This document summarizes research on applying a threshold cointegration pair trading strategy to pairs of assets in the Thai stock and futures markets. The research finds cointegrating relationships between 3 pairs - SET50 spot and futures, KTB spot and futures, and TRUE spot and futures. A threshold vector error correction model is used to formulate pair trading rules. Backtesting shows the threshold cointegration strategy generates higher profits than a traditional pair trading strategy based on 2 standard deviation bands. However, low futures trading volumes currently limit the attractiveness of using pair trading in Thailand.

1. University Logo
2.18 * 3.37 cm
Research Papers by College of Management, Mahidol University
“Statistical Arbitrage in SET and TFEX : Pair Trading Strategy
from Threshold Co-integration Model”
The 2014 Capital Market Research Scholarship
for Graduate Students
By
Surasak Choedpasuporn, Master Degree
Piyapas Tharavanij, Ph.D. & Assoc.Prof. Tatre Jantarakolico, Ph.D., Research Advisors
20 February 2015

2. Research Objectives
& Benefit for Thai Capital Market
• How does a future price relate to its underlying asset and another series from the
same underlying asset.
• Is Pair-Trading Strategy profitable in Thailand Stock & Futures Market
• How can we improve the pair trading strategy
• How attractive to use the pair trading strategy in Thailand Stock & Futures Market
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3. Executive Summary
• Study 5-minutes intraday price relationship between pairs of assets in SET and
TFEX.
• 3 pairs of series of the same underlying asset (SET50, KTB, TRUE) which trade
between 2/Jul/14 – 29/Aug/14 are studied.
• Found long-run relationship and short-run dynamic of the prices of pairs.
• With the existence of the transaction cost, the price relationship is estimated
following the Threshold Vector Error Correction Model (TVECM)
• TVECM pair trading strategy is formulated. The performance of the TVECM pair
trading strategy is superior to the traditional pair trading strategy.
• Present amount of trading volume in TFEX is too low to be attractive applying the
pair trading strategy.
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4. Pair Trading Strategy
– Market Neutral (Profitable in any market condition)
– Choose a pair of highly correlated price securities
• When the pair diverges, open ‘Short’ position in outperforming one and
‘Long’ position in underperforming one.
• When the pair converges, close all positions
Open ‘Short’ position
Open ‘Long’ position
Close both positions
4Traditional Pair Trading uses Moving Average 2 S.D. as positioning signal

5. Threshold Co-integration Pair Trading Strategy
• Threshold Vector Error Correction Model (TVECM )
– With existence of Transaction Cost (ex.Commission), the Adjustment Process
could be Asymmetric.
– In different regime, speed of adjustment might be different.
“No-arbitrage band”
If the mispricing is too small to
cover the transaction cost.
Then, adjustment speed might be
small.
Regime 3
Regime 1
Regime 2
Speed of adjustment : High
Speed of adjustment : Low
Speed of adjustment : Zero
Upper
Threshold
Lower
Threshold
Mispricing

6. 6
Threshold Co-integration Pair Trading Strategy
-0.001
-0.0008
-0.0006
-0.0004
-0.0002
0
0.0002
0.0004
ECT
LowThr
UpThr
Regime 3
Regime 1
Regime 2
Data : S50U14 & S50Z14 (freq : 5mins)
Example of Threshold Co-integration Behavior

7. TVECM Pair Trading 1
Regime 3
Regime 1
Regime 2
Open
Positions Type 1
Positions Type 1 – Short Asset 1 & Long Asset 2
Positions Type 2 – Long Asset 1 & Short Asset 2
Close
Positions
Open
Positions Type 2
Trading Rule 1
Close
Positions

8. Trading Rule
Regime 3
Regime 1
Regime 2
Open
Positions Type 1
Positions Type 1 – Short Asset 1 & Long Asset 2
Positions Type 2 – Long Asset 1 & Short Asset 2
Close Positions Type 1
& open Positions Type 2
Trading Rule 2

9. Performance Measurement
• Time-rolling (Out-sample Test)
1) Set Training Period = 600 periods (10 trading days) to estimate threshold values
2) Execute trading rule for next 300 periods (5 trading days)
3) Move forward 300 periods, redo steps 1) & 2) and repeat until end of data
9
Time-rolling#1
Training Period Execute Period
Apply
Time Rolling#1’s
Parameters
Time-rolling#2
Move forward
300 periods
Training Period Execute Period
Apply
Time Rolling#2’s
Parameters

10. Data
• Data selection criteria
– Asset from SET and TFEX markets
– Pair Formulate
• Spot and its future
• 2 different contract month futures from same underlying asset
– Data Frequency : 5 mins
– Missing data (no trade) < 10%
• Selected Data & Pairs (Trading period : 2/Jul/14 – 29/Aug/14 (2,439 Obs))
– Pair 1 - Assets : S50U14 & S50Z14
– Pair 2 - Assets : KTB & KTBU14
– Pair 3 - Assets : TRUE & TRUEU14
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11. Empirical Results
(Compare training & execute period)
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Trading Rule
Pair 1
(S50U14 & S50Z14)
200 stocks / contract
Pair 2
(KTB & KTBU14)
1,000 stocks / contract
Pair 3
(TRUE & TRUEU14)
1,000 stocks / contract
Training : 600
Execute : 300
Training : 300
Execute : 60
Training : 600
Execute : 300
Training : 300
Execute : 60
Training : 600
Execute : 300
Training : 300
Execute : 60
Trading Rule
1
*No. of
Transactions
132 152 192 226 160 196
Gross Profit 3,820 5,100 7,660 9,890 6,076 6,852
**Transaction
Cost
1,848 2,128 7,182 8,453 5,774 7,073
Net Profit 1,972 2,972 478 1,437 302 (-221)
Trading Rule
2
*No. of
Transactions
82 86 124 178 128 136
Gross Profit 2,940 3,100 5,280 8,750 5,585 5,820
**Transaction
Cost
1,148 1,204 4,641 6,658 4,620 4,908
Net Profit 1,792 1,896 639 2,092 965 912
Traditional
Pair Trading
(2SD)
*No. of
Transactions
36 60 40 46 46 34
Gross Profit 1,280 1,820 1,790 1,770 1,535 1,257
**Transaction
Cost
504 840 1,496 1,720 1,659 1,226
Net Profit 776 980 294 50 (-124) 31

12. Conclusion
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• Found long-run, short-run relationships
– S50U14 & S50Z14
– KTB & KTBU14
– TRUE & TRUEU14
• At 5-min frequency, found arbitrage opportunities for
– S50U14 & S50Z14
– KTB & KTBU14
– TRUE & TRUEU14
• Both TVECM Pair Trading Strategy (Trading Rule 2) are superior to Traditional Pair
Trading Strategy

13. Conclusion (cont’d)
• Attractiveness : Potential maximum profit in real-life for Prop. Trade in 2 months
• Pair 1 : S50U14 & S50Z14
– Average trading volume = 73 contracts per period (5 mins)
– Estimated potential maximum profit = THB 143,956
• Pair 2 : KTB & KTBU14
– Average trading volume = 66 contracts per period (5 mins)
– Estimated potential maximum profit = THB 42,174
• Pair 3 : TRUE & TRUEU14
– Average trading volume = 211 contracts per period (5 mins)
– Estimated potential maximum profit = THB 201,716
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14. References
• Balke, N. S., & Fomby, T. B. (1997). Threshold cointegration. International economic review, 627-645.
• Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica: Journal of the Econometric Society, 1057-1072.
• Engle, R. F., & Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: journal of the Econometric Society, 251-
276.
• Fama, E. F. (1965). The behavior of stock-market prices. Journal of business, 34-105.
• Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work*. The journal of Finance, 25(2), 383-417.
• Gatev, E., Goetzmann, W. N., & Rouwenhorst, K. G. (2006). Pairs trading: Performance of a relative-value arbitrage rule. Review of Financial Studies, 19(3), 797-827.
• Granger, C. W. (1981). Some properties of time series data and their use in econometric model specification. Journal of econometrics, 16(1), 121-130.
• Hansen, B. E., & Seo, B. (2002). Testing for two-regime threshold cointegration in vector error-correction models. Journal of econometrics, 110(2), 293-318.
• Johansen, S. (1991). Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica: Journal of the Econometric
Society, 1551-1580.
• Kaewmongkolsri, C. (2011). Lead-lag Relationship and Price Discovery in KTB Spot and KTB Futures Markets. Faculty of Commerce and Accountancy, Thammasat
University.
• Nestorovski, M., Naumoski, A. (2013). Economic Crisis and the Equity Risk Premium. 9th International ASECU Conference on "Systemic Economic Crisis: Current Issues
and Perspectives".
• Songyoo, K. (2013). Optimal Positioning in Thailand's Spot and Futures Markets: Arbitrage Signaling from Threshold Cointegration Model (Dissertation, Thammasat
University).
• Thongthip, S. (2010). Lead-lag Relationship and Mispricing in SET50 Index Cash and Futures Markets (Doctoral dissertation, Faculty of Economics, Thammasat University).
• Vidyamurthy, G. (2004). Pairs Trading: quantitative methods and analysis (Vol. 217). John Wiley & Sons.
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