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Meso-Scale Particle Image Velocimetry Studies of Neurovascular Flows In Vitro
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Volume Prediction With Neural Networks.

Daniel Libman1, Simi Haber1, Mary Schaps1

  • 1Department of Mathematics, Bar-Ilan University, Ramat Gan, Israel.

Frontiers in Artificial Intelligence
|March 18, 2021
PubMed
Summary
This summary is machine-generated.

Forecasting intraday trading volume changes is crucial for algorithmic trading. This study introduces a hybrid Long Short Term Memory (LSTM) and Autoregressive (AR) model, enhanced with time-of-day data, for accurate volume prediction.

Keywords:
LSTMchange in volumefinancemachine learningneural networksvolume prediction

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Area of Science:

  • Quantitative Finance
  • Machine Learning
  • Financial Market Analysis

Background:

  • Algorithmic trading strategies rely heavily on accurate intraday trading volume forecasts.
  • Understanding and predicting trading volume is essential for financial market analysis.

Purpose of the Study:

  • To develop a novel method for forecasting the log change in trading volume.
  • To evaluate the efficacy of Long Short Term Memory (LSTM) networks, Support Vector Regression (SVR), and Autoregressive (AR) models in volume prediction.

Main Methods:

  • A hybrid model combining LSTM with AR was developed.
  • The model was extended to incorporate time-of-day data to capture intraday patterns.
  • Support Vector Regression (SVR) was also utilized for comparative analysis.

Main Results:

  • The LSTM-based hybrid model, particularly with AR, demonstrated superior forecasting accuracy.
  • Incorporating time-of-day data significantly improved the model's ability to associate volume changes with specific hours.
  • The hybrid LSTM-AR model with temporal data achieved the best performance.

Conclusions:

  • Hybrid LSTM-AR models offer a powerful approach for forecasting log changes in intraday trading volume.
  • Time-of-day data is a critical feature for enhancing the accuracy of trading volume prediction models.
  • This method provides a valuable tool for algorithmic trading strategies and financial market understanding.