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  • Search: subject:"Stock volatility prediction"
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Year of publication
Subject
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Artificial chemical reaction optimization 2 Artificial neural network 2 Extreme learning machine 2 Financial time series forecasting 2 Genetic algorithm 2 Particle swarm optimization 2 Single layer feed-forward network 2 Stock volatility prediction 2 Algorithm 1 Algorithmus 1 Artificial intelligence 1 Börsenkurs 1 Chemical industry 1 Chemieindustrie 1 Evolutionary algorithm 1 Evolutionärer Algorithmus 1 Forecast 1 Forecasting model 1 Künstliche Intelligenz 1 Learning process 1 Lernprozess 1 Mathematical programming 1 Mathematische Optimierung 1 Neural networks 1 Neuronale Netze 1 Prognose 1 Prognoseverfahren 1 Share price 1 Theorie 1 Theory 1 Volatility 1 Volatilität 1
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Online availability
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Free 2 CC license 1
Type of publication
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Article 2
Type of publication (narrower categories)
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Article 1 Article in journal 1 Aufsatz in Zeitschrift 1
Language
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English 2
Author
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Mishra, Bijan Bihari 2 Nayak, Sarat 1 Nayak, Sarat Chandra 1
Published in...
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Financial Innovation 1 Financial innovation : FIN 1
Source
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ECONIS (ZBW) 1 EconStor 1
Showing 1 - 2 of 2
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Extreme learning with chemical reaction optimization for stock volatility prediction
Nayak, Sarat Chandra; Mishra, Bijan Bihari - In: Financial Innovation 6 (2020) 1, pp. 1-23
Extreme learning machine (ELM) allows for fast learning and better generalization performance than conventional gradient-based learning. However, the possible inclusion of non-optimal weight and bias due to random selection and the need for more hidden neurons adversely influence network...
Persistent link: https://www.econbiz.de/10012602852
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Cover Image
Extreme learning with chemical reaction optimization for stock volatility prediction
Nayak, Sarat; Mishra, Bijan Bihari - In: Financial innovation : FIN 6 (2020) 16, pp. 1-23
Extreme learning machine (ELM) allows for fast learning and better generalization performance than conventional gradient-based learning. However, the possible inclusion of non-optimal weight and bias due to random selection and the need for more hidden neurons adversely influence network...
Persistent link: https://www.econbiz.de/10012268745
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