Perlin, M. (2007): M of a kind: A Multivariate Approach at Pairs Trading.
Download (186kB) | Preview
Pairs trading is a popular trading strategy that tries to take advantage of market inefficiencies in order to obtain profit. Such approach, on its classical formulation, uses information of only two stocks (a stock and its pairs) in the formation of the trading signals. The objective of this paper is to suggest a multivariate version of pairs trading, which will try to create an artificial pair for a particular stock based on the information of m assets, instead of just one. The performance of three different versions of the multivariate approach was assessed for the Brazilian financial market using daily data from 2000 to 2006 for 57 assets. Considering realistic transaction costs, the analysis of performance was conducted with the calculation of raw and excessive returns, beta and alpha calculation, and the use of bootstrap methods for comparing performance indicators against portfolios build with random trading signals. The main conclusion of the paper is that the proposed version was able to beat the benchmark returns and random portfolios for the majority of the parameters. The performance is also found superior to the classic version of the strategy, Perlin (2006b). Another information derived from the research is that the proposed strategy picks up volatility from the data, that is, the annualized standard deviations of the returns are quite high. But, such event is “paid” by high positive returns at the long and short positions. This result is also supported by the positive annualized sharpe ratios presented by the strategy. Regarding systematic risk, the results showed that the proposed strategy does have a statistically significant beta, but it isn’t high in value, meaning that the relationship between return and risk for the trading rules is still attractive.
|Item Type:||MPRA Paper|
|Original Title:||M of a kind: A Multivariate Approach at Pairs Trading|
|Keywords:||pairs trading, asset allocation, quantitative strategy|
|Subjects:||C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C10 - General
G - Financial Economics > G1 - General Financial Markets > G11 - Portfolio Choice ; Investment Decisions
|Depositing User:||Marcelo Perlin|
|Date Deposited:||17. Apr 2008 17:09|
|Last Modified:||12. Feb 2013 21:26|
ALEXANDER, C., DIMITRIU, A (2000) ‘The Cointegration Alpha: Enhanced Index Tracking and Long-Short Market Strategies’ ICMA Discussion Paper in Finance.
ALMEIDA, N., M., PEREIRA, P., V. (2000) ‘Mudança de regime para séries financeiras: Um estudo empírico destes modelos para a realização de regras de mercado’ Finance Lab Working Paper, n. 03.
BROOKS, C., KATSARIS, A., PERSAND, G. (2005) ‘Timing is Everything: A Comparison and Evaluation of Market Timing Strategies’ Working Paper, Available at SSRN: http://ssrn.com/abstract=834485.
CARVALHAL DA SILVA, A. L., RIBEIRO, T. L. (2002) ‘Estimating and Forecasting Latin American Indexes Using Artificial Neural Networks’ Proceedings of BALAS.
CHEN, A., LEUNG, M. T., DAOUK, H. (2003) ‘Application of Neural Networks to an Emerging Financial Market: Forecasting and Trading the Taiwan Stock Index’ Computers & Operations Research, v. 30, p. 901–923.
DIMSON, E., MUSSAVIAN, M. (1998) ‘A brief history of market efficiency’ European Financial Management, v. 4, p. 91-193.
DUEKER, M. J., NEELY, C. J. (2006) ‘Can Markov Switching Models Predict Excess Foreign Exchange Returns?’ Working Paper, Federal Reserve Bank of St. Louis.
EFETKHARI, B. (1997) ‘The Markov Regime Switching model as Trading Tool’ Working Paper, University of Cambridge. FAMA, E. (1991) ‘Efficient Capital Markets: II’ Journal of Finance, v. 46, p. 1575-1617.
FAMA, E., FRENCH, K. (1992) ‘The cross-section of expected stock returns’ Journal of Finance, v. 47 (2), p. 427-465.
FERNÁNDEZ-RODRÍGUEZ, F., RIVERO, S. S., FELIX, J. A. (2002) ‘Nearest Neighbor Predictions in Foreign Exchange Markets’ Working Paper, n. 05, FEDEA.
FERNÁNDEZ-RODRÍGUEZ, F., SOSVILLA-RIVERO, S., GARCÍA-ARTILES, M. (1997) ‘Using nearest neighbor predictors to forecast the Spanish Stock Market’ Investigaciones Económicas, v. 21, p. 75-91.
FERNÁNDEZ-RODRÍGUEZ, F., SOSVILLA-RIVERO, S., GARCÍA-ARTILES, M. (2001) ‘An empirical evaluation of non-linear trading rules’ Working paper, n. 16, FEDEA.
FRENCH, K. (1980) ‘Stock Returns and the Weekend Effect’ Journal of Financial Economics, March, p. 55-69.
GATEV, E., GOETZMANN, W. N., ROUWENHORST, K. G. (1999) ‘Pairs Trading: Performance of a Relative Value Arbitrage Rule’ Working Paper, Yale School of Management. Available at SSRN: http://ssrn.com/abstract=141615.
MADDALA, G. S. (2001) ‘Introduction to Econometrics’ John Wiley & Sons.
MURPHY, J. (2001) ‘Technical Analysis of the Financial Markets’. New York Institute of Finance.
PARK, C., IRWIN. (2004) ‘The Profitability of Technical Analysis: A Review’. AgMAS Project Research Report, n 04.
PERLIN, M S. (2006b) Evaluation of Pairs Trading Strategy at Brazilian Financial Market, Working Paper, http://ssrn.com/abstract=952242.
PERLIN, M. S. (2006a) ‘Non Parametric Modelling in Major Latin America Market Indexes: An Analysis of the Performance from the Nearest Neighbor Algorithm in Trading Strategies’. BALAS Conference, Lima, Peru.
VIDYAMURTHY, G. (2004) ‘Pairs Trading: Quantitative Methods and Analysis’ John Wiley & Sons, 2004.
NATH, P. (2003) ‘High Frequency Pairs Trading with U.S. Treasury Securities: Risks and Rewards for Hedge Funds’, Working Paper, London Business School.
GATEV, E., GOETZMANN, W. N., ROUWENHORST, K. G. (1999) ‘Pairs Trading: Performance of a Relative Value Arbitrage Rule’, Working Paper, Yale School of Management. Available at SSRN: http://ssrn.com/abstract=141615.