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A comparative study of demand forecasting models for a multi-channel retail company : a novel hybrid machine learning approach

Mitra, Arnab; Jain, Arnav; Kishore, Avinash; Kumar, Pravin - In: Operations research forum 3 (2022) 4, pp. 1-22

Persistent link: https://www.econbiz.de/10013461968

Forecasting Korean stock returns with machine learning

Noh, Hohsuk; Jang, Hyuna; Yang, Cheol-Won - In: Asia-Pacific journal of financial studies 52 (2023) 2, pp. 193-241

Persistent link: https://www.econbiz.de/10014315552

Electricity consumption prediction using artificial intelligence

Čegovnik, Tomaž; Dobrovoljc, Andrej; Povh, Janez; … - In: Central European journal of operations research 31 (2023) 3, pp. 833-851

Persistent link: https://www.econbiz.de/10014326562

Machine learning and the cross-section of emerging market stock returns

Hanauer, Matthias Xaver; Kalsbach, Tobias - In: Emerging markets review 55 (2023), pp. 1-38

Persistent link: https://www.econbiz.de/10014481087

A modified random forest incremental interpretation method for explaining artificial and deep neural networks in cycle time prediction

Chen, Toly; Wang, Yu-Cheng - In: Decision analytics journal 7 (2023), pp. 1-11

Methods based on artificial neural network (ANN) or deep neural network (DNN) applications have been proposed to …-output relationship of an ANN (or DNN) is fitted by decision rules using a random forest approach. Then, domain knowledge is extracted …

Persistent link: https://www.econbiz.de/10014436432

Comparing out-of-sample performance of machine learning methods to forecast U.S. GDP growth

Chu, Ba; Qureshi, Shafiullah - In: Computational economics 62 (2023) 4, pp. 1567-1609

Persistent link: https://www.econbiz.de/10014437505

Using machine learning prediction models for quality control : a case study from the automotive industry

Msakni, Mohamed Kais; Risan, Anders; Schütz, Peter - In: Computational management science 20 (2023) 1, pp. 1-28

Persistent link: https://www.econbiz.de/10014391952

Building portfolios based on machine learning predictions

Kaczmarek, Tomasz; Perez, Katarzyna - In: Economic research 35 (2022) 1,1, pp. 19-37

Persistent link: https://www.econbiz.de/10014380393

Machine learning for cryptocurrency market prediction and trading

Jaquart, Patrick; Köpke, Sven; Weinhardt, Christof - In: The Journal of finance and data science : JFDS 8 (2022), pp. 331-352

We employ and analyze various machine learning models for daily cryptocurrency market prediction and trading. We train the models to predict binary relative daily market movements of the 100 largest cryptocurrencies. Our results show that all employed models make statistically viable...

Persistent link: https://www.econbiz.de/10014433737

A machine learning approach to GDP nowcasting : an emerging market experience

Ghosh, Saurabh; Ranjan, Abhishek - In: Bulletin of monetary economics and banking 26 (2023), pp. 33-54

Persistent link: https://www.econbiz.de/10014266367