Triangular Arbitrage Opportunities Research Articles

Price discovery in fiat currency and cryptocurrency markets

We study the dynamic relations between the direct exchange rate of fiat currencies and the rate implied by bitcoin prices. The empirical results show the deviation between actual and implied rates of EUR/USD, GBP/USD, and JPY/USD affects the movements of actual and BTC-implied rates. We observe that implied rates contribute more to price discovery than actual rates before 2019 for EUR/USD and before 2018 for JPY/USD. Triangular arbitrage opportunities arise when VIX is high. The arbitrage opportunities are also related to the market capitalization of bitcoin and the trading of bitcoin futures on CBOE and CME.

Detecting correlations and triangular arbitrage opportunities in the Forex by means of multifractal detrended cross-correlations analysis

Multifractal detrended cross-correlation methodology is described and applied to Foreign exchange (Forex) market time series. Fluctuations of high-frequency exchange rates of eight major world currencies over 2010–2018 period are used to study cross-correlations. The study is motivated by fundamental questions in complex systems’ response to significant environmental changes and by potential applications in investment strategies, including detecting triangular arbitrage opportunities. Dominant multiscale cross-correlations between the exchange rates are found to typically occur at smaller fluctuation levels. However, hierarchical organization of ties expressed in terms of dendrograms, with a novel application of the multiscale cross-correlation coefficient, is more pronounced at large fluctuations. The cross-correlations are quantified to be stronger on average between those exchange rate pairs that are bound within triangular relations. Some pairs from outside triangular relations are, however, identified to be exceptionally strongly correlated as compared to the average strength of triangular correlations. This in particular applies to those exchange rates that involve Australian and New Zealand dollars and reflects their economic relations. Significant events with impact on the Forex are shown to induce triangular arbitrage opportunities which at the same time reduce cross-correlations on the smallest timescales and act destructively on the multiscale organization of correlations. In 2010–2018, such instances took place in connection with the Swiss National Bank intervention and the weakening of British pound sterling accompanying the initiation of Brexit procedure. The methodology could be applicable to temporal and multiscale pattern detection in any time series.

Detecting and identifying arbitrage in the spot foreign exchange market

We propose a theoretical framework for the detection and identification of triangular arbitrage opportunities between currency exchange rates in the spot foreign exchange market. We obtain sufficient conditions for the exclusion of triangular arbitrage opportunities in the setting of non-trivial transaction costs in terms of the currency rates of the market under consideration. Then we propose an efficient computational approach which can detect triangular arbitrage opportunities in real time. Finally, we consider numerical studies that utilize spot currency exchange rate quotes to substantiate and present applications of the theoretical findings as well as to demonstrate the efficiency of the proposed computational arbitrage detection and identification methods.

A new wavelet-based ultra-high-frequency analysis of triangular currency arbitrage

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.

Robust Prediction of Triangular Currency Arbitrage with Liquidity and Realized Risk Measures: A New Wavelet-Based Ultra-High-Frequency Analysis

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 milliseconds) 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.

Teaching The Bid-Ask Spread And Triangular Arbitrage For The Foreign Exchange Market

The foreign exchange (FX) market is an important chapter in international finance. Understanding the market microstructure is critical for learning the FX market. To assist students better understand the FX market microstructure, an instructor can use an event study with minute-by-minute quote data provided in the Excel assignment, asking students to investigate the impact of an event on the bid-ask spread and triangular arbitrage opportunities. This pedagogical paper provides two examples of making the Excel assignment for reference.

Detecting Arbitrage in the Foreign Exchange Market

In this paper, we propose a theoretical and computational framework for the detection and identification of (triangular) arbitrage opportunities among spot currency exchange rates in a foreign exchange market. We obtain sufficient conditions for excluding the triangular arbitrage opportunities in a market with or without market frictions, i.e. transaction costs. Then we propose a very efficient computational approach not only to detect triangular arbitrage opportunities in real time but also to identify the combinations of currencies that lead to the arbitrage opportunity from market data. In numerical studies, we utilize empirical data of foreign currency exchange rates to substantiate our theoretical findings and demonstrate the efficiency of the proposed computational approach.

Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market

ABSTRACTWe study the impact of algorithmic trading (AT) in the foreign exchange market using a long time series of high‐frequency data that identify computer‐generated trading activity. We find that AT causes an improvement in two measures of price efficiency: the frequency of triangular arbitrage opportunities and the autocorrelation of high‐frequency returns. We show that the reduction in arbitrage opportunities is associated primarily with computers taking liquidity. This result is consistent with the view that AT improves informational efficiency by speeding up price discovery, but that it may also impose higher adverse selection costs on slower traders. In contrast, the reduction in the autocorrelation of returns owes more to the algorithmic provision of liquidity. We also find evidence consistent with the strategies of algorithmic traders being highly correlated. This correlation, however, does not appear to cause a degradation in market quality, at least not on average.

THE MIRAGE OF TRIANGULAR ARBITRAGE IN THE SPOT FOREIGN EXCHANGE MARKET

We investigate triangular arbitrage within the spot foreign exchange market using high-frequency executable prices. We show that triangular arbitrage opportunities do exist, but that most have short durations and small magnitudes. We find intra-day variations in the number and length of arbitrage opportunities, with larger numbers of opportunities with shorter mean durations occurring during more liquid hours. We demonstrate further that the number of arbitrage opportunities has decreased in recent years, implying a corresponding increase in pricing efficiency. Using trading simulations, we show that a trader would need to beat other market participants to an unfeasibly large proportion of arbitrage prices to profit from triangular arbitrage over a prolonged period of time. Our results suggest that the foreign exchange market is internally self-consistent and provide a limited verification of market efficiency.

Triangular arbitrage as an interaction among foreign exchange rates

We first show that there are in fact triangular arbitrage opportunities in the spot foreign exchange markets, analyzing the time dependence of the yen–dollar rate, the dollar–euro rate and the yen–euro rate. Next, we propose a model of foreign exchange rates with an interaction. The model includes effects of triangular arbitrage transactions as an interaction among three rates. The model explains the actual data of the multiple foreign exchange rates well.