---
title: Intraday Volatility Forecasting
url: https://www.ml-quant.com/papers/ssrn/5216864/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 5216864
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5216864
featured: 2025-04-16
citations: unknown
topic: Derivatives & Volatility
---


# Intraday Volatility Forecasting

The paper presents a new model for predicting high-frequency intraday conditional discrete return densities and volatility using deep learning, which surpasses empirical nonparametric forecasting rules and Space State Models.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5216864
- Identifier: SSRN 5216864
- Released: 2024-03-01
- First featured: Quant Letter No. 93 (2025-04-16): https://www.ml-quant.com/issues/2025-04-16/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Derivatives & Volatility

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