---
title: Volatility Connectedness in Global Forex Markets
url: https://www.ml-quant.com/papers/ssrn/5130870/
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 5130870
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5130870
featured: 2025-02-19
citations: unknown
topic: Derivatives & Volatility
---


# Volatility Connectedness in Global Forex Markets

The study examines volatility links among top traded currencies, identifying the Swiss franc and Japanese yen as ideal for managing currency risk.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5130870
- Identifier: SSRN 5130870
- Released: 2025-02-10
- First featured: Quant Letter No. 85 (2025-02-19): https://www.ml-quant.com/issues/2025-02-19/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Derivatives & Volatility

## Related

- [Filling in Missing FX Implied Volatilities with Uncertainties: Improving VAE-Based Volatility Imputation](https://www.ml-quant.com/papers/arxiv/2411.05998/): The study explores enhancing the prediction of missing implied volatilities in FX options using modified variational autoencoders (VAEs), which better manage data uncertainty.
- [Foreign Exchange Exposure and Hedging Strategies: A Case-Based Analysis of MNCs](https://www.ml-quant.com/papers/ssrn/4986846/): The article discusses how multinational companies like CocaCola and IBM manage currency exposure using a mix of financial derivatives and natural hedges.
- [Prediction of linear fractional stable motions using codifference, with application to non-Gaussian rough volatility](https://www.ml-quant.com/papers/arxiv/2507.15437/): A new method for predicting future changes in linear fractional stable motion (LFSM) has been proposed, which performs better than the fractional Brownian motion in predicting high-frequency FX rates and volatility time series.
- [CVA Hedging by Risk-Averse Stochastic-Horizon Reinforcement Learning](https://www.ml-quant.com/papers/ssrn/4673150/): The study uses risk-averse Reinforcement Learning for managing potential credit losses on a derivatives portfolio, proving its effectiveness through a numerical study for a portfolio consisting of a single FX forward contract.
- [FX Forecast Volatility in Risk Management](https://www.ml-quant.com/papers/ssrn/5114727/): A dynamic Bayesian model using skewed distributions improves currency risk management and hedging strategies by better capturing financial data asymmetry.
- [Currency Hedging Impact on Exchange Rates](https://www.ml-quant.com/papers/ssrn/5143899/): Nonbank financial institutions tend to sell domestic currency when portfolio returns are low, causing G10 currencies to depreciate against the USD.
