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

2. 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

3. 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

4. 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

5. 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

6. 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)

7. 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

8. Exclude financial firms and very small firms (total assets < $25mn)
Sample
Sample period:
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

9. 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

10. 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.

11. 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.

12. IC investment and stock returns

13. IC investment and future investment

14. IC investment and future profitability

15. IC investment and factor loadings

16. 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.

17. 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.

18. 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.

19. 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