# Lead-lag Relationships in Foreign Exchange Markets

## TL;DR

This paper investigates lead-lag relationships in foreign exchange markets using correlation, partial correlation, and Granger causality, revealing significant directional influences among exchange rates and challenging the efficient market hypothesis.

## Contribution

The study provides a comprehensive analysis of lead-lag effects in FX markets using multiple methods and network analysis, an area less explored compared to stock markets.

## Key findings

- Many exchange rate pairs show statistically significant lead-lag relationships.
- Directed networks reveal influential exchange rates, often stock indexes, via PageRank.
- Results challenge the notion of instantaneous information spread in FX markets.

## Abstract

Lead-lag relationships among assets represent a useful tool for analyzing high frequency financial data. However, research on these relationships predominantly focuses on correlation analyses for the dynamics of stock prices, spots and futures on market indexes, whereas foreign exchange data have been less explored. To provide a valuable insight on the nature of the lead-lag relationships in foreign exchange markets here we perform a detailed study for the one-minute log returns on exchange rates through three different approaches: i) lagged correlations, ii) lagged partial correlations and iii) Granger causality. In all studies, we find that even though for most pairs of exchange rates lagged effects are absent, there are many pairs which pass statistical significance tests. Out of the statistically significant relationships, we construct directed networks and investigate the influence of individual exchange rates through the PageRank algorithm. The algorithm, in general, ranks stock market indexes quoted in their respective currencies, as most influential. In contrast to the claims of the efficient market hypothesis, these findings suggest that all market information does not spread instantaneously.