Forecasting Intraday Volume in Equity Markets with Machine Learning
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866916734988976128 |
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| author | Cucuringu, Mihai Li, Kang Zhang, Chao |
| author_facet | Cucuringu, Mihai Li, Kang Zhang, Chao |
| contents | This study focuses on forecasting intraday trading volumes, a crucial component for portfolio implementation, especially in high-frequency (HF) trading environments. Given the current scarcity of flexible methods in this area, we employ a suite of machine learning (ML) models enriched with numerous HF predictors to enhance the predictability of intraday trading volumes. Our findings reveal that intraday stock trading volume is highly predictable, especially with ML and considering commonality. Additionally, we assess the economic benefits of accurate volume forecasting through Volume Weighted Average Price (VWAP) strategies. The results demonstrate that precise intraday forecasting offers substantial advantages, providing valuable insights for traders to optimize their strategies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_08180 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Forecasting Intraday Volume in Equity Markets with Machine Learning Cucuringu, Mihai Li, Kang Zhang, Chao Computational Finance Statistical Finance This study focuses on forecasting intraday trading volumes, a crucial component for portfolio implementation, especially in high-frequency (HF) trading environments. Given the current scarcity of flexible methods in this area, we employ a suite of machine learning (ML) models enriched with numerous HF predictors to enhance the predictability of intraday trading volumes. Our findings reveal that intraday stock trading volume is highly predictable, especially with ML and considering commonality. Additionally, we assess the economic benefits of accurate volume forecasting through Volume Weighted Average Price (VWAP) strategies. The results demonstrate that precise intraday forecasting offers substantial advantages, providing valuable insights for traders to optimize their strategies. |
| title | Forecasting Intraday Volume in Equity Markets with Machine Learning |
| topic | Computational Finance Statistical Finance |
| url | https://arxiv.org/abs/2505.08180 |