---
title: Mixed-Frequency Volatility Model
url: https://www.ml-quant.com/papers/repec/taf-reroxx-v-36-y-2023-i-1-p-2117228/
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: RePEc:taf:reroxx:v:36:y:2023:i:1:p:2117228
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1080%2F1331677X.2022.2117228%3Bh%3Drepec%3Ataf%3Areroxx%3Av%3A36%3Ay%3A2023%3Ai%3A1%3Ap%3A2117228
featured: 2024-03-20
citations: unknown
topic: Derivatives & Volatility
---


# Mixed-Frequency Volatility Model

The MF-MoP model, based on predictability momentum, is more effective than GARCH and Realized GARCH models in predicting financial asset volatility.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1080%2F1331677X.2022.2117228%3Bh%3Drepec%3Ataf%3Areroxx%3Av%3A36%3Ay%3A2023%3Ai%3A1%3Ap%3A2117228
- Identifier: RePEc:taf:reroxx:v:36:y:2023:i:1:p:2117228
- Released: 2023-04-01
- First featured: Quant Letter No. 41 (2024-03-20): https://www.ml-quant.com/issues/2024-03-20/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Derivatives & Volatility

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