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Understanding Dynamic Market Condition Using Deep Direct Reinforcement Learning
, Ashwini Chavan
Published in Universal Review
Volume: VIII
Issue: II
Pages: 151.0 - 155.0
The Share Market Prices fluctuates very often because of multiple external variables like crude oil price change, gold, government policy change, etc. This paper describes the Deep Neural Network (DNN) for the actual-time financial fluctuations (stock market) and also for future market price situation prediction. Authors have design the model by using two related important concepts of Deep Learning (DL) and Reinforcement Learning (RL). For informative feature learning, deep learning is used to automatically sense the dynamic market condition. Then, using this deep information, RL module takes decisions about trading to collect the rewards in strange environment. Many researchers have developed various Deep Learning Models and Algorithms to predict the Share Market fluctuations. This paper talks about the understanding of the dynamic market and the deep learning techniques to understand and predict the future situation in Share Market Prices.
About the journal
JournalUniversal Review
PublisherUniversal Review
Open Access0