Metadatas
February, 2020
- ISIDORE Id: 10670/1.ccc5e0...
- hal: hal-02512423
- doi: 10.1016/j.econmod.2019.05.006
- PII: S0264-9993(18)31907-2
HALSHS : archive ouverte en Sciences de l’Homme et de la Société - notices sans texte intégral
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info:eu-repo/semantics/altIdentifier/doi/10.1016/j.econmod.2019.05.006
http://creativecommons.org/licenses/by-nc/ , info:eu-repo/semantics/OpenAccess
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Arbitrage--Law and legislationCite this document
Nikola Gradojevic et al., « A new wavelet-based ultra-high-frequency analysis of triangular currency arbitrage », HALSHS : archive ouverte en Sciences de l’Homme et de la Société - notices sans texte intégral, ID : 10.1016/j.econmod.2019.05.006
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Abstract
We develop a new framework to characterize the dynamics of triangular (three-point) arbitrage in electronic foreign exchange markets. To examine the properties of arbitrage, we propose a wavelet-based regression approach that is robust to estimation errors, measurement bias and persistence. Relying on this wavelet-based (denoising) inference, we consider various liquidity and market risk indicators to predict arbitrage in a unique ultra-high-frequency exchange rate data set. We find strong empirical evidence that limit order book, realized volatility and cross-correlations help forecast triangular arbitrage profits. The estimates are statistically significant and relevant for investors such that on average 80−100 arbitrage opportunities exist with a short duration (100−500 ms) on a daily basis. Our analysis also reveals that triangular arbitrage opportunities are counter-cyclical at ultra-high-frequency levels: arbitrage returns tend to increase (decrease) in periods when volatility risk and correlations are relatively low (high). We show that liquidity-driven microstructure measures, however, appear to be more powerful in exploiting arbitrage profits when compared to market-driven factors.
