1. Investor Sentiment and Price Discovery: Evidence from the Pricing Dynamics between the Futures and Spot Markets SWJTU, Chengdu, 2015 Robin K. Chou National Chengchi University, Taiwan Chu Bin Lin National Chengchi University, Taiwan George H.K. Wang George Mason University, United States

2. Introduction  Price discovery is arguably one of the most important products of a financial market. In a perfectly frictionless world, price movements of stock index futures and the underlying spot market are contemporaneously correlated and not cross-autocorrelated (Hasbrouck, 1995; Chan, 1992).  However, if one market reacts to new information faster than the other, an asymmetric lead–lag relation is observed (Chan, 1992). 2

3. Introduction SpotFutures 3 Frictionless world

4. Introduction SpotFutures 4 Real world

5. Introduction  Informed traders prefer to trade on the futures markets, which, compared to the spot markets, offer higher leverages, lower costs, and fewer short-sale restrictions(Black, 1975; Kawaller, Koch, and Koch, 1987; Stoll and Whaley, 1990; Käppi, 1997; Chan, 1992; Back, 1993; Mayhew, Sarin, and Shastri, 1995; Easley, O’Hara, and Srinivas, 1998).  The most popular explanation for the asymmetric lead–lag relation is that the futures market is less costly for informed traders to utilize than the spot market, so the futures market is dominant in revealing information(Chan, 1992). 5

6. Introduction SpotFutures 6 Lead-lag relation Investor sentiment

7. Introduction  Investor sentiment has been found to affect investor trading behavior, stock returns, return volatility, and market efficiency (Lee, Jiang, and Indro, 2002; Baker and Wurgler, 2006; Schmeling, 2009; Kurov, 2010; Baker, Wurgler and Yuan, 2012; Berger and Turtle, 2011).  Baker and Wurgler (2006) construct an index of investor sentiment and find that their index can predict subsequent returns for stocks. 7

8. Introduction  Yu and Yuan (2011) discover a critical role for investor sentiment in the market efficiency. Specifically, there is a strong positive mean-variance tradeoff when sentiment is low but little if any relation when sentiment is high.  Similarly, Stambaugh, Yu and Yuan (2012) examine the profitability of long-short strategies on 11 market anomalies and find that each anomaly is stronger following high levels of sentiment but little following low levels of sentiment. 8

9. Introduction 9 Sentiment Price volatility Bid-ask spread Noise trader risk (+)

10. Introduction  The theory of limits to arbitrage suggests that informed traders would become less willing to leverage their information when trading risk is high.  Trading cost hypothesis suggests that informed trading decreases when it is more costly for informed traders to exploit their information. 10

11. Hypotheses  Hypothesis 1: The leading role of the futures market is weakened during high investor sentiment periods.  Hypothesis 2: The prices on the futures market become less informative during high investor sentiment periods. 11

12. Data and Methodology  Three intraday ETFs-and-futures price pairs from 2002 to 2010 are examined: 1. S&P 500 ETFs and E-mini futures, 2. Nasdaq 100 ETFs and E-mini futures, 3. DJIA 30 ETFs and E-mini futures.  Monthly sentiment index is from Baker and Wurgler (2006). 12

13. Data and Methodology 13

14. Empirical Results

15. Empirical Results: Part I Table 2 Realized volatility and investor sentiment

16. Empirical Results: Part I Table 3 Bid-Ask Spread and Investor Sentiment

17. Empirical Results  In summary, this paper finds adequate evidence showing that investor sentiment is positively correlated with the realized volatility and bid-ask spread.  It is expected that the higher trading risk and cost caused by high sentiment to deter informed traders from trading on the futures market, which in turn diminishes the leading role of the futures market. 17

18. Table 4 VECM estimation of ETFs and E-mini Futures of S&P 500

19. Table 5 VECM estimation of ETFs and E-mini Futures of Nasdaq 100

20. Table 6 VECM estimation of ETFs and E-mini Futures of DJIA

21. Empirical Results  Tables 4 to 6 support Hypothesis 1 that the leading role of the futures market is weakened during high investor sentiment periods.  This indicates that the informed and/or arbitrageurs are reluctant to trade when the noise trading risk is particularly high. 21

22. Table 8 Regression Analysis of the Information Shares on Investor Sentiment

23. Table 9 Regression Analysis of the GG Factor Weights on Investor Sentiment

24. Empirical Results  The results reported above support our Hypothesis 2 that the prices on the futures market become less informative during high investor sentiment periods.  This study is in line with Shleifer and Vishny (1997) and Barberis, Shleifer, and Vishny (1998) that informed traders will avoid exposing themselves to extreme risk during high sentiment periods. 24

25. Conclusion  Investor sentiment has a positive impact on both price volatility and bid-ask spread.  The leading role of futures market becomes significantly weaker when investor sentiment is high.  The information shares of futures market have a negative relation with investor sentiment. 25

26. 26 Thank you.