A Cointegration Approach for Selection of Currency Pairs
DOI:
https://doi.org/10.17010/ijf/2021/v15i12/160018Keywords:
Forex Market
, Currency, Pairs Trading, Cointegration.JEL Classification Codes
, C32, G11, G15.Paper Submission Date
, April 10, 2021, Paper Sent Back for Revision, November 20, Paper Acceptance Date, November 30, Paper Published Online, December 15, 2021.Abstract
Pairs trading is a statistical arbitrage strategy based on the construction of mean reversion in prices of securities. While these strategies tend to perform well in equities, their effectiveness and performance in the currency market is yet to be tested, which is generally inefficient and predictable. The purpose of this study was to select the pairs for pairs trading in the forex market of select currencies: EUR/USD, GBP/USD, USD/CAD, USD/INR, USD/JPY, and USD/NZD during the period starting from October 1, 2010 – October 20, 2020. The research was organized into three parts to determine the possible pairs of six currencies over different time periods. First, the closeness of potential pairs of six currencies was established using the distance approach for 10 years, 5 years, and 2 years. After that, the Engle – Granger two-step test for cointegration was applied to examine the validity of the top 10 closest pairs of currencies for pairs trading in the study. Based on the empirical results of the cointegration approach, we found very few good pairs in the forex market in our study. USD_INR/USD_NZD was found to be statistically significant at a 10% level of significance over the 10-year sample period, and the same pair of currencies was also found to be statistically significant over a 5-year sample period, but this pair was not found to be statistically significant in the 2-year sample period; whereas, USD_JPY/USD_NZD was found to be statistically significant in the 2 - year period at a 10% level of significance.Downloads
Downloads
Published
How to Cite
Issue
Section
References
Aggarwal, G., & Aggarwal, N. (2020). Risk-adjusted returns from statistical arbitrage opportunities in Indian stock futures market. Asia-Pacific Financial Markets, 28, 79 – 99. https://doi.org/10.1007/s10690-020-09317-1
Avellaneda, M., & Lee, J.-H. (2010). Statistical arbitrage in the US equities market. Quantitative Finance, 10(7), 761–782. https://doi.org/10.1080/14697680903124632
Bowen, D. A., & Hutchinson, M. C. (2014). Pairs trading in the UK equity market: Risk and return. The European Journal of Finance, 22(14), 1363–1387. https://doi.org/10.1080/1351847X.2014.953698
Brooks, C. (2008). Introductory econometrics for finance. Cambridge University Press.
Broussard, J. P., & Vaihekoski, M. (2012). Profitability of pairs trading strategy in an illiquid market with multiple share classes. Journal of International Financial Markets, Institutions and Money, 22(5), 1188 – 1201.https://doi.org/10.1016/j.intfin.2012.06.002
Burgess, A. N. (1999). A computational methodology for modelling the dynamics of statistical arbitrage (PhD Thesis). University of London, London Business School.
Chen, D., Cui, J., Gao, Y., & Wu, L. (2017). Pairs trading in Chinese commodity futures markets: An adaptive cointegration approach. Accounting & Finance, 57(5), 1237–1264. https://doi.org/10.1111/acfi.12335
Chen, H., Chen, S., Chen, Z., & Li, F. (2009). Empirical investigation of an equity pairs trading strategy. Management Science, 65(1), 370 – 389. https://doi.org/10.1287/mnsc.2017.2825
Cheng, X., Yu, P. L., & Li, W. K. (2011). Basket trading under cointegration with the logistic mixture autoregressive model. Quantitative Finance, 11(9), 1407–1419. https://doi.org/10.1080/14697688.2010.506445
Clegg, M., & Krauss, C. (2018). Pairs trading with partial cointegration. Quantitative Finance, 18(1), 121–138. https://doi.org/10.1080/14697688.2017.1370122
Cohen, L., & Frazzini, A. (2008). Economic links and predictable returns. The Journal of Finance, 63(4), 1977–2011. https://doi.org/10.1111/j.1540-6261.2008.01379.x
Cummins, M., & Bucca, A. (2012). Quantitative spread trading on crude oil and refined products markets. Quantitative Finance, 12(12), 1857–1875. https://doi.org/10.1080/14697688.2012.715749
Dadhich, G., Chotia, V., & Chaudhry, O. (2015). Impact of foreign institutional investments on stock market volatility in India. Indian Journal of Finance, 9(10), 22–35. https://doi.org/10.17010/ijf/2015/v9i10/79561 14) De, S., & Chakraborty, T. (2015). Foreign portfolio investment and stock market volatility in India. Indian Journal of Finance, 9(1), 49 – 59. https://doi.org/10.17010/ijf/2015/v9i1/71535
Do, B., & Faff, R. (2012). Are pairs trading profits robust to trading costs? The Journal of Financial Research, 35(2), 261 – 287. https://doi.org/10.1111/j.1475-6803.2012.01317.x
Do, B., & Faff, R. (2018). Does simple pairs trading still work? Financial Analysts Journal, 66(4), 83–95. https://doi.org/10.2469/faj.v66.n4.1
Enders, W. (2010). Applied econometric time series (3rd ed.). John Wiley & Sons.
Engle, R. F., & Granger, C. W. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. https://doi.org/10.2307/1913236
Gatarek, L. T., Hoogerheide, L. F., Van Dijk, H. K. (2011). A simulation-based Bayes’ procedure for robust prediction of pairs trading strategies. Tinbergen Institute Discussion Paper, 09–061.
Gatarek, L. T., Hoogerheide, L. F., & Van Dijk, H. K. (2014). Return and risk of pairs trading using a simulation-based Bayesian procedure for predicting stable ratios of stock prices. SSRN Electronic Journal. http://dx.doi.org/10.2139/ssrn.2412455
Gatev, E., Goetzmann, W. N., & Rouwenhorst, K. G. (2006). Pairs trading: Performance of a relative-value arbitrage rule. The Review of Financial Studies, 19(3), 797–827. https://doi.org/10.1093/rfs/hhj020
Hong, G., & Susmel, R. (2003). Pairs-trading in the Asian ADR market (Working Paper). The University of Houston. https://doi.org/10.1093/rfs/hhj020
Huck, N., & Afawubo, K. (2015). Pairs trading and selection methods: Is cointegration superior? Applied Economics, 47(6), 599–613. https://doi.org/10.1080/00036846.2014.975417
Karakas, O. (2009). Mean reversion between different classes of shares in dual-class firms: Evidence and implications (Working Paper). London Business School.
Khuntia, S. P., & Jamini, K. (2017). Dynamics of Indian foreign exchange market efficiency: An adaptive market hypothesis approach. Indian Journal of Finance, 11(9), 39–52. https://doi.org/10.17010/ijf/2017/v11i9/118088
Liu, S.-M., & Chou, C.-H. (2003). Parities and spread trading in gold and silver markets: A fractional cointegration analysis. Applied Financial Economics, 13(12), 899–911. https://doi.org/10.1080/0960310032000129626
Puspaningrum, H. (2012). Pairs trading using cointegration approach (PhD Thesis). The University of Wollongong.
Ramos-Requena, J. P., Trinidad-Segovia, J. E., & Sánchez-Granero, M. Ã. (2020a). Some notes on the formation of a pair in pairs trading. Mathematics, 8(3), 348. https://doi.org/10.3390/math8030348
Ramos-Requena, J.P., Trinidad-Segovia, J.E., & Sánchez-Granero, M.Ã. (2020b). An alternative approach to measure comovement between two time series. Mathematics, 8(2), 261. https://doi.org/10.3390/math8020261
Tokat, E., & HayrullahoÄŸlu, A. C. (2021). Pairs trading: Is it applicable to exchange-traded funds? Borsa Istanbul Review. https://doi.org/10.1016/j.bir.2021.08.001
Tsay, R. S. (2010). Analysis of financial time series. Wiley series in probability and statistics (3rd edition). John Wiley & Sons.
Vidyamurthy, G. (2004). Pairs trading: Quantitative methods and analysis. John Wiley & Sons.
Yadav, S. (2016). Integration of exchange rate and stock market: Evidence from the Indian stock market. Indian Journal of Finance, 10(10), 56–63. https://doi.org/10.17010/ijf/2016/v10i10/103015
