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A machine learning pipeline for forecasting time series in the banking sector
Gorodetskaya, Olga; Gobareva, Yana; Koroteev, Mikhail - In: Economies : open access journal 9 (2021) 4, pp. 1-15
The problem of forecasting time series is very widely debated. In recent years, machine learning algorithms have been very prolific in this area. This paper describes a systematic approach to building a machine learning predictive model for solving optimization problems in the banking sector. A...
Persistent link: https://www.econbiz.de/10012800488
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Application of integrated data mining techniques in stock market forecasting
Huang, Chin-yin; Lin, Philip K. P. - In: Cogent economics & finance 2 (2014) 1, pp. 2-17
techniques and supports the decision-making for stock trades. The proposed system embeds the top-down trading theory, artificial … neural network theory, technical analysis, dynamic time series theory, and Bayesian probability theory. To experimentally …
Persistent link: https://www.econbiz.de/10010482340
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An outliers detection and elimination framework in classification task of data mining
Dash, Ch. Sanjeev Kumar; Behera, Ajit Kumar; Dehuri, … - In: Decision analytics journal 6 (2023), pp. 1-8
An outlier is a datum that is far from other data points in which it occurs. It can have a considerable impact on the output. Therefore, removing or resolving it before the analysis is essential to prevent skewing. Outliers in a survey sampling can have a significant outcome on statistical...
Persistent link: https://www.econbiz.de/10014505859
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Forecasting sovereign risk in the euro area via machine learning
Belly, Guillaume; Boeckelmann, Lukas; Caicedo Graciano, … - In: Journal of forecasting 42 (2023) 3, pp. 657-684
Persistent link: https://www.econbiz.de/10014292224
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Datamining und computational finance : Ergebnisse des 7. Karsruher Ökonometrie-Workshops
Bol, Georg (ed.); Hann, Tae Horn (contributor) - 2000
Persistent link: https://www.econbiz.de/10001455393
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Machine learning advances for time series forecasting
Masini, Ricardo P.; Medeiros, Marcelo C.; Mendes, Eduardo F. - In: Journal of economic surveys 37 (2023) 1, pp. 76-111
Persistent link: https://www.econbiz.de/10014287800
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Traffic time series forecasting on highways : a contemporary survey of models, methods and techniques
Jayanthi, G.; Jothilakshmi, P. - In: International journal of logistics systems and … 39 (2021) 1, pp. 77-110
Persistent link: https://www.econbiz.de/10012599143
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Forecasting the total non-coincidental monthly system peak demand in the Philippines : a comparison of seasonal autoregressive integrated moving average models and artificial neura...
Parreno, Samuel John - In: International Journal of Energy Economics and Policy : IJEEP 13 (2023) 5, pp. 544-552
Persistent link: https://www.econbiz.de/10014384462
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Forecasting the stock exchange of Thailand using data mining techniques
Kanokkarn Snae Namahoot; Viphasiri Jantasri - In: International journal of electronic finance : IJEF 10 (2021) 4, pp. 211-231
Persistent link: https://www.econbiz.de/10012798947
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Forecasting S&P 500 index using artificial neural networks and design of experiments
Niaki, Seyed Taghi Akhavan; Hoseinzade, Saeid - In: Journal of industrial engineering international 9 (2013), pp. 1-9
The main objective of this research is to forecast the daily direction of Standard & Poor's 500 (S&P 500) index using an artificial neural network (ANN). In order to select the most influential features (factors) of the proposed ANN that affect the daily direction of S&P 500 (the response),...
Persistent link: https://www.econbiz.de/10009759307