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[1]
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A comparative study of the neural network models for the stock market data classification—A multicriteria optimization approach
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Expert Systems with Applications,
2024 |
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[2]
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Modeling of limit order book data with ordered fuzzy numbers
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Applied Soft Computing,
2024 |
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[3]
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Hawkes-based cryptocurrency forecasting via Limit Order Book data
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arXiv preprint arXiv …,
2023 |
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[4]
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A Signature Transform of Limit Order Book Data for Stock Price Prediction
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IEEE …,
2023 |
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[5]
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Prediction-Based Limit Order Trading
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2023 |
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[6]
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An Integrated Machine Learning Approach Predicting Stock Values Using Order Book Details
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… of International Conference on Data Science …,
2023 |
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[7]
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Modelling a System for Intelligent Forecasting of Trading on Stock Exchanges
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… Systems and Internet …,
2023 |
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[8]
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Conditional generators for limit order book environments: Explainability, challenges, and robustness
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Proceedings of the Fourth …,
2023 |
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[9]
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DE MÉXICO
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2023 |
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[10]
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The prediction of price gap anomaly in Chinese stock market: Evidence from the dependent functional logit model
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Finance Research Letters,
2022 |
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[11]
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Forecasting the Mid-price Movements with High-Frequency LOB: A Dual-Stage Temporal Attention-Based Deep Learning Architecture
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Arabian Journal for Science and Engineering,
2022 |
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[12]
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Mind the Gaps: Short-Term Crypto Price Prediction
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Available at SSRN …,
2022 |
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[13]
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Predicting intraday jumps in stock prices using liquidity measures and technical indicators
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2021 |
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[14]
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Real Time Distributed Stock Market Forecasting using Feed-Forward Neural Networks, Market Orders, and Financial indicators
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2021 |
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[15]
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Algorithmic Sangfroid? The Decline of Sensitivity of Crude Oil Prices to News on Potentially Disruptive Terror Attacks and Political Unrest
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2021 |
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[16]
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Machine Learning for Active Portfolio Management
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The Journal of …,
2021 |
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[17]
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A multicriteria optimization approach for the stock market feature selection
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Computer Science and …,
2021 |
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[18]
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Big Data in Financial Economics
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2021 |
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[19]
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Использование полной книги предельных заказов для прогнозирования скачка цен
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Kazakh Mathematical Journal,
2020 |
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[20]
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An Application of Deep Reinforcement Learning for Order Execution
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2020 |
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[21]
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Using full limit order book for price jump prediction
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2020 |
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[22]
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Artificial Intelligence in Asset Management
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2020 |
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[23]
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The impact of stock market price Fourier transform analysis on the Gated Recurrent Unit classifier model
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2020 |
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[24]
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Multi-level order-flow imbalance in a limit order book
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2019 |
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[25]
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Feature Engineering for Mid-Price Prediction Forecasting with Deep Learning
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2019 |
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[26]
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Ateities sandorių vykdymo analizė
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2019 |
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[27]
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Feature Engineering for Mid-Price Prediction With Deep Learning
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2019 |
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[28]
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Estratégias de investimento baseadas em microestrutura de mercado
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2019 |
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[29]
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Modeling the Information Content of the Limit Order Book by Bagging
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2018 |
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[30]
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A high‐frequency trade execution model for supervised learning
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High Frequency,
2018 |
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[31]
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Predicting Jump Arrivals in Stock Prices Using Neural Networks with Limit Order Book Data
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SSRN,
2018 |
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[32]
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Benchmark dataset for mid‐price forecasting of limit order book data with machine learning methods
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Journal of forecasting,
2018 |
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[33]
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Kernel Optimization Techniques for Price Prediction
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2018 |
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[34]
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Deep learning for limit order books
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2018 |
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[35]
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Стратегія біржової високочастотної торгівлі фінансовими активами: ефективність та етика
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2018 |
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[36]
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ТОРГ?ВЛЯ ТА Б?РЖОВА Д?ЯЛЬН?СТЬ В УКРА?Н?: СУЧАСНИЙ СТАН, КОНЦЕПЦ?? ? СТРАТЕГ?? РОЗВИТКУ
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2018 |
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[37]
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Торгівля та біржова діяльність в Україні: проблеми і стратегії розвитку
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2018 |
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[38]
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Интеграция социальных норм в моделирование процесса принятия финансово-экономических решений
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2018 |
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[39]
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Master Thesis Finance
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2017 |
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[40]
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Quantitative Trading: Algorithms, Analytics, Data, Models, Optimization
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2017 |
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[41]
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Comparing fast-and slow-acting features for short-term price predictions
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Thesis,
2017 |
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[42]
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Sequence classification of the limit order book using recurrent neural networks
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Journal of Computational Science,
2017 |
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[43]
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Tensor representation in high-frequency financial data for price change prediction
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2017 |
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[44]
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High frequency market making with machine learning
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2017 |
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[45]
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Optimal placement in a limit order book: an analytical approach
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Mathematics and Financial Economics,
2017 |
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[46]
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Benchmark dataset for mid-price prediction of limit order book data
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2017 |
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[47]
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Limit order books
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2016 |
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[48]
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Queue imbalance as a one-tick-ahead price predictor in a limit order book
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Market Microstructure and Liquidity,
2016 |
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[49]
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Second order proximal methods applied to elastic net penalised vector generalised linear models
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2016 |
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[50]
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Microstructural changes befor macroeconomic announcements: Predictability of economic surprises in the US market
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2016 |
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[51]
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Une approche mathématique de l'investissement boursier
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Thèse,
2015 |
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[52]
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Marouane Anane
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Thesis,
2015 |
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[53]
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Algorithmic and High-Frequency Trading
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2015 |
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[54]
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On Jump Risk of Liquidation in Limit Order Book
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中央大學統計研究所學位論文,
2015 |
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[55]
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Modelling high-frequency limit order book dynamics with support vector machines
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Quantitative Finance,
2015 |
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[56]
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Microstructural changes before Macroeconomic Announcements: Predictability of Economic Surprises in the US market
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2015 |
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[57]
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Modelling bid and ask prices using constrained hawkes processes: Ergodicity and scaling limit
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SIAM Journal on Financial Mathematics,
2014 |
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[58]
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Detecting and Forecasting High Frequency Price Jumps in the Stock Market
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Available at SSRN 2226455,
2014 |
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[59]
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Kernel Modification Effects for Support Vector Machine Applied to Limit Order Book of Nikkei 225 Futures
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2014 |
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[60]
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Optimal placement in a limit order book
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Bid,
2013 |
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[61]
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An empirical study of a no-arbitrage liquidity model in financial markets where limit order books are modeled by a Brownian sheet
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ProQuest Dissertations Publishing,
2013 |
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[62]
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Modeling high-frequency limit order book dynamics with support vector machines
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2013 |
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[63]
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Ergodicity and scaling limit of a constrained multivariate Hawkes process
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arXiv preprint arXiv:1301.5007,
2013 |
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[64]
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Рекомендовано до друку Вченою радою Дніпровського національного університету імені Олеся Гончара (протокол № 14 від 26.06. 2018) …
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ДА Горовий
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[65]
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A CASE STUDY ON STOCK VALUE PREDICTION USING ENSEMBLE MACHINE LEARNING MODEL
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