---
title: Observable vs Latent Markov Chains for Volatility
url: https://www.ml-quant.com/papers/ssrn/4706972/
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 4706972
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4706972
featured: 2024-01-30
citations: unknown
topic: Derivatives & Volatility
---


# Observable vs Latent Markov Chains for Volatility

The latent-regime Betat-EGARCH model outperforms the observable-regime Betat-EGARCH model in in-sample statistical performance, but their out-of-sample density forecasting performances are similar.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4706972
- Identifier: SSRN 4706972
- Released: 2024-01-25
- First featured: Quant Letter No. 35 (2024-01-30): https://www.ml-quant.com/issues/2024-01-30/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Derivatives & Volatility

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