Discussion of The Examination of R&D Impact on Firm Value

1. Discussion ofThe Examination of R&D Impact on Firm Value By Chuan Yang Hwang Nanyang Technological University

2. Summary • Positive future returns for firms which have a large decrease in R&D • Lower future operating performance for firms which have a large decrease in R&D • The cost of capital decreases after large decrease in R&D • Explain the results with overinvestment hypothesis: firms which expect decrease in growth opportunity reduce R&D, but investors underestimate the benefit of reduction such as the reduction in the cost of capital and the agency cost

3. Comments • An interesting paper, have enjoyed reading it. • How to distinguish the cost of capital and future return. They seems to be measured by the sample variable and in the same way. Explain in time line when the cost of the capital becomes lower and when the future return becomes higher after firms have a large reduction in R&D. • The authors argue that (1) investors (financial analysts ) are able to forecast or detect the deterioration of operating performance (2) investors fail to recognize the benefit of the R&D reduction. Somewhat inconsistent .

4. Comments • The major result in this paper can be affected (or due to) tax loss-selling generated January effect for the following reasons. • Firms with large R&D reductions are small firms (Table1) • The effect is much stronger for equally-weighted than value-weighted portfolios (Table 2) • The results are much stronger for firms with high institutional ownership (Table 6). This is because institutional investors tend to engage in window dressing (selling losers at year end) , which can also generate large January return. • The finding of the reduction in cost of capital for the large R&D decrease firms may indicate the capital loss rather than lower cost of capital hence the candidates of the tax-loss selling.

5. Measure Development • Private information is revealed in the sequence of trade prices. • Glosten and Milgrom (1985) and Kyle (1985) • Price discovery: incorporation of new information into stock price(O’Hara,2003) • Llorente et al. (2002), trade price is likely to continue if the trade is driven by information; particular true for trade of large volume • Informed traders prefer large trade • Easley and O'Hara (1987) • Uninformed trade in both large and small size • Informed trade only in large size • Barclay and Warner (1993) • Informed trades concentrate in the trades of 1000 to 9900 shares

6. Large Trade and Small Trade Classification • Lee (1992), Lee and Radhakrishna (2000) and Hvidkyaer (2006) • Large and small trades are defined based on investment value • Avoid the sensitivity to small stock price change • $20, $10,000, 100-500 shares • $20⅛, $10,000, 100-400 shares • Conditional on firm size

7. Measure Development • Cointegration and VECM, estimate the price discovery in the large trade. • Harris et al. (1995) , Hasbrouck (1995) , Eun and Sabherwal (2003) , Werner and Kleidon (1996) • Price discovery (informativeness) of security price in different markets. • Huang (2002), Booth, Lin, Martikainen, and Tse (2002), Hendershott and Jones (2005) • Price discovery (informativeness) of prices by different clienteles.

8. VECM • is the error correction term, a stationary process with mean zero. • αL<0; αS>0; • If αLcloser to zero, PL reflects more (private) information. • - Why not public? • - Why not αS? • αLis the asymmetric information risk measure (ECIN)

9. Hypotheses 1) There is more informed trading and price discovery in large trades than in small trades, so |αL|< αS 2) αL is positively related to the degree of information asymmetry. 3) If the asymmetric information risk is a priced risk, αL will be positively related to the future stock returns.

10. Data Samples • NYSE and AMEX • January 1983-December 2005 for ECIN estimation • January 1984-December 2006 for asset pricing test • VECM is estimated for each firm each calendar year • augmented Dickey-Fuller unit-root test • Johansen cointegration test • 32,706 firm-years

11. Match Large and Small Trades • MINISPAN (Harris, McInish, Shoesmith, and Wood (1995)) • In 50.44% of the matched pairs, the large trade precedes the small trade • Within-pair mean time gap is 3.96 minutes. • Between-pair mean time gap is 9.15 minutes • Retrieve the matched pairs at fixed intervals of 15 minutes.

12. Table 3 VECM Parameters • In total, we have 61.53% firm-years with |αL|< αS

13. The Correlation of ECIN with Other Information Asymmetry Measures • Probability of Information-Based Trading (PIN) • Easley, Kiefer, O'Hara, and Paperman (1996), Easley, Hvidkjaer and O’Hara(2002) • Bid-ask Spread • Firm Size

14. Table 5 Asset Pricing Tests

15. Table 6 Asset Pricing Tests – Further Check

16. Table 7 Compare ECIN with PIN

17. Table 8 Economic Significance of ECIN

18. Table 8 Economic Significance of ECIN

19. Conclusion • Information risk is priced. • Information risk matters in the stock return beyond the illiquidity. • ECIN dominates PIN in the asset pricing test. • More precise • Avoid the converging and corner solution problem • Easy to estimate • Not subsumed by illiquidity

20. Thanks!