Lead–lag relationships in foreign exchange markets
Journal
Physica A: Statistical Mechanics and its Applications
Date Issued
2020-02-01
Author(s)
Stojkoski, Viktor
Utkovski, Zoran
Kocarev, Ljupco
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.
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.
Subjects
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