Assessing cross-currency predictability in forex markets: Insights from limit order book data

Yana Petrova, Anders Vilhelmsson and Lars L. Nordén

International Journal of Forecasting, 2026, vol. 42, issue 3, 937-953

Abstract: Theoretical research suggests potential cross-currency predictability in currency exchange markets, but empirical findings with macro-based models show mixed results. This has led to a growing focus on micro-based models which explore how trading integrates fundamental information into exchange rates. This study stands out by using detailed limit order book data for the foreign exchange market, enabling micro-level insights. It covers multiple currency pairs, assessing cross-currency predictability. Emphasizing short-term forecasts from one minute to one hour, it introduces factor-augmented regressions, including unsupervised and supervised principal components analysis to tackle data dimensionality, and contrasts those to LASSO and random forest methods. Our findings reveal generally low predictability across various models, supporting the efficient market hypothesis. We find that cross-currency variables offer limited additional insight, but certain microstructure variables like order flow show short-term predictive power, suggesting transient market inefficiencies.

Keywords: Forecasting; Market microstructure; Common factors; Principal components; Thresholding (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0169207025001281
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:42:y:2026:i:3:p:937-953

DOI: 10.1016/j.ijforecast.2025.12.007

Access Statistics for this article

International Journal of Forecasting is currently edited by R. J. Hyndman

More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Catherine Liu ().