---
title: Pre-registering a Market Risk Backtest: A Frozen Gaussian Model for a Rates and Currency Portfolio, 2015–25
url: https://www.ml-quant.com/papers/ssrn/7616161/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-10-16
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 7616161
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7616161
featured: 2026-10-16
citations: unknown
topic: Derivatives & Volatility
---


# Pre-registering a Market Risk Backtest: A Frozen Gaussian Model for a Rates and Currency Portfolio, 2015–25

A frozen Gaussian VaR model, pre-registered and anchored in Bitcoin, passed coverage tests but showed clustering in 2020, 2022 and 2023, while exponentially weighted variance improved.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7616161
- Identifier: SSRN 7616161
- Released: 2026-10-16
- First featured: Quant Letter No. 135 (2026-10-16): https://www.ml-quant.com/issues/2026-10-16/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Derivatives & Volatility
- Authors: Rishith Sharma

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