Hybrid Vector Auto Regression and Neural Network Model for Order Flow Imbalance Prediction in High Frequency Trading
Published in The Journal of Financial Data Science, 2024
This paper proposes a hybrid model that integrates Vector Auto Regression with Neural Networks to predict order flow imbalance in high-frequency trading. The results demonstrate improved forecasting accuracy and robustness compared to traditional models.
Recommended citation: Abdul Rahman, Neelesh Upadhye. (2024). "Hybrid Vector Auto Regression and Neural Network Model for Order Flow Imbalance Prediction in High Frequency Trading." The Journal of Financial Data Science. Submitted for review.
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