external finance; increases success in fundraising but reduces bank finance.