Main Reference PaperSequence Classification of the Limit Order Book using Recurrent Neural Networks, Journal of Computational Science, 2018.[Python]
  • The proposed method exploits the Recurrent Neural Network (RNN) to predict the forthcoming price-flip based on the shorter observation sequences of limit order book depths and orders. The RNN based classification helps to resolve the sequence classification constraints.

Description
  • The proposed method exploits the Recurrent Neural Network (RNN) to predict the forthcoming price-flip based on the shorter observation sequences of limit order book depths and orders. The RNN based classification helps to resolve the sequence classification constraints.

  • To address the sequence classification issue

  • To avoid conflicting price selection

Aim & Objectives
  • To address the sequence classification issue

  • To avoid conflicting price selection

  • To reduce the memory and time constraints under handling the large-scale historical data

Contribution
  • To reduce the memory and time constraints under handling the large-scale historical data

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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