Capital Investment, Innovative Capacity, and Stock Returns Praveen Kumar University of Houston Dongmei Li University of South Carolina

Motivation Asset pricing implications of capital investment Literature: Titman, Wei, and Xie (2004), Cooper, Gulen, and Schill (2008), Xing (2008), Lyandres, Livdan, and Zhang (2008), Polk and Sapienza (2009), Li and Zhang (2010), Cooper and Priestley (2011), among others. Explanations: Traditional real options view: Berk, Green, and Naik (1999), Carlson, Fisher, and Giammarino (2006) Behavioral explanations (under-reaction or over-reaction) This paper: innovative capacity (IC) investment

Real-world examples of IC investment Building research center/infrastructure Many large pharmaceutical companies (e.g., Merck, Johnson & Johnson) spent billions of dollars setting up “innovation hubs” in Boston, San Francisco, Shanghai, and London. Buying R&D equipment/machinery for both current and future alternative projects Buying patents from other firms A group of firms led by Apple spent $4.5 billion buying patents from Nortel Network

Unique Features of IC Investment Facilitates options generation with significant uncertainty If successful, allows firms to charge higher quality-based price and sales. Dynamic implications: Expected returns Future investment Profitability Factor loadings

Main Predictions and Findings Effect of IC investment on future expected returns is unique and dynamic: Depend on the resolution of the uncertainty regarding the generation and exercise of options. Before the uncertainty is resolved, the effect is ambiguous After the resolution, the effect is positive for firms with non-increasing revenue returns of IC investment (large IC firms) IC investment increases expected future investment Large IC firms have higher future profitability

Identification of IC Investment Innovation-driven firms’ capital investment/asset growth Identification of IC firms Main method: R&D-active firms Robustness check: Firms with low leverage or high market-to-book assets (dominant characteristics of R&D-intensive firms)

Measures of Capital Investment Measures used in the literature Abnormal capital investment (Titman et al. 2004) Growth in capital investment (Xing 2008) Investment-to-assets ratio (Lyandres et al. 2008) Investment-to-capital ratio (Polk and Sapienza 2009) Asset growth (Cooper et al. 2008) The results are robust to all these measures

Exclude financial firms and very small firms (total assets < $25mn) Sample Sample period: 1976-2011 R&D reporting is standardized in 1975 Exclude financial firms and very small firms (total assets < $25mn) To reduce backfilling bias, we only keep firms that are listed on Compustat for at least two years

Empirical Test Design Portfolio sorts Fama-MacBeth regressions Independent triple sorts on innovation proxies, size, and capital investment (2 by 2 by 10) Examine the capex-return relation over the post-sorting years Fama-MacBeth regressions

Summary Statistics RDS Rank Size Rank AG Rank AG Size BTM MABA DTE Low Small 1 (Low) -0.20 137 1.62 1.18 2.35 5 0.07 224 1.10 1.25 0.90   10 (High) 227 0.75 1.77 1.12 Big -0.19 3807 0.87 1.48 0.97 5113 0.80 1.52 1.14 3907 0.55 2.20 0.65 High 132 1.43 222 1.00 1.42 0.57 237 0.58 2.36 0.48 4816 0.72 1.76 0.54 8799 0.60 0.40 1.20 6348 0.37 3.53 0.30 Spread in asset growth (AG) is similar across the RDS-size groups.

Confirmation of Investment Anomalies Monthly Carhart Alphas (in percentage)   AG Deciles (EW) AG Deciles (VW) Year 1(Low) 10(High) 10−1 1 0.55 -0.35 -0.90 -0.01 -0.26 -0.25 (3.42) (-2.74) (-6.15) (-0.06) (-2.37) (-1.38) 2 0.41 -0.10 -0.51 -0.06 -0.02 0.04 (2.67) (-0.67) (-3.37) (-0.46) (-0.15) (0.21) 3 0.51 0.18 -0.34 0.12 0.00 (3.61) (1.19) (-2.80) (0.96) (0.97) (-0.01) 4 0.40 0.17 -0.23 -0.14 0.26 (2.78) (1.33) (-1.98) (-0.93) (0.92) (1.42) 5 0.47 0.24 0.35 (3.06) (2.06) (-1.69) (-0.35) (2.51) (1.73) For equal-weighted (EW) portfolios, there is a significantly negative relation between asset growth (AG) and future abnormal returns. For value-weighted (VW) portfolios, the relation is much weaker.

IC investment and stock returns

IC investment and future investment

IC investment and future profitability

IC investment and factor loadings

Investment Anomalies within RDS-Size Groups Value-weighted monthly Carhart alphas (%) Low RDS, Small Low RDS, Big High RDS, Small High RDS, Big AG Deciles Yr 1 10 10-1   -0.15 -0.71 -0.56 0.12 -0.44 0.03 -0.38 -0.41 -0.01 0.01 0.02 2 -0.52 -0.58 -0.06 -0.28 -0.20 0.07 0.13 0.06 -0.07 0.30 0.28 3 -0.10 -0.21 -0.12 0.37 -0.32 -0.70 0.09 0.00 -0.09 0.16 0.39 0.23 4 -0.19 -0.18 -0.25 -0.27 -0.16 0.49 0.58 5 -0.29 -0.11 0.15 -0.13 0.70 The pattern is similar for equal-weighted portfolios.

Test of the “Empire-Building” Hypothesis Year AG AG*HRDS_LDCF HRDS_LDCF ln(Size) ln(BTM) Momentum 1 -0.75 0.18 0.26 -0.10 0.19 0.56 (-7.23) (1.22) (4.07) (-2.04) (2.44) (2.53) 2 -0.41 0.08 0.22 -0.13 0.47 (-4.62) (0.62) (3.73) (-2.68) (1.04) (2.09) 3 -0.27 0.21 0.20 -0.14 0.01 0.44 (-2.70) (1.48) (3.34) (-2.94) (0.12) (1.96) 4 -0.19 0.07 -0.15 -0.01 0.29 (-1.92) (0.51) (3.36) (-3.07) (-0.13) (1.25) 5 -0.26 0.00   (-2.35) (0.01) (3.03) (-2.84) (-0.19) (1.06) HRDS_LDCF is a dummy variable for high R&D firms with low debt-to-cash flow (i.e., more investment discretion). The slope on AG*HRDS_LDCF is insignificant, which is inconsistent with the “empire-building” hypothesis.

Robustness Check — Alternative proxy of IC firms Value-weighted monthly Carhart alphas (%) Low MABA, Small Low MABA, Big High MABA, Small High MABA, Big AG Deciles Yr 1 10 10-1   0.13 -0.26 -0.40 0.00 -0.23 -0.25 -0.61 -0.36 0.07 -0.08 -0.16 2 -0.33 -0.07 -0.13 -0.06 0.08 -0.31 -0.01 0.17 0.18 3 -0.12 -0.32 -0.20 0.20 -0.59 -0.79 0.09 -0.03 0.16 0.36 0.19 4 -0.37 -0.19 0.06 -0.15 -0.22 -0.04 0.25 0.30 5 0.01 -0.70 -0.71 -0.28 -0.45 -0.10 0.65 0.75 Identifying IC firms with low leverage generates similar results in portfolio sorts and Fama-MacBeth regressions.

Summary and Conclusion We find that the implication of IC investment on future returns, risk, investment and profitability are in sharp contrast to traditional capex This evidence potentially helps differentiate alternative explanations of the investment anomalies