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Forecasting Stock Prices from the Limit Order Book Using Convolutional Neural Networks.

, , , , , и . CBI (1), стр. 7-12. IEEE Computer Society, (2017)

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Avraam Chatzivasileiou

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Другие публикации лиц с тем же именем

Using Deep Learning for price prediction by exploiting stationary limit order book features., , , , , и . CoRR, (2018)Time-series classification using neural Bag-of-Features., , , , , и . EUSIPCO, стр. 301-305. IEEE, (2017)Using Deep Learning for price prediction by exploiting stationary limit order book features., , , , , и . Appl. Soft Comput., (2020)Improving Deep Reinforcement Learning for Financial Trading Using Neural Network Distillation., , и . MLSP, стр. 1-6. IEEE, (2020)Using deep learning to detect price change indications in financial markets., , , , , и . EUSIPCO, стр. 2511-2515. IEEE, (2017)Multisource financial sentiment analysis for detecting Bitcoin price change indications using deep learning., , , , , , и . Neural Comput. Appl., 34 (22): 19441-19452 (2022)Improving Deep Reinforcement Learning for Financial Trading Using Deep Adaptive Group-Based Normalization., , , и . MLSP, стр. 1-6. IEEE, (2021)Forecasting Stock Prices from the Limit Order Book Using Convolutional Neural Networks., , , , , и . CBI (1), стр. 7-12. IEEE Computer Society, (2017)Learning Sentiment-Aware Trading Strategies for Bitcoin Leveraging Deep Learning-Based Financial News Analysis., , , и . AIAI, том 627 из IFIP Advances in Information and Communication Technology, стр. 757-766. Springer, (2021)Deep learning techniques for financial data. Aristotle University Of Thessaloniki, Greece, (2021)National Archive of PhD Theses: oai:10442/51390.