arXiv Open Access 2025

Forecasting Intraday Volume in Equity Markets with Machine Learning

Mihai Cucuringu Kang Li Chao Zhang

Lihat Sumber

Abstrak

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.

Topik & Kata Kunci

q-fin.CP q-fin.ST

Penulis (3)

Mihai Cucuringu

Kang Li

Chao Zhang

Format Sitasi

APA MLA BibTeX

Cucuringu, M., Li, K., Zhang, C. (2025). Forecasting Intraday Volume in Equity Markets with Machine Learning. https://arxiv.org/abs/2505.08180

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Informasi Jurnal

Tahun Terbit: 2025
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓