Research Literature on Cointegration and Pairs Trading

# Looking for materials regarding Pair Trading


# Looking for materials regarding Pair Trading












For my master thesis, I wish to work onto Cointegration and Pair Trading. I was wondering if any of you had some scholar/blog material recommendations.

Best Regards

## Answer by Artem Korol (score 7)

https://quant.stackexchange.com/a/31970

Here is a literature list from my masters thesis on stat arb.

> Lederman, J., (1996). Market Neutral: Long/Short Strategies for Every Market Environment, 2. – 3. lpp. Gatev, E., Goetzman, W. N., Rouwenhorst, K. G. (1999). Pairs Trading: Performance of a Relative Value Arbitrage Rule, Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 19(3), pp 797-827. doi:10.1093/rfs/hhj020 Vidyamurthy, G., (2004). Pairs Trading: Quantitative Methods and Analysis, 75. – 79. lpp. Avellaneda, M., Lee, J.-H. (2008). Statistical arbitrage in the US equities market. Quantitative Finance, 10(7): pp 761 - 782. Chan, E., (2013). Algorithmic Trading: Winning Strategies and Their Rationale, 42. – 78. lpp. Drakos, S. (2016) Statistical Arbitrage in S&P500. Journal of Mathematical Finance, 6, pp 166-177. dx.doi.org/10.4236/jmf.2016.61016 Chen, Y., Ren, W., Lu, X., (2015). Machine Learning in Pairs Trading Strategies, 1. – 5. lpp. Wenbin, Z., Zhen, D., Bindu, P., Milan, D., (2014). A Multi-factor adaptive statistical arbitrage model, 2. – 3. lpp. Bogomolov, T., (2010). Pairs trading in the land down under. Finance and Corporate Governance Conference. 13. – 14. lpp. Do, B., Faff, R., (2012). Are pairs trading profits robust to trading costs?. Journal of Financial Research, 35(2): pp 261–287. doi: 10.1111/j.1475-6803.2012.01317.x Kristoufek, L., Vosvarda, M., (2013). Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy. The European Physical Journal B July 2014, pp. 87-162. Kristoufek, L., Vosvarda, M., (2012). Measuring capital market efficiency: Global and local correlations structure. Physica A: Statistical Mechanics and its Applications. Volume 392, Issue 1, 1 January 2013, pp 184–193. doi:10.1016/j.physa.2012.08.00373 Boehemer, E., Fong, K., Wu, J., (2015). International Evidence on Algorithmic Trading, 7. – 8. lpp. Hendershott, T., Riordan, R., (2011). High Frequency Trading and Price Discovery. Manuscript, University of California, Berkeley, 6. – 7. lpp. Lamont, A., Thaler, R., (2003). Anomalies: The Law of One Price in Financial Markets. Journal of Economic Perspectives, 17(4): pp 191-202. doi: 10.1257/089533003772034952 Do, B., Fa, R., Hamza, K. (2006). A new approach to modeling and estimation for pairs trading. In Proceedings of 2006 Financial Management Association European Conference. 3. – 4. lpp. Gatev, E., Goetzmann, W. N., Rouwenhorst, K. G. (2006). Pairs trading: Performance of a relative-value arbitrage rule. Review of Financial Studies, 19(3): pp 797 - 827. Krauss, C., (2015). Statistical arbitrage pairs trading strategies: Review and outlook, IWQW Discussion Paper Series, No. 09/2015. 5. – 8. lpp. Engle, R. F., Granger, C. W. J., (1987). Co-Integration and error correction: Representation, estimation, and testing. Econometrica, 55(2): pp 251-276. Do, B., Faff, R., (2010). Does Simple Pairs Trading Still Work?. Financial Analysts Journal, 66(4): pp 83–95. doi: http://dx.doi.org/10.2469/faj.v66.n4.1 Huck, N. (2015). Pairs trading: does volatility timing matter? Applied Economics, pp 1-18. Huck, N. and Afawubo, K. (2015). Pairs trading and selection methods: is cointegration superior? Applied Economics, 47(6): pp 599-613. Johansen, S., (1988). Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control, 12(2-3): pp 231-254. Lim, V., Martin, L., (1995). Regression‐based cointegration estimators with applications. Journal of Economic Studies, 22 (1), pp 3 – 22. 74 Odelson, BJ., Rajamani, MR., Rawlings JB., (2006). A new autocovariance least-squares method for estimating noise covariances. Automatica 42 (2), pp. 303-308. Rajamani, MR., Rawlings JB., (2009). Estimation of the disturbance structure from data using semidefinite programming and optimal weighting. Automatica 45 (1), pp. 142-148. Bentz, Y. (2003), Quantitative Equity Investment Management with Time- Varying Factor Sensitivities. Applied Quantitative Methods for Trading and Investment. John Wiley & Sons, Chichester, 213. - 237. lpp. Bogomolov, T. (2013). Pairs trading based on statistical variability of the spread process. Quantitative Finance, 13(9): pp. 1411 - 1430. Mudchanatongsuk, S., Primbs, J. A., Wong, W. (2008). Optimal pairs trading: A stochastic control approach. In American Control Conference, 2008, pp 1035 – 1039. Boguslavsky, M., Boguslavskaya, E. (2004). Arbitrage under power. Risk, 17(6): pp. 69 - 73. Chen, H., Chen, S. J., Li, F. (2012). Empirical investigation of an equity pairs trading strategy. 5. - 7. lpp. Pole, A. (2008). Statistical arbitrage: algorithmic trading insights and techniques. John Wiley & Sons, Hoboken, N.J. 105. - 106. lpp. Bowen, D. A., Hutchinson, M. C. (2014). Pairs trading in the UK equity market: Risk and return. The European Journal of Finance, 0(0): pp 1 - 25. Frank, N. (2009). Linkages between asset classes during the financial crisis, accounting for market microstructure noise and non-synchronous trading, Economics Series Working Papers 2009-W04, University of Oxford, Department of Economics. 26. – 30. lpp. Manda K., (2010). Stock Market Volatility during the 2008 Financial Crisis. The Leonard N. Stern School of Business Glucksman Institute for Research in Securities Markets. 13. – 24. lpp. Sandoval L., Franca I., (2011). Correlation of financial markets in times of crisis. Insper, Instituto de Ensino e Pesquisa. 15. – 17. lpp. 75 Perlin, M. S. (2009). Evaluation of pairs-trading strategy at the Brazilian financial market. Journal of Derivatives & Hedge Funds, 15(2): pp. 122 - 136. Rudy J., (2011). Four essays in statistical arbitrage in equity markets. Liverpool John Moores University. 15. – 17. Lpp. Mori, M., Ziobrowski, A. J., (2011). Performance of pairs trading strategy in the U.S. REIT market. Real Estate Economics, 39(3): pp. 409 - 428. Puspaningrum, H. (2012). Pairs trading using cointegration approach. University of Wollongong. 31. – 33. lpp. Lin, Y.-X. McCrae,. M., Gulati, C. (2006). Loss protecetion in pairs trading through minimum profit bounds: A cointegration approach. Journal of Applied Mathematics and Decision Sciences, 2006: pp 1-14. dx.doi.org/10.1155/JAMDS/2006/73803 Bee M., Gatti G., (2015). An improved pairs trading strategy based on switching regime volatility, DEM Discussion Papers 2015/13. 10. – 14. lpp. Grima, P., Paulson, A. (1999). Risk arbitrage opportunities in petroleum futures spreads. Journal of Futures markets (19): pp 931-955 Dolatabadi S., Nielsen, M., Xu K., (2015). A fractionally cointegrated VAR analysis of price discovery in commodity futures markets. Journal of Futures Markets, 35(4): pp. 339 – 356. Broumandi, S., Reuber, T., (2012). Statistical arbitrage and FX exposure with South American ADRs listed on the NYSE. Financial Assets and Investing, 3(2): pp. 5 - 18. Hong, G. and Susmel, R. (2003). Pairs-trading in the Asian ADR market. Working paper, University of Houston. 9. – 11. lpp. Coldeira, J. F., Moura, G. V. (2013). Selection of a portfolio of pairs based on cointegration: A statistical arbitrage strategy. Brazilian Review of Finance, 11(1): pp. 49 - 80. Dunis, C. L., Giorgioni, G., Laws, J., Rudy, J. (2010). Statistical arbitrage and high-frequency data with an application to Eurostoxx 50 equities. Working paper, Liverpool Business School. 12. lpp. 76 Dunis, C. L., Ho, R. (2005). Cointegration portfolios of European equities for index tracking and market neutral strategies. Journal of Asset Management, 6(1): pp 33 - 52. Alexander C., Dimitriu A., (2002). The cointegration alpha: enhanced index tracking and long–short market neutral strategies. 10. lpp. Karakas, O. (2009). Mean reversion between different classes of shares in dual-class firms: Evidence and implications. Working paper, London Business School. 10. – 12. lpp. Morse D., Ushman N., (1983). The Effect of Information Announcements on the Market Microstructure. The Accounting Review 58 (2): pp. 247-258. Park, J., 1995, A market microstructure explanation for predictable variations in stock returns following large price changes, Journal of Financial and Quantitative Analysis (30): pp. 241-256. Alexander, C. (1999). Optimal hedging using cointegration. Philosophical Transactions: Mathematical, Physical and Engineering Sciences, 357(1758): pp 2039 - 2058. Bruno C., Caldeira F., Guilherme M., (2014). Is Pairs Trading Performance Sensitive to the Methodologies?: A Comparison. 16. lpp. Montana, G., Triantafyllopoulos, K., Tsagaris, T. (2009). Flexible least squares for temporal data mining and statistical arbitrage. Expert Systems with Applications, 36(2): pp 2819 - 2830. Aldridge, I. (2009). High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems, 2nd Edition. 131. - 144. lpp Kim, K. (2011). Performance analysis of pairs trading strategy utilizing high frequency data with an application to KOSPI 100 equities. SSRN Electronic Journal. 6. - 10. lpp Bogomolov, T. (2011). Pairs trading in the land down under. In Finance and Corporate Governance Conference. 11. - 12. lpp Pastukhov S., (2005). On Some Probabilistic-Statistical Methods in Technical Analysis. Theory of Probability & Its Applications, 49 (2): pp 245–260. 77 Mudchanatongsuk, S., Primbs, J. A., Wong, W. (2008). Optimal pairs trading: A stochastic control approach. In American Control Conference, 2008, pp 1035 - 1039. Patro K., (2001). Measuring performance of international closed-end funds. Journal of Banking & Finance. 25(9): pp 1741 – 1767. doi:10.1016/S0378-4266(00)00151-5 Infantino, Leandro R., Itzhaki S., (2010). Developing high-frequency equities trading models. Sloan School of Management. 41. – 52. lpp. Blokker J., Chamoun E., Jreige I., Georgoudis, P., Galal, S., (2010). Statistical Arbitrage. 5. – 8. lpp. Platania D., (2015). Valuation of derivative assets under cyclical mean-reversion processes for spot prices. 26. – 30. lpp. Lund, J., (1999). Model for Studying the Effect of EMU on European Yield Curves. European Finance Review, (2): pp 321 – 363. Ruiter H., J., (2009). The Performance of a Pairs Trading Strategy in Asian Markets for 2002 to 2009. 16. – 26. lpp Fama, E. F. (1965a), Random walks in stock market prices, Financial Analysts Journal, 21(5): pp. 55 – 59. Chong, T., T.-H. Lam, I. Yan (2011). Is the Chinese stock market really ineficient? China Economic Review 23(1): pp. 122-137. Lim, K.-P., R. Brooks, J. Kim (2008). Financial crisis and stock market eciency: Empirical evidence from Asian countries. International Review of Financial Analysis 17: pp 571 - 591. Alexeev, V., Tapon. F., (2011). Testing weak form efficiency on the Toronto Stock Exchange. Journal of Empirical Finance 18: pp. 661 - 691. Barunik, J., T. Aste, T. Di Matteo, Liu R., (2012). Understanding the source of multifractality in financial markets. Physica A 391, pp. 4234 - 4251. 78 Cajueiro, D., B. Tabak (2004a). Evidence of long range dependence in Asian equity markets: the role of liquidity and market restrictions. Physica A 342: pp 656 - 664. Vandewalle, N., Ausloos M.,, Boveroux P., (1997). Detrended Fluctuation Analysis of the Foreign Exchange Market. 46. – 48. lpp. Barkoulas, J., Baum C. (1996). Long-term dependence in stock returns. Economics Letters 53, pp. 253 - 259. Matteo, D., Aste, T., Dacorogna, M.,(2005). Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development. Journal of Banking & Finance 29: pp. 827 - 851. Gneiting, T., Schlather, M., (2004). Stochastic Models That Separate Fractal Dimension and the Hurst Effect. SIAM Review 46(2):, pp. 269 – 282. Pincus S., M., (1991). Approximate entropy as a measure of system complexity. PNAS 88 (6): pp. 2297–2301, doi: 10.1073/pnas.88.6.2297 Bhattacharya, Bhattacharya, (2012). Long Memory in Stock Returns: A Study of Emerging Markets. Iranian Journal of Management Studies 5 (2): pp 66 – 88.