---
title: Modeling Volatility
url: https://www.ml-quant.com/papers/repec/bla-socsci-v-105-y-2024-i-4-p-965-979/
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:bla:socsci:v:105:y:2024:i:4:p:965-979
source_url: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1111%2Fssqu.13406%3Bh%3Drepec%3Abla%3Asocsci%3Av%3A105%3Ay%3A2024%3Ai%3A4%3Ap%3A965-979
featured: 2024-08-21
citations: unknown
topic: Derivatives & Volatility
---


# Modeling Volatility

The research shows the effectiveness of modeling compositional volatility, using German political party support and US income shares data as examples.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1111%2Fssqu.13406%3Bh%3Drepec%3Abla%3Asocsci%3Av%3A105%3Ay%3A2024%3Ai%3A4%3Ap%3A965-979
- Identifier: RePEc:bla:socsci:v:105:y:2024:i:4:p:965-979
- Released: 2024-08-21
- First featured: Quant Letter No. 62 (2024-08-21): https://www.ml-quant.com/issues/2024-08-21/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Derivatives & Volatility

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