Don’t Hide Your Light under a Bushel: Innovative Originality and Stock Returns David Hirshleifer UC Irvine Po-Hsuan Hsu University of Hong Kong Dongmei Li University of South Carolina

Motivation – Psychological Evidence Limited attention: Individuals pay less attention to information that is hard to process View toward complex signals: People are more suspicious about more complex signals They view the subject riskier than it actually is e.g., Alter and Oppenheimer (2006), Song and Schwarz (2008, 2009, 2010)

Motivation – Valuation of Innovation Hard technical uncertainty long road from concept to actual profits market risk and competitor risk Evidence suggesting market misvaluation of innovation proxies Chan, Lakonishok, and Sougiannis (2001), Eberhart, Maxwell, and Siddique (2004), Hirshleifer, Hsu, and Li (2012), Cohen, Diether, and Malloy (2012), among others

Question and Hypotheses Does market fully impound originality of a firm’s innovative activities (IO)? If IO is + indicator of future fundamentals, limited attention  (in spirit of models of Hirshleifer & Teoh 2003, Hirshleifer, Lim & Teoh 2011) Higher IO predicts higher abnormal returns Predictability is stronger among firms with More valuation uncertainty Lower investor attention Higher sensitivity of fundamentals to IO

Empirical Findings IO and fundamentals IO and future abnormal returns High-IO firms have lower contemporaneous ROA/ROE High-IO predicts significantly higher future ROA/ROE IO and future abnormal returns High IO predicts significantly higher future abnormal returns Predictability much stronger among younger, more opaque, lower investor attention, larger, and growth firms

Measure of Innovative Originality Popular view of invention  recombinant search E.g., Gilfillan 1935; Schumpeter 1939; Basalla 1988; Weitzman 1996; Henderson and Clark 1990. Invention comes from Combining technological components in novel manner Reconfiguring existing combinations Example/analogy: Steamship — combination of boat/steam engine Behavioral finance

Empirical Proxy of Innovative Originality Breadth/Diversity of knowledge drawn upon by an invention Patent level # tech classes contained in a patent’s reference list (N) Firm level Average N across a firm’s recently granted patents

Empirical Proxy of IO (cont’d) Common in innovation/corporate finance literature E.g., Trajtenberg, Henderson & Jaffe (1997), Hall, Jaffe & Trajtenberg (2001), Lerner, Sorensen & Strömberg (2011), and Custodio, Ferreira & Matos (2013). Additional supporting evidence High IO predicts higher future citations received per patent and better future fundamentals

Proxies of Conditioning Variables Valuation uncertainty (VU) Firm age (Kumar 2009): an inverse proxy Opacity of financial reports (Hutton, Marcus & Tehranian 2009) VU Index = Standardized opacity – Standardized age Investor attention Analyst-to-shareholder ratio (ATS) PEAD/Earnings surprise (Hirshleifer, Lim & Teoh 2009): an inverse proxy Attention Index = Standardized ATS – Standardized PEAD/Earnings surprise

Proxies of Conditioning Variables (cont’d) Sensitivity of fundamentals to IO Size Large firms benefit more from high IO E.g., Schumpeter (1950); Acs and Audretsch (1987); Cohen, Levin & Mowery (1987) Book-to-Market (BTM) Values of growth firms (low BTM) derive more from IO Sensitivity Index = Standardized size – Standardized BTM Verification of the validity of these proxies: Regressing future ROA/ROE on IO Significantly higher slopes on IO among large firms, low BTM firms.

Empirical Test Design Portfolio sorts Fama-MacBeth regressions Industry- and characteristics-adjusted returns Alphas relative to standard risk factor models Fama-MacBeth regressions Industry effects Other return predictors such as: Size, book-to-market, momentum, innovative efficiency (IE), patents, R&D intensity, institutional ownership, stock illiquidity, short-term return reversal, asset growth, net stock issuance, capital investment, ROA, idiosyncratic volatility (IVOL) and skewness.

IO of Selected Industries Industry (FF48) Mean Stdev Min P30 P50 P70 Max Healthcare 7.01 4.48 1.00 4.60 6.00 8.00 27.00 Medical equipment 7.38 4.91 4.47 6.04 8.35 43.92 Pharmaceutical products 6.59 4.41 4.33 5.50 7.00 42.47 Chemicals 6.53 3.83 4.61 5.80 7.25 38.00 Machinery 5.95 3.38 4.00 5.12 6.93 27.25 Electrical equipment 5.78 3.92 3.71 5.00 6.50 49.06 Automobiles and trucks 5.10 2.45 4.92 5.75 20.50 Aircraft 4.93 2.08 3.74 4.75 5.77 12.65 Shipbuilding, railroad equipment 5.54 2.63 2.00 4.66 5.90 14.40 Telecommunications 6.32 4.16 5.03 6.38 31.00 Personal services 4.73 4.22 2.50 24.00 Business services 7.88 5.43 6.60 8.83 66.00 Computers 6.26 3.75 4.08 36.61 Electronic equipment 5.92 3.82 46.50 Measuring and control equipment 6.25 5.33 7.26 31.23 Transportation 4.42 9.00 22.00

Summary Statistics of IO Portfolios IO Rank Obs IO Size (mn) BTM ROA (%) ROE (%) No 3270 642 0.83 1.68 1.00 Low 419 3.02 1154 0.74 1.32 1.50 Middle 550 5.37 4334 0.70 3.05 4.40 High 409 9.78 2033 0.64 0.29 0.80

IO and Next Year’s ROE Model 1 Model 2 Estimate (%) t-stat IO 1.42   Estimate (%) t-stat IO 1.42 (9.03) 0.94 (7.96) ROE 25.01 (24.32) 24.89 (24.36) ΔROE -4.48 (-11.03) -4.41 (-10.93) MTB -1.60 (-2.02) -1.56 (-1.95) AdvEx 0.72 (4.75) 0.71 (4.65) CapEx 0.58 (1.59) 0.62 (1.67) R&D -2.38 (-7.04) -2.52 (-7.32) IE 1.10 (5.35) R2 0.37 Results even stronger for next five-year average ROE and are robust for ROA.

Return Predictive Power of IO IO Rank Exret Ind-adjret Char-adjret Alpha MKT SMB HML UMD No 0.60 -0.04 -0.03 -0.13 0.98 0.18 0.07 0.03 (2.38) (-1.10) (-0.13) (-2.07) (59.50) (7.03) (2.54) (1.37) Low 0.48 -0.12 1.00 0.17 (1.74) (-1.73) (-0.53) (-1.49) (40.60) (4.96) (-2.54) (-1.02) Middle 0.73 0.16 0.97 -0.15 -0.17 -0.02 (2.83) (0.76) (0.31) (2.49) (53.59) (-6.07) (-5.75) High 0.80 0.09 0.19 0.24 0.95 0.01   (3.09) (1.86) (2.74) (44.26) (0.21) (-3.08) (-1.64) High-Low 0.32 0.22 0.37 -0.05 -0.16 -0.01 (2.62) (2.43) (2.67) (3.12) (-1.58) (-3.39) (-0.26) (-0.34) Results robust to controlling for other risk factors.

Valuation Uncertainty (VU) and Return Predictive Power of IO Age Exret Ind-adjret Char-adjret 4F 4F + IMC 4F + INV 4F + LIQ 4F + EMI Young 0.75 0.68 0.80 0.81 0.82 0.89 0.83 0.79   (2.83) (2.79) (3.05) (2.66) (2.60) (2.90) (2.69) Old 0.20 0.08 0.21 0.25 0.28 0.16 (1.50) (0.87) (1.58) (1.78) (1.72) (1.70) (1.92) (1.10) Opacity High 0.57 0.33 0.62 0.66 (1.81) (1.19) (1.99) (2.19) (2.15) (2.13) (1.84) (1.86) Low 0.27 0.14 0.41 0.29 0.30 0.26 (1.25) (0.90) (1.07) (1.09) (0.97) (1.20) (1.11) VU Index 0.69 0.61 0.72 0.70 0.71 0.64 (2.39) (2.32) (2.54) (2.04) (2.01) (2.23) (1.93) 0.19 0.11 (1.47) (1.17) (1.60) (1.88) (1.83) (2.07) (1.37) Returns, alphas for high-low IO portfolios

Investor Attention and Return Predictive Power of IO Attention proxied by analyst-to-shareholder ratio (ATS) ATS Exret Ind-adjret Char-adjret 4F 4F + IMC 4F + INV 4F + LIQ 4F + EMI Low 0.34 0.23 0.33 0.39 0.37 0.42 0.32   (2.61) (2.46) (2.57) (2.96) (2.86) (2.79) (3.11) (2.36) High 0.12 0.07 0.18 0.14 (0.72) (0.43) (1.11) (0.67) (0.76) (1.01) (0.77) (0.65) Attention proxied by Post-Earnings-Announcement-Drift / Earning Surprise (PEAD) PEAD 0.83 0.64 0.68 0.75 0.73 0.72 0.67 (3.96) (3.47) (3.17) (3.30) (3.25) (3.14) (3.09) (2.94) 0.04 0.28 0.40 0.20 (0.53) (0.19) (1.04) (1.12) (1.03) (1.28) (0.66) Attention proxied by the composite index Index 0.60 0.54 0.70 0.69 0.71 0.56 (3.61) (3.26) (3.24) (4.25) (4.17) (4.16) (4.32) (3.54) 0.06 0.13 0.15 (0.36) (0.46) (0.75) (0.70) (0.87)

Sensitivity of Future Profitability to IO and Return Predictive Power of IO Size Exret Ind-adjret Char-adjret 4F 4F + IMC 4F + INV 4F + LIQ 4F + EMI Big 0.46 0.35 0.42 0.53 0.52 0.56 0.41   (2.86) (3.11) (2.70) (3.19) (3.08) (3.12) (3.32) (2.50) Small 0.00 -0.06 0.03 -0.08 -0.07 (-0.03) (-0.61) (0.34) (-0.81) (-0.76) (-0.65) (-0.68) (-0.60) BTM Low 0.25 0.34 0.31 (2.44) (2.35) (2.32) (2.87) (2.79) (2.84) (2.14) High 0.11 0.09 0.16 0.21 (1.38) (0.82) (0.51) (0.68) (0.70) (0.49) (0.92) (0.94) Sensitivity Index 0.27 0.36 0.40 0.44 (2.45) (2.56) (2.52) (2.76) (2.67) (2.69) (2.90) (2.06) 0.05 -0.01 0.07 0.06 (0.36) (0.23) (-0.04) (0.47) (0.42) (0.48) (0.41) (0.75)

Return predictive power of IO not driven by difference in IO spreads. Average IO Firm Age Opacity VU Index IO Rank Young Old High Low 2.97 3.05 3.54 3.61 2.98 3.04 Middle 5.39 5.36 6.37 6.38 10.33 9.32   12.03 11.40 10.38 9.33 Analyst-to-Shareholder PEAD/Earnings Surprise Attention Index 3.08 3.03 3.56 3.43 3.06 5.37 5.82 5.79 9.26 10.06 10.08 10.37 9.75 9.57 Size Book-to-Market Sensitivity Index Big Small 3.36 2.95 3.11 2.91 5.35 5.38 8.48 10.13 9.90 9.61 9.67 9.99 Return predictive power of IO not driven by difference in IO spreads.

Average Size (in Millions) Firm Age Opacity VU Index IO Rank Young Old High Low 532 1754 1233 2290 565 1679 Middle 872 6287 4224 9182 1048 6062 581 3356   2066 4403 704 3100 Analyst-to-Shareholder PEAD/Earnings Surprise Attention Index 2073 861 3320 1994 1255 1589 7873 1568 8554 5448 4546 5280 3777 1025 4549 2210 2161 2589 Size Book-to-Market Sensitivity Index Big Small 10413 131 1550 707 2016 125 20405 146 6101 1885 6542 155 15578 136 2699 1007 3228 122 Return predictive power of IO not driven by small firms.

IE vs. IO Average IO IE Rank IO Exret Ind-adjret Char-adjret 4F 4F + IMC 4F + INV 4F + LIQ 4F + EMI L High-Low 0.14 0.12 0.05 0.16 0.21 0.13   (0.66) (0.71) (0.24) (0.78) (0.79) (0.99) (0.61) M 0.08 0.18 0.22 0.20 0.28 0.15 (0.42) (0.77) (0.95) (1.00) (0.87) (1.22) (0.68) H 0.75 0.63 0.67 0.58 0.55 0.64 0.53 0.69 (2.43) (2.20) (2.12) (2.02) (1.90) (2.21) (1.76) (2.31) Average IO IO Rank IE Rank L M H H-L 2.94 5.36 9.69 6.74 3.32 5.34 9.02 5.70 3.26 5.43 9.96 6.71

Fama-MacBeth Regressions (I)   IO Control Variables   Model 1 0.16 BTM, size, momentum, institutional ownership, illiquidity, short-term return reversal (7.22) Model 2 0.08 Above variables plus innovative efficiency, patents-to-assets, R&D/ME, ROA, investment, net stock issuance, idiosyncratic volatility, skewness, sales diversity  (2.93)

Fama-MacBeth Regressions (II)   Firm Age Opacity VU Index IO Young Old High Low High-Low Slope 0.12 0.06 0.17 -0.01 0.04 0.13 t-stat (2.56) (1.90) (3.16) (-0.21) (4.62) (1.85) (3.15) Analyst-to-Shareholder PEAD/Earnings Surprise Attention Index Low-High 0.08 0.02 0.11 -0.02 (1.99) (0.46) (1.74) (0.64) (2.81) (-0.44) (2.41) Size Book-to-Market Sensitivity Index Big Small 0.22 0.05 (3.03) (2.90) (0.89) (3.47) (1.30) (2.29) IO effect much stronger among firms with more valuation uncertainty, lower investor attention, and higher sensitivity of profitability to IO.

Additional Robustness Tests Fama-French five-factor model (market, size, value, investment, profitability factors) Subperiod analysis Transaction costs Alternative IO measure based on generalized Herfindahl index

Alternative Explanations Risk Information asymmetry Financing constraints Obsolescence Investment-specific technological change

Summary and Conclusion We document a positive relation between firms’ IO and future fundamentals and abnormal returns. Relation stronger among firms with Lower investor attention Higher valuation uncertainty Higher sensitivity of future profitability to IO. Overall, evidence suggests that IO is a useful input for firm valuation, and evidence is consistent with limited investor attention and skepticism of complexity.