Triangular arbitrage in foreign exchange rate forecasting markets

The non-existence of triangular arbitrage in an efficient foreign exchange markets is widely believed. In this paper, we deploy a forecasting model to predict foreign exchange rates and apply the triangular arbitrage model to evaluate the possibility of an arbitrage opportunity. Surprisingly, we substantiate the existence of triangular arbitrage opportunities in the exchange rate forecasting market even with transaction costs. This also implies the inefficiency of the market and potential market threats of profit-seeking investors. In our experiments, neural network based model with back-propagation (BP-NN) is used for exchange rate forecasting.

[1]  Phil Mattox,et al.  The stock market , 2002 .

[2]  Jacob A. Frenkel,et al.  Transaction Costs and Interest Arbitrage: Tranquil versus Turbulent Periods , 1977, Journal of Political Economy.

[3]  George Leland Leffler,et al.  The Stock Market , 1957 .

[4]  Naomichi Hatano,et al.  Triangular arbitrage and negative auto-correlation of foreign exchange rates , 2003 .

[5]  F. Mccormick,et al.  Covered Interest Arbitrage: Unexploited Profits? Comment , 1979, Journal of Political Economy.

[6]  Christopher J. Neely,et al.  Intraday Technical Trading in the Foreign Exchange Market , 1999 .

[7]  George E. P. Box,et al.  Time Series Analysis: Forecasting and Control , 1977 .

[8]  Nicholas Sarantis,et al.  On the short-term predictability of exchange rates: A BVAR time-varying parameters approach , 2006 .

[9]  Charles Goodhart,et al.  Every minute counts in financial markets , 1991 .

[10]  Guido Deboeck,et al.  Trading on the Edge: Neural, Genetic, and Fuzzy Systems for Chaotic Financial Markets , 1994 .

[11]  James L. McClelland.  Parallel Distributed Processing , 2005 .

[12]  Kin Keung Lai,et al.  Adaptive Smoothing Neural Networks in Foreign Exchange Rate Forecasting , 2005, International Conference on Computational Science.

[13]  Gwilym M. Jenkins,et al.  Time series analysis, forecasting and control , 1971 .

[14]  Richard K. Lyons,et al.  The Microstructure Approach to Exchange Rates , 2001 .

[15]  Gabjin Oh,et al.  Market efficiency in foreign exchange markets , 2007 .

[16]  Naomichi Hatano,et al.  Triangular arbitrage as an interaction among foreign exchange rates , 2002 .

[17]  Jingtao Yao,et al.  Foreign Exchange Rates Forecasting with Neural NetworksJingtao , 1996 .

[18]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[19]  Mark P. Taylor,et al.  Covered Interest Arbitrage and Market Turbulence , 1989 .

[20]  Mark P. Taylor,et al.  Covered Interest Parity: A High-Frequency, High-Quality Data Study , 1987 .

[21]  Jingtao Yao,et al.  A case study on using neural networks to perform technical forecasting of forex , 2000, Neurocomputing.

[22]  G. Tellis,et al.  The Value of Quality: Stock Market Returns to Reviewed Quality of New Products , 2007 .

[23]  Imad A. Moosa.  Triangular arbitrage in the spot and forward foreign exchange markets , 2001 .

[24]  Naomichi Hatano,et al.  Triangular arbitrage in the foreign exchange market , 2004 .

[25]  K. Clinton.  Transactions Costs and Covered Interest Arbitrage: Theory and Evidence , 1988, Journal of Political Economy.

[26]  Richard M. Levich,et al.  Covered Interest Arbitrage: Unexploited Profits? , 1975, Journal of Political Economy.

[27]  Marios Mavrides.  Triangular Arbitrage in the Foreign Exchange Market: Inefficiencies, Technology, and Investment Opportunities , 1992 .