Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31009
Applications of Conic Optimization and Quadratic Programming in the Investigation of Index Arbitrage in the Thai Derivatives and Equity Markets

Authors: Satjaporn Tungsong, Gun Srijuntongsiri


This research seeks to investigate the frequency and profitability of index arbitrage opportunities involving the SET50 futures, SET50 component stocks, and the ThaiDEX SET50 ETF (ticker symbol: TDEX). In particular, the frequency and profit of arbitrage are measured in the following three arbitrage tests: (1) SET50 futures vs. ThaiDEX SET50 ETF, (2) SET50 futures vs. SET50 component stocks, and (3) ThaiDEX SET50 ETF vs. SET50 component stocks are investigated. For tests (2) and (3), the problems involve conic optimization and quadratic programming as subproblems. This research is first to apply conic optimization and quadratic programming techniques in the context of index arbitrage and is first to investigate such index arbitrage in the Thai equity and derivatives markets. Thus, the contribution of this study is twofold. First, its results would help understand the contribution of the derivatives securities to the efficiency of the Thai markets. Second, the methodology employed in this study can be applied to other geographical markets, with minor adjustments.

Keywords: transaction costs, quadratic programming, Conic optimization, Equity index arbitrage, Executionlags, SET50 index futures, ThaiDEX SET50ETF

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1248


[1] Bae, K.-H., Chan, K. & Cheung, Y.-L. (1998). The profitability of index futures arbitage: Evidence from bid-ask quotes. The Journal of Futures Markets,18, 743-763.
[2] Bolshakova, I. and Kovalev, M., Girlich, E. (2009). Portfolio optimization problems: A survey. Fakultat fur Mathematik working paper.
[3] Chung, P. Y. (1991) A transactions data test of stock index futures market efficiency and index arbitrage profitability. The Journal of Finance, XLVI, 1791-1809.
[4] Cummings, J. R. & Frino, A. (2008) Index arbitrage and the pricing relationship between Australian stock index futures and their underlying shares. 21st Australasian Finance and Banking Conference 2008 proceeding.
[5] Fernando, K. V. Practical portfolio optimization. The Numerical Algorithms Group, Ltd White Paper.
[6] Klemkosky, R. C. & Lee, J. H. (1991) The intraday ex post and ex ante profitability of index arbitrage. The Journal of Futures Markets, 11, 291- 311.
[7] Lobo, M. S., Fazel, M. & Boyd, S. (2007) Portfolio optimization with linear and fixed transaction costs. Annals of Operations Research, 152, 341-365
[8] Neal, R. (1996) Direct tests of index arbitrage models. Journal of Financial and Quantitative Analysis, 31, 541-562.
[9] Richie, N., Daigler R., and Gleason K. (2008) The limits to stock index arbitrage: Examining S&P 500 futures and SPDRS. Journal of Futures Markets, 28(12), 1182-1205.