1. 1 The Dynamic Relation of Volatility and Futures Trading under Market Conditions and Changing Sentiments PAUL L. HSUEH Y. ANGELA LIU NICHOLAS R. LEE

2. 2 1. INTRODUCTION Critics of financial market innovations and liberalization –increased stock market volatility can be largely attributed to the introduction of futures trading and the increased derivatives trading activities. –derivatives transactions help stabilizing the prices of underlying securities in the cash market an important issue of whether increased futures trading leads to or is caused by increased spot volatility

3. 3 Paper Reviewed Earlier studies by Edwards (1988a, 1998b), Aggarwal (1988), and Schwert (1990) generally find no volatility increase in the cash market since the advent of index futures trading. Lee and Ohk (1992), on the other hand, present evidence that futures trading affects cash market volatility only in more matured markets including Japan, the U.K. and the U.S., but not in less developed markets such as Australia or Hong Kong.

4. 4 Paper Reviewed Subsequent research focuses on the lead-lag relationship between derivative trading and cash market volatility, but the results are still mixed.(Chen et al. (1995), Ciner (2002), Fung and Patterson (1999), Hagelin (2000), Kocagil and Shachmurove (1998), Kyriacou and Sarno (1999), Yang et al. (2005), etc.)

5. 5 Motivation The mixed empirical evidence put forth in the literature warrants a further investigation of the relationship between futures trading and volatility. Past studies focus primarily on the markets of western industrial nations, with little evidence reported for the eastern emerging markets. Past literature lacks a direct comparison of possible changes in such relationship between markets of differing infrastructure when going through liquidity periods. Our research attempts to reinvestigate the issue of concern to fill this empirical gap.

6. 6 Our Examination In this study, we focus on futures trading activities for hedgers and speculators on the S&P 500 index and the Hang Seng index contracts, and examine and compare the dynamic relationship with the volatility of trading-hour index returns in markets of differing degree of sophistication.

7. 7 Our Examination(2) To further attempt to analyze their respective trading behaviors during periods of changing futures trading, providing examinations and comparisons of hedgers ’ hedging and arbitrage activity and speculators ’ speculative activity based on the argument of Harris (1989).

8. 8 2. METHODOLOGY AND DATA 2.1 Experimental variable defined Spot Volatility Measure (C) Futures trading measure (F)

9. 9 In this study, we employ the volatility measured by Garman and Klass (1980) to proxy for the cash market volatility (C) In this study, we employ the volatility measured by Garman and Klass (1980) to proxy for the cash market volatility (C)

10. 10 We also follow Schwert (1990) and Jones et al. (1994) to construct another daily volatility. we derive a measure of volatility, |e t |, that corresponds to open-close, close-open, and close-close futures returns used in the regression analysis above.

11. 11 In this study, we follow Garcia et al. (1986) and define futures trading activities (F) as the ratio of daily closing volumes over open interest as follows:

12. 12 Futures trading by traders types In order to differentiate hedger and speculator activities in futures trading, some studies rely on the Commitments of Traders (COT) filed with the CFTC. Although it is simple, the CFTC classification can be misleading. This is because while speculators normally conduct speculative trades, hedgers do not limit themselves to just hedging activities.

13. 13 Bessembinder and Seguin (1992) Pagan and Schwert (1990) Harris(1989) argument Decompositions of futures trading with two steps procedures

14. 14 the expected component is consistent with Harris’ (1989) ‘populist variant’, predicting that uninformed speculative activity destroys the information process and destabilizes the market. the unexpected component is consistent with Harris’ (1989) ‘liquidity variant’, which predicts that order imbalances related to arbitrage trading can cause the volatility to increase. Harris(1989) argument Decompositions of futures trading with two steps procedures(2)

15. 15 Increased speculative/arbitrage trading Less hedging trading Less speculative/arbitrage trading Increased hedging trading our decomposition of the futures trading activities can reveals interesting trading behaviors about the speculators and hedgers in the market Changing Sentiments FIGURE 1 The impact of futures trading for changing sentiments of hedgers on the market

16. 16 Trivariate VAR methodology according to Fung and Patterson (1999) Where is a column vector for return volatility, speculating trading, and arbitrage activity at time t for index futures. and are and matrices of coefficients, respectively. M is the exogenous Monday variable that controls for Monday/weekend effect, and e is the column vector of serially uncorrelated error terms.

17. 17 Data Description This study employs daily data spanning the period from January 1, 1987 through December 31, 2005. Futures trading volume and open interest across all outstanding contracts, as well as the daily opening, high, low, and closing prices of the nearby futures contracts on S&P 500 index and the Hang Seng Index (HSI) are obtained from DataStream database.

18. 18 3. EMPIRICAL RESULTS

19. 19 TABLE I Returns statistics for the daily sample period from 1987 to 2005 US HK Statistics(%)TRCCRTRCCR Mean0.0190.0340.0310.037 Maximum19.09517.74919.24422.153 Minimum-27.016-33.700-41.437-58.045 Std. Dev.1.0951.2311.5772.054 Note: Trading-hour return (TR) and close-close return (CCR) are computed based on open-close, and close-close prices, respectively.

20. 20 TABLE II Sample statistics, volatility and futures trading Note: ** and * represent significance levels of 1% and 5%, respectively. USHK StatisticsCFCF TRVCCVHLVTRVCCVHLV Mean0.6980.7700.81128.3901.0021.2411.01539.043 Std. Dev.0.8270.9500.61415.7101.1911.6200.87116.218 ADF-4.46 ** -5.00 ** -3.78 ** -2.62 ** -5.50 ** -6.24 ** -5.23 ** -1.27 Lag(PACF)1-5

21. 21 U.S. Hong Kong FIGURE 2 Detrended futures trading for U.S. and Hong Kong market

22. 22 TABLE III Correlation of futures trading and volatility for hedgers and speculators Note: ** and * represent significance levels of 1% and 5%, respectively. HedgerSpeculator USTRV0.240 ** 0.107 ** CCV0.237 ** 0.114 ** HLV0.234 ** 0.177 ** HKTRV0.220 ** 0.067 ** CCV0.267 ** 0.071 ** HLV0.208 ** 0.137 **

23. 23 Table IV Granger causality test by applying Trivariate VARs model for causal relations HedgerSpeculator ModelCFCFCFCFCFCFCFCF USHLV 47.06 ** 120.11 ** 46.47 ** 10.90 TRV 28.46 ** 99.05 ** 43.41 ** 7.61 CCV 28.44 ** 97.16 ** 29.44 ** 9.89 HKHLV 32.31 ** 17.09 ** 20.22 ** 48.38 ** TRV 11.70 18.85 ** 21.38 ** 34.13 ** CCV 30.83 ** 36.27 ** 21.97 ** 20.47 ** Note: ** and * represent significance levels of 1% and 5%, respectively.

24. 24 Table V Granger causality test by alternative four cases HS VOIModel FCFCFCFCFCFCFCFC USLow HLV51.76 ** 8.8235.48 ** 35.58 ** TRV19.67 ** 5.977.6318.37 ** CCV18.83 ** 7.905.6513.63 LowHighHLV41.77 ** 72.19 ** 21.51 ** 9.12 TRV14.67 * 40.30 ** 17.92 * 1.58 CCV15.83 * 45.24 ** 8.411.18 HighLowHLV25.67 ** 25.40 ** 22.42 ** 7.57 TRV31.99 ** 27.20 ** 44.48 ** 9.66 CCV29.90 ** 33.76 ** 42.26 ** 17.80 High HLV66.96 ** 62.55 ** 37.59 ** 21.12 ** TRV33.97 ** 45.39 ** 36.92 ** 37.13 ** CCV33.77 ** 41.05 ** 37.36 ** 39.99 ** HKLow HLV51.79 ** 38.26 ** 26.04 ** 32.91 ** TRV57.46 ** 31.22 ** 26.83 ** 22.83 ** CCV52.29 ** 23.10 ** 20.62 ** 20.86 ** LowHighHLV23.42 ** 26.66 ** 9.4222.88 ** TRV34.28 ** 22.12 ** 7.9913.97 * CCV30.17 ** 17.20 ** 14.46 * 34.25 ** HighLowHLV31.44 ** 29.00 ** 9.1419.73 ** TRV22.44 ** 22.16 ** 13.37 * 8.97 CCV29.64 ** 25.84 ** 16.84 ** 9.71 High HLV37.56 ** 19.88 ** 15.89 * 6.28 TRV15.99 * 6.098.243.91 CCV11.277.864.9510.58 Note: ** and * represent significance levels of 1% and 5%, respectively.

25. 25 4. CONCLUSIONS Our data show that the U.S. and Hong Kong market exhibit quite different characteristics. Futures trading activity is dominated by hedgers in U.S. market, while speculators’ trading is more prevalent in Hong Kong. Furthermore, the Hong Kong market in general exhibits greater volatility than their U.S counterpart, and findings from contemporaneous correlations suggest that the U.S. market is relatively more liquid and efficient.

26. 26 4. CONCLUSIONS(2) volatility leading futures trading for both hedgers in the U.S. market and speculators in the Hong Kong market is found to stabilize the market whereas futures trading leading volatility destabilize the market under investigation for different information and trader- types.

27. 27 4. CONCLUSIONS(3) As a somewhat surprising result, our finding further indicates that hedgers may take either hedging or speculative/ arbitrage activities whereas speculators purely take speculative activities although observing the distinct relationship between volatility under different information and futures trading activity for hedgers and speculators in both markets across market conditions.

28. 28 4. CONCLUSIONS(4) our examinations of volatility, changing sentiments, and decompositions of futures trading activities, offer further insights into the causal relation of volume and volatility about markets of differing degrees of sophistication.