Search Results - subject:"ensemble methods"

Enhancing Bitcoin trading signal prediction in crisis periods using an improved machine learning approach

Sadati-Keneti, Yaser; Sebt, Mohammad Vahid; … - In: Risks : open access journal 14 (2026) 3, pp. 1-25

The aim of this research is to employ improved machine learning techniques to determine the best Bitcoin trading positions in response to sudden price changes caused by global emergencies such as pandemics, conflicts, and economic disputes. Specifically, this study examines price fluctuations...

Persistent link: https://www.econbiz.de/10015638961

Enhancing fraud detection in banking using advanced machine learning techniques

Detthamrong, Umawadee; Chansanam, Wirapong; Boongoen, … - In: International journal of economics and financial issues … 14 (2024) 5, pp. 177-184

Persistent link: https://www.econbiz.de/10015085228

A machine learning approach for flagging incomplete bid-rigging cartels

Wallimann, Hannes; Imhof, David; Huber, Martin - In: Computational economics 62 (2023) 4, pp. 1669-1720

Persistent link: https://www.econbiz.de/10014437552

Shipping economic forecasting : recent developments, applications, and future directions

Mo, Jixian; Gao, Ruobin; Yuen, Kum Fai; Suganthan, … - In: Transport reviews : a transnational transdisciplinary … 45 (2025) 6, pp. 897-923

Persistent link: https://www.econbiz.de/10015547214

Ensemble interval forecasts of mortality

Li, Jackie; Wang, Mingke; Liu, Jacie Jia; Tickle, Leonie - In: Scandinavian actuarial journal 2025 (2025) 6, pp. 598-616

Persistent link: https://www.econbiz.de/10015534589

Improved hybrid resampling and ensemble model for imbalance learning and credit evaluation

Kou, Gang; Chen, Hao; Hefni, Mohammed A. - In: Journal of management science and engineering 7 (2022) 4, pp. 511-529

A clustering-based undersampling (CUS) and distance-based near-miss method are widely used in current imbalanced learning algorithms, but this method has certain drawbacks. In particular, the CUS does not consider the influence of the distance factor on the majority of instances, and the...

Persistent link: https://www.econbiz.de/10014315644

The wisdom of crowds in forecasting at high-frequency for multiple time horizons : a case study of the Brazilian retail sales

Lopes, Gustavo - In: Revista Brasileira de Finanças : RBFin 20 (2022) 2, pp. 77-115

Persistent link: https://www.econbiz.de/10013257742

Creditworthiness pattern prediction and detection for GCC Islamic banks using machine learning techniques

Shilbayeh, Samar; Grassa, Rihab - In: International journal of Islamic and Middle Eastern … 17 (2024) 2, pp. 345-365

Persistent link: https://www.econbiz.de/10014547069

A machine learning-based analysis on the causality of financial stress in banking institutions

Souza, João Gabriel de Moraes; Castro, Daniel Tavares de; … - In: Computational economics 64 (2024) 3, pp. 1857-1890

Persistent link: https://www.econbiz.de/10015143964

An implementation of ensemble methods, logistic regression, and neural network for default prediction in peer-to-peer lending

Dzik-Walczak, Aneta; Heba, Mateusz - In: Zbornik radova Ekonomskog Fakulteta u Rijeci : časopis … 39 (2021) 1, pp. 163-197

Persistent link: https://www.econbiz.de/10012615873