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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

Improving out-of-sample forecasts of stock price indexes with forecast reconciliation and clustering

Mattera, Raffaele; Athanasopoulos, George; Hyndman, Rob J. - 2023

Persistent link: https://www.econbiz.de/10014452575

Healthcare operations and black swan event for COVID-19 pandemic : a predictive analytics

Devarajan, Jinil Persis; Manimuthu, Arunmozhi; … - In: IEEE transactions on engineering management : EM 70 (2023) 9, pp. 3229-3243

Persistent link: https://www.econbiz.de/10014364887

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

The predictive power of public Twitter sentiment for forecasting cryptocurrency prices

Kraaijeveld, Olivier; De Smedt, Johannes - In: Journal of international financial markets, … 65 (2020), pp. 1-22

Persistent link: https://www.econbiz.de/10012495742

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

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

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

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

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

shown to perform better than traditional time series models in cryptocurrency price prediction. However, very few studies …

Persistent link: https://www.econbiz.de/10012173959

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