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Machine-learning stock market volatility : predictability, drivers, and economic value
Díaz, Juan; Hansen, Erwin; Cabrera, Gabriel - In: International review of financial analysis 94 (2024), pp. 1-23
Persistent link: https://www.econbiz.de/10014544073
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Predicting stock return and volatility with machine learning and econometric models: a comparative case study of the Baltic stock market
Nõu, Anders; Lapitskaya, Darya; Eratalay, M. Hakan; … - 2021
Persistent link: https://www.econbiz.de/10012694117
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Predicting stock return and volatility with machine learning and econometric models : a comparative case study of the Baltic stock market
Nõu, Anders; Lapitskaya, Darya; Eratalay, M. Hakan; … - In: International journal of computational economics and … 13 (2023) 4, pp. 446-489
Persistent link: https://www.econbiz.de/10014439728
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Realized volatility forecasting with neural networks
Bucci, Andrea - In: Journal of financial econometrics 18 (2020) 3, pp. 502-531
Persistent link: https://www.econbiz.de/10012316696
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Fate of some tourism companies pre and during Covid 19 : using various machine learning models
Sarkar, Astma - In: Praj̄nȧn : journal of social and management sciences 51 (2022/2023) 1, pp. 9-32
Persistent link: https://www.econbiz.de/10013477522
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Forecasting realized volatility with machine learning : panel data perspective
Zhu, Haibin; Bai, Lu; He, Lidan; Liu, Zhi - In: Journal of empirical finance 73 (2023), pp. 251-271
Persistent link: https://www.econbiz.de/10014477028
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Application of artificial intelligence in stock market forecasting : a critique, review, and research agenda
Chopra, Ritika; Sharma, Gagan Deep - In: Journal of risk and financial management : JRFM 14 (2021) 11, pp. 1-34
The stock market is characterized by extreme fluctuations, non-linearity, and shifts in internal and external environmental variables. Artificial intelligence (AI) techniques can detect such non-linearity, resulting in much-improved forecast results. This paper reviews 148 studies utilizing...
Persistent link: https://www.econbiz.de/10012795264
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Application of machine learning in quantitative investment strategies on global stock markets
Grudniewicz, Jan; Ślepaczuk, Robert - 2021
Persistent link: https://www.econbiz.de/10012816704
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Pricing vanilla options using artificial neural networks : application to the South African market
Du Plooy, Ryno; Venter, Pierre J. - In: Cogent economics & finance 9 (2021) 1, pp. 1-15
European call options using a constructed implied volatility surface. The prices generated by the ANN were compared to the …
Persistent link: https://www.econbiz.de/10013183896
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Do Artificial Neural Networks Provide Improved Volatility Forecasts : Evidence from Asian Markets
Sahiner, Mehmet; McMillan, David G.; Kambouroudis, Dimos S - 2021
Forecasts of stock market volatility is an important input for market participants in measuring and managing investment … Machine Learning methods, and specifically Artificial Neural Network (ANN) models to forecast volatility. The ANN models are … measures including the value-at-risk (VaR) average failure rate, the Kupiec LR test, the Christoffersen independence test, the …
Persistent link: https://www.econbiz.de/10013310404