1. R&D-Intensity, Mispricing, and Stock Returns in Taiwan Stock Market

2. Literatures review: properties of high R&D-intensive firms 1.Barron et al (2001) and Barth, Kasznink, and Mcnichols (1999) observe that analysts’ forecast error is negatively associated with a firm level of intangible assets including R&D and others. 2.Aboody and Lev (2000) suggest that R&D expenditures generate information asymmetry and insider gain 3.Kothari et al. (2002) report that the earnings volatility associated with R&D expenditures is three times larger than that associated with tangible investment in property, plant and equipment 4.Barron, Byard, Kile, and Riedl (2001) find that lower levels of analyst consensus are associated with the R&D expenditures of high-technology manufacturing companies.

3. The high R&D intensity firms are hard to be correctly evaluated. R&D are increasingly importantly under Taiwan’s economic development. Given the increasing importance of R&D, are their valuations for R&D different from those in the U.S. stock market recorded in previous literature? Motivations

4. The three essential issues 1.Does the stock market correctly value firms’ R&D intensity? 2.Is the valuation meaningfully attributable to the fundamental dimensions of return and associated risks or characteristics of firms? Does mispricing associated with the R&D intensity exist? 3.Is the valuation, if existing, subject to numerous conditions, such as seasonality, market conditions, industrial structures, and even the development process of Taiwan’s Economics?

5. Recent evidence 1.Chan, Lakonishok and Sougiannis (2001) find evidence that returns on firms involved in R&D are equivalent to the returns on firms without R&D. 2.Many researchers find a positive relationship between R&D expenditures and subsequent stock returns (e.g., Hirschey and Weygandt, 1985; Cockburn and Griliches, 1988; Bublitz and Ettredge, 1989; Lev and Sougiannis, 1996) 3.A recent study by Titman, Wei, and Xei (2001) provide evidence that firms with high capital expenditures yield lower benchmark-adjusted stock returns, a result primarily driven by the over-investing problem.

6. Samples and Methodology Data 1.All the data are obtained from the Taiwan Economic Journal (TEJ). 2.The sample period covers from July 1988 to June 2002. There are totally 168 observations for each stock. 3.Following Chan, Lakonishok and Sougiannis (2001), we use R&D expenditures relative to sales (R&D/Sales) and R&D expenditures relative to market value (R&D/ME) as the two measures of R&D intensity.

7. 1.The first measure (R&D/Sales) is used as an indicator of how much money, proportional to their sales, firms spend in R&D activities or how enthusiastically firms devotes their resources to R&D activities. 2.The second measure of R&D intensity (R&D/ME), unlike the first measure, not only depends on firms’ spending in R&D, but also explicitly accommodates the market price or the valuation of investors. The essence of this measure plausibly keeps up with many financial indicators widely used in financial research, such as the ratios of BM, EP, and cash flows to price that embed the stock price information. The economic interpretations of two R&D intensity measures

8. Methodology 1.Follow Chan and Chen (1991) to derive the size- adjusted portfolio returns. 2.Follow Carhart (1997) to derive the abnormal returns. The four-factor model is explicitly defined as: where a p is the intercept term of the regression or so-called the abnormal return of portfolio p after controlling for the risks mimicked by MOM, SMB, and HML.

9. Preliminary results (Table 1) 1.There is a remarkable upward trend in the aggregate R&D intensity. 2.Compared to those in other countries, R&D intensity in Taiwan was low but grew strongly. 3.Firms in the Electronics industry are enthusiastic in R&D activities. 4.The two measures of R&D intensity, R&D/Sales and R&D/ME, may be very different in essence. 5.Given the high correlation coefficient between R&D/ME and BM as well as size, we expect that R&D/ME is able to predict future returns than R&D/Sales.

10. Table 1: Descriptive Statistics of R&D intensity

11. Table 1: Descriptive Statistics of R&D intensity (cont.)

12. The findings based on R&D/Sales (Table 2) 1.The returns before formation generally increase with respect to the R&D/Sales. 2.The returns after formation monotonically are increasing with R&D/Sales. 3.The zero-cost portfolio returns reported in the last column in years 1, 2, and 3 after formation get enlarged over time and are 0.77%, 0.99%, and 0.73%, with t-value = 1.49, 1.87, and 1.33, respectively. 4.These observations indicate that firms having invested more on R&D are not only the prior winners but also the future winners, and the spread between the portfolio returns with the highest and lowest R&D intensity widens. 5.There is a pronounced difference between the returns on stocks with highest R&D/Sales and stocks without R&D expenditures.

13. 6.The results above are inconsistent with Lakonishok, Shleifer, and Vishny (1994) and Chan, Lakonishok and Sougiannis (2001). 7.The evidence suggests that firms that the return spread between firms with different levels of R&D intensity is not caused by size effect. 8.Investors undervalue the R&D-intensive firms and overvalue the non-R&D-intensive firms. 9.These preliminary results seem to support mispricing hypothesis that the market could not correctly values the future benefits from the R&D spending. The findings of portfolios based on R&D/Sales (cont.)

14. Table 2: Monthly returns (%) and characteristics of portfolios based on R&D/Sales

15. Table 2: Monthly returns (%) and characteristics of portfolios based on R&D/Sales (cont.)

16. 1.The relationship between returns and R&D/ME are much stronger than between returns and R&D/SALES. 2.The mispricing of stocks not only exists but also is persistent. 3.Size effect cannot explain the anomaly. 4.It is obvious that mispricing phenomenon is even stronger using R&D/ME as the measure of the R&D intensity than using R&D/Sales. The findings based on R&D/ME (Table 3)

17. Table 3: Monthly returns (%) and characteristics of portfolios based on R&D/ME

18. Table 3: Monthly returns (%) and characteristics of portfolios based on R&D/ME (cont.)

19. Abnormal returns (Table 4) 1.The four-factor model works rather well for R&D/Sales-based portfolio returns, but not for R&D/ME-based portfolio returns. 2.All results provide further evidence that mispricing does exist and persist, especially when applying R&D/ME as the measure of R&D intensity. 3.The relatively low adjusted R 2 ’s of the regressions on the R&D-intensive portfolio returns support that the uncertainty associated with the R&D activities cannot be captured by the four well-known factors.

20. Table 4: Abnormal returns

21. Explanatory power of the R&D intensity in stock returns To investigate the relationship between stock returns and competing characteristics such as firm size, BM, R&D/Sales, and R&D/ME, we employ the following empirical model the estimate the stock returns:

22. The results (Table 5) 1.Consistent with the results of Chan et al. (1998) and Chui and Wei (1997), no evidence of the BM effect exists in Taiwan stock market. 2.The explanatory power of the R&D intensity measured by R&D/ME is stronger than that measured by R&D/Sales. 3.The result suggests that, in Taiwan stock market, the R&D intensity may be more informative than firm size and BM.

23. Table 5: Average coefficients of the regression results of stock returns on ln(ME), ln(BM), ln(R&D/SALES), and ln(R&D/ME)

24. Figure 1: Cumulative returns on the market index, Electronic index, and zero-cost portfolios from July 1988 to June 2002

25. Table 8: Returns and characteristics of portfolios based on R&D/ME in the Electronic industry and non-Electronic industries

26. Table 9: Average coefficients of regressions of stock returns on ln(ME), ln(BM), and ln(R&D/ME) for all firms, firms in the Electronic industry, and firms in non-Electronic industries before and after 07/1996