Publication details

FX Market Volatility Modelling: Can we use low-frequency data?

Investor logo
Authors

LYÓCSA Štefan PLÍHAL Tomáš VÝROST Tomáš

Year of publication 2021
Type Article in Periodical
Magazine / Source Finance Research Letters
MU Faculty or unit

Faculty of Economics and Administration

Citation
Web https://www.sciencedirect.com/science/article/pii/S1544612320315907#!
Doi http://dx.doi.org/10.1016/j.frl.2020.101776
Keywords Daily price; range; Realized volatility; Expected shortfall; Forecasting
Attached files
Description High-frequency data tend to be costly, subject to microstructure noise, difficult to manage, and lead to high computational costs. Is it always worth the extra effort? We compare the forecasting accuracy of low- and high-frequency volatility models on the market of six major foreign exchange market (FX) pairs. Our results indicate that for short-forecast horizons, high-frequency models dominate their low-frequency counterparts, particularly in periods of increased volatility. With an increased forecast horizon, low-frequency volatility models become competitive, suggesting that if high-frequency data are not available, low-frequency data can be used to estimate and predict long-term volatility in FX markets.
Related projects:

You are running an old browser version. We recommend updating your browser to its latest version.

More info