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Predicting stock market using natural language processing
Puh, Karlo; Bagić Babac, Marina - In: American journal of business 38 (2023) 2, pp. 41-61
Persistent link: https://www.econbiz.de/10014342260
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Forecasting Spanish economic activity in times of COVID-19 by means of the RT-LEI and machine learning techniques
Poza, Carlos; Monge González, Manuel - In: Applied economics letters 30 (2023) 4, pp. 472-477
Persistent link: https://www.econbiz.de/10013553654
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From data to action : empowering COVID-19 monitoring and forecasting with intelligent algorithms
Charles, Vincent; Mousavi, Seyed Muhammad Hossein; … - In: Journal of the Operational Research Society 75 (2024) 7, pp. 1261-1278
Persistent link: https://www.econbiz.de/10014555908
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Big Data in Energy Economics
Liu, Hui; Nikitas, Nikolaos; Li, Yanfei; Yang, Rui - 2022
Preface -- Chapter 1 Introduction -- Chapter 2 Big Data Analysis of Energy Economics in Oil Market -- Chapter 2 Big Data Analysis of Energy Economics in Oil Market -- Chapter 3 Big Data Analysis of Energy Economics in Coal Market -- Chapter 4 Big Data Analysis of Energy Economics in Wind Power...
Persistent link: https://www.econbiz.de/10012819083
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Combining robust dynamic neural networks with traditional technical indicators for generating mechanic trading signals
Giribone, Pier Giuseppe; Ligato, Simone; Penone, Francesco - In: International journal of financial engineering 5 (2018) 4, pp. 1-44
Persistent link: https://www.econbiz.de/10012028821
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Forecasting tourist daily arrivals with a hybrid SARIMA-LSTM approach
Wu, Chi Wai; Ji, Lei; He, Kaijian; Tso, Kwok Fai Geoffrey - In: Journal of hospitality & tourism research : JHTR ; the … 45 (2021) 1, pp. 52-67
Persistent link: https://www.econbiz.de/10012426089
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Evaluating the effectiveness of modern forecasting models in predicting commodity futures prices in volatile economic times
Vancsura, László; Tatay, Tibor; Bareith, Tibor - In: Risks : open access journal 11 (2023) 2, pp. 1-16
The paper seeks to answer the question of how price forecasting can contribute to which techniques gives the most accurate results in the futures commodity market. A total of two families of models (decision trees, artificial intelligence) were used to produce estimates for 2018 and 2022 for 21-...
Persistent link: https://www.econbiz.de/10014233184
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Forecasting exchange rates with neural networks : time variation, nonstationarity, and causal models
Reikard, Gordon - In: International economic journal 37 (2023) 2, pp. 202-219
Persistent link: https://www.econbiz.de/10014295003
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A gated recurrent unit approach to bitcoin price prediction
Dutta, Aniruddha; Kumar, Saket; Basu, Meheli - In: Journal of risk and financial management : JRFM 13 (2020) 2/23, pp. 1-16
In today's era of big data, deep learning and artificial intelligence have formed the backbone for cryptocurrency portfolio optimization. Researchers have investigated various state of the art machine learning models to predict Bitcoin price and volatility. Machine learning models like recurrent...
Persistent link: https://www.econbiz.de/10012173959
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Nonparametric uncertain time series models : theory and application in Brent crude oil spot price analysis
Zhang, Yi; Gao, Jinwu - In: Fuzzy optimization and decision making : a journal of … 23 (2024) 2, pp. 239-252
Persistent link: https://www.econbiz.de/10015079783