Quantitative spread trading on crude oil and refined products markets

Quantitative Finance

Volumn 12, Issue 12, 2012, Pages 1857-1875

  Cummins, Mark ^a   Bucca, Andrea ^b  

^a DUBLIN CITY UNIVERSITY   (Ireland)

^b A Glencore Company   (Australia)

Author keywords

Econometrics; Energy derivatives; Quantitative trading strategies; Trading systems

Indexed keywords

EID: 84871233035     PISSN: 14697688     EISSN: 14697696     Source Type: Journal    
DOI: 10.1080/14697688.2012.715749     Document Type: Article

References (51)

1. Aldridge, I. 2009. High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems, Hoboken, NJ: Wiley.
2. Alizadeh, AH and Nomikos, NK. 2004. Cost of carry, causality and arbitrage between oil futures and tanker freight markets. Transport. Res. Part E, 40: 297-316.
3. Andrade, S. di Pietro, V. and Seasholes, M., Understanding the profitability of pairs trading. Working Paper, UC Berkley, 2005
4. Avellaneda, M and Lee, JH. 2010. Statistical arbitrage in the US equities market. Quant. Finance, 10: 761-782.
5. Bertram, WK. 2010. Analytic solutions for optimal statistical arbitrage trading. Physica A, 389: 2234-2243.
6. Bowen, D, Hutchinson, MC and O'Sullivan, N. 2010. High-frequency equity pairs trading: Transaction costs, speed of execution, and patterns in returns. J. Trading, 5: 1-38.
7. Burgess, AN and modelling, A computational methodology for the dynamics of statistical arbitrage. PhD Thesis, London Business School, 1999
8. Burgess, AN. 2000. "Statistical arbitrage models on the FTSE 100". In Computational Finance, Edited by: Abu-Mustafa, Y, LeBaron, B, Lo, AW and Weigend, AS. Cambridge, MA: MIT Press.
9. Crowder, W and Hamed, A. 1993. A cointegration test for oil futures market efficiency. J. Fut. Mkts, 13: 933-941.
10. Cummins, M. 2011. Optimal statistical arbitrage: A model specification analysis on ISEQ equity data. Irish Account. Rev., 17: 21-40.
11. Do, B and Faff, R. Does naïve pairs trading still work? Working Paper, Monash University, 2009
12. Do, B. Faff, R. and Hamza, K., A new approach to modeling and estimation for pairs trading. Working Paper, Monash University, 2006
13. Dunis, CL. Giorgini, G., Laws, J. and Rudy, J., Statistical arbitrage and high-frequency data with an application to Eurostoxx 50 equities. Working Paper, Liverpool Business School, 2010
14. Elliott, RJ, Van der Hoek, J and Malcolm, WP. 2005. Pairs trading. Quant. Finance, 5: 271-276.
15. Gatev, E, Goetzmann, WN and Rouwenhorst, KG. 2006. Pairs trading: Performance of a relative-value arbitrage rule. Rev. Financ. Stud., 19: 797-827.
16. Gilbert, CL. Commodity speculation and commodity investment. Working Paper, Universita Degli Studi di Trento, 2008
17. Girma, PB and Paulson, AS. 1999. Risk arbitrage opportunities in petroleum futures spreads. J. Fut. Mkts, 19: 931-955.
18. Gjolberg, O and Johnsen, T. 1999. Risk management in the oil industry: Can information on long-run equilibrium prices be utilized?. Energy Econ., 21: 517-527.
19. Gregeriou, GN, Huber, G and Kooli, M. 2009. Performance and persistence of commodity trading advisors: Further evidence. J. Fut. Mkts, 30: 725-752.
20. Hansen, PR. 2005. A test for superior predictive ability. J. Bus. Econ. Statist., 23: 365-380.
21. Hogan, S, Jarrow, R, Teo, R and Warachka, M. 2004. Testing marking efficiency using statistical arbitrage with applications to momentum and value strategies. J. Financ. Econ., 73: 525-565.
22. Hsu, PH and Kuan, CM. Re-examining the profitability of technical analysis with White's reality check. Working Paper, 2005
23. Hsu, PH. Hsu, Y.C. and Kuan, C.M., Testing the predictive ability of technical analysis using a new stepwise test without data snooping bias. Working Paper, 2009
24. Kaldor, N. 1939. Speculation and economic stability. Rev. Econ. Stud., 7: 1-27.
25. Kanamura, T, Rachev, ST and Fabozzi, FJ. 2010. A profit model for spread trading with an application to energy futures. J. Trading, 5: 48-62.
26. Kavussanos, MG and Alizadeh, A. 2002. The expectations hypothesis of the term structure and risk premia in dry bulk shipping freight markets. J. Transp. Econ. Policy, 36: 267-304.
27. Kellard, N, Newbold, P, Rayner, A and Ennew, C. 1999. The relative efficiency of commodity futures markets. J. Fut. Mkts, 19: 413-432.
28. Kinnear, K. The Brent WTI arbitrage: Linking the world's key crudes. Working Paper, 2002
29. Laws, J. Dunis, C.L. and Evans, B., Trading and filtering futures spread portfolios: Futher applications of threshold and correlation lters. Working Paper, 2008
30. Lin, Y, McRae, M and Gulati, C. 2006. Loss protection in pairs trading through minimum profit bounds: A cointegration approach. J. Appl. Math. Decis. Sci., 6: 1-14.
31. Marshall, BR. Cahan, R.H. and Cahan, J.M., Can commodity futures be protably traded with quantitative market timing strategies? Working Paper, 2008
32. Mou, Y. Limits to arbitrage and commodity index investment: Front-running the Goldman roll. Working Paper, 2010
33. Papadakis, G and Wysocki, P. Pairs trading and accounting information. Working Paper, 2007
34. Park, CH and Irwin, SH. 2007. What do we know about the profitability of technical analysis?. J. Econ. Surv., 21: 786-826.
35. Qui, M and Wu, Y. 2006. Technical trading-rule profitability, data snooping, and reality check: Evidence from the foreign exchange market. J. Money, Credit, Bank., 38: 2135-2158.
36. Ricciardi, LM and Sato, S. 1988. First-passage-time density and moments of the Ornstein-Uhlenbeck process. J. Appl. Probab., 25: 43-57.
37. Romano, JP. Shaikh, A.M. and Wolf, M., Hypothesis testing in econometrics. Working Paper, 2009
38. Romano, JP and Wolf, M. 2007. Control of generalized error rates in multiple testing. Ann. Statist., 35: 1378-1408.
39. Romano, JP and Wolf, M. 2010. Balanced control of generalized error rates. Ann. Statist., 38: 598-633.
40. Sarr, A and Lybek, T. Measuring liquidity in financial markets. Working Paper, 2002
41. Sato, S. 1977. Evaluation of the first-passage time probability to a square root boundary for the Wiener process. J. Appl. Probab., 14: 850-856.
42. Schwarz, TV and Szakmary, AC. 1994. Price discovery in petroleum markets: Arbitrage cointegration and the time interval of analysis. J. Fut. Mkts, 14: 147-167.
43. Shleifer, A and Vishny, R. 1997. The limits of arbitrage. J. Finance, 52: 35-55.
44. Silvapulle, P and Moosa, I. 1999. The relationship between spot and futures prices: Evidence from the crude oil market. J. Fut. Mkts, 19: 175-193.
45. Sullivan, R, Timmermann, A and White, H. 1999. Data-snooping, technical trading rule performance, and the bootstrap. J. Finance, 54: 1647-1691.
46. Thomas, MU. 1975. Some mean first-passage time approximations for the Ornstein-Uhlenbeck process. J. Appl. Probab., 12: 600-604.
47. Trapletti, A, Geyer, A and Leisch, F. 2002. Forecasting exchange rates using cointegration models and intraday data. J. Forecast., 21: 151-166.
48. Vasicek, OA. 1977. An equilibrium characterization of the term structure. J. Forecast., 5: 177-188.
49. Vidyamurthy, G. 2004. Pairs Trading: Quantitative Methods and Analysis, Hoboken, NJ: Wiley.
50. Whistler, M. 2004. Trading Pairs: Capturing Profits and Hedging Risk with Statistical Arbitrage Strategies, Hoboken, NJ: Wiley.
51. White, H. 2000. A reality check for data snooping. Econometrica, 68: 1097-1126.