Efecto de las variables climáticas 29

An alternative way to examine the conditional characteristic effects is to form equally weighted long-short portfolios on the basis of firm characteristics. Besides, this ap-

62

Cross-Sectional Variations in Stock Returns with Respect to Firm Opacity and Investor Sentiment

Table 3.7 Conditional Alphas at Given Levels of Investor Sentiment from an Expanded Risk Factor Model

This table reports the parameter estimates for conditional alphas with associated p-values, for various percentiles of sentiment portfolios ranging from the 5th to the 95th across firm-characteristic portfolios: Rj,t=αj,0+βj,mRm,t+βj,SM BRSM B,t+βj,HM LRHM L,t+βj,U M DRU M D,t+βj,sentSent⊥t−1+ej,t; where the conditioning information instrument, Sent⊥_j,t−1,is known at the beginning of each investment interval and both the portfolio excess return,Rj,t, and the market excess return,Rm,t, are contemporaneously measured over the subsequent period. Hence, assuming that the past sentiment is available to the market, the resultant conditional alpha is computed asαj,t=αj,0+αj,sentSent⊥j,t−1. D95−5 indicating the alpha differential between the 95th and 5th percentile of

sentiment. * and ** indicate that the coefficient estimate is significant at the 95% and 99% level, respectively.

Percentile Port1 Port2 Port3 Port4 Port5 Port6 Port7 Port8 Port9 Port10 σ 5 0.3557 0.3755 0.3886 0.3980 0.3658 0.3507 0.4247 0.4201* 0.5185* 0.6082* 25 0.3766 0.3936 0.4060 0.4116 0.3724 0.3491 0.3817 0.3555* 0.4087* 0.4554* 50 0.3938 0.4085 0.4204 0.4229 0.3779 0.3478 0.3461 0.3022* 0.3180* 0.3292* 75 0.4148 0.4266 0.4378 0.4365 0.3846 0.3462 0.3030 0.2374* 0.2079* 0.1759* 95 0.4596 0.4653 0.4752 0.4657 0.3988 0.3428 0.2106 0.0989* -0.0277* -0.1521* D95−5 0.1039 0.0897 0.0866 0.0677 0.0331 -0.0079 -0.2141 -0.3211* -0.5462* -0.7603* Size 5 0.4990* 0.4314* 0.4181* 0.3596 0.2995 0.2240 0.1502 0.0984 0.0619 0.0244 25 0.3984* 0.3406* 0.3216* 0.2722 0.2306 0.1737 0.1122 0.0721 0.0442 0.0165 50 0.3153* 0.2656* 0.2419* 0.2001 0.1736 0.1321 0.0808 0.0504 0.0296 0.0099 75 0.2143* 0.1745* 0.1450* 0.1125 0.1044 0.0817 0.0427 0.0241 0.0118 0.0020 95 -0.0016* -0.0203* -0.0621* -0.0749 -0.0436 -0.0263 -0.0387 -0.0323 -0.0262 -0.0150 D95−5 -0.5006* -0.4518* -0.4801* -0.4345 -0.3432 -0.2503 -0.1889 -0.1307 -0.0882 -0.0394 E 5 0.5597* 0.6931* 0.4988 0.5746* 0.4372 0.4735 0.3999 0.4114 0.3113 0.3594 25 0.4208* 0.5640* 0.3817 0.4642* 0.3483 0.3868 0.3189 0.3484 0.2632 0.3325 50 0.3061* 0.4574* 0.2851 0.3730* 0.2749 0.3152 0.2520 0.2964 0.2235 0.3103 75 0.1667* 0.3279* 0.1676 0.2622* 0.1857 0.2282 0.1707 0.2333 0.1752 0.2834 95 -0.1314* 0.0509* -0.0836 0.0252* -0.0051 0.0422 -0.0031 0.0981 0.0720 0.2256 D95−5 -0.6910* -0.6422* -0.5824 -0.5494* -0.4423 -0.4313 -0.4030 -0.3133 -0.2393 -0.1338 D 5 0.4894* 0.5908* 0.4965* 0.4100 0.5141 0.3923 0.4229 0.4044 0.3608 0.3200 25 0.4217* 0.5152* 0.4329* 0.3508 0.4584 0.3442 0.4052 0.4053 0.3674 0.3247 50 0.3658* 0.4527* 0.3803* 0.3019 0.4124 0.3045 0.3906 0.4061 0.3729 0.3286 75 0.2978* 0.3768* 0.3165* 0.2426 0.3565 0.2562 0.3728 0.4071 0.3796 0.3334 95 0.1525* 0.2146* 0.1801* 0.1156 0.2370 0.1530 0.3348 0.4091 0.3938 0.3436 D95−5 -0.3369* -0.3762* -0.3164* -0.2944 -0.2770 -0.2393 -0.0882 0.0047 0.0331 0.0236 PPE 5 0.2532* 0.1902* 0.2332* 0.2629 0.2737 0.2810 0.2672 0.2880 0.2290 0.3466 25 0.1371* 0.1060* 0.1443* 0.1677 0.1940 0.2082 0.2108 0.2377 0.1876 0.3137 50 0.0412* 0.0365* 0.0709* 0.0890 0.1281 0.1481 0.1643 0.1961 0.1534 0.2865 75 -0.0753* -0.0479* -0.0183* -0.0065 0.0481 0.0751 0.1078 0.1457 0.1118 0.2535 95 -0.3245* -0.2285* -0.2091* -0.2109 -0.1230 -0.0811 -0.0130 0.0377 0.0228 0.1829 D95−5 -0.5777* -0.4187* -0.4423* -0.4738 -0.3967 -0.3621 -0.2802 -0.2503 -0.2062 -0.1637 RD 5 0.2267 0.2389 0.2882 0.2215 0.2096 0.2490 0.5396 0.4642 0.6054 0.5902 25 0.1606 0.1579 0.1999 0.1484 0.1447 0.1573 0.4155 0.3523 0.4832 0.4877 50 0.1060 0.0910 0.1270 0.0880 0.0912 0.0815 0.3131 0.2597 0.3824 0.4030 75 0.0396 0.0097 0.0384 0.0147 0.0261 -0.0106 0.1887 0.1474 0.2598 0.3002 95 -0.1023 -0.1641 -0.1510 -0.1421 -0.1131 -0.2075 -0.0775 -0.0930 -0.0023 0.0802 D95−5 -0.3290 -0.4030 -0.4392 -0.3636 -0.3227 -0.4565 -0.6171 -0.5572 -0.6076 -0.5100 BE/ME 5 -0.0759 -0.0697* 0.0119 0.0067 0.0575 0.0323 -0.1100 -0.0568 0.0163 -0.0520* 25 -0.2166 -0.1703* -0.2552 -0.1976 -0.2678 -0.2818 -0.2189 -0.3250 -0.5097 -0.4233* 50 -0.2733 -0.2178* -0.2921 -0.2268 -0.2932 -0.3168 -0.2861 -0.3932 -0.5855 -0.5056* 75 -0.3422 -0.2756* -0.3368 -0.2624 -0.3240 -0.3593 -0.3677 -0.4761 -0.6776 -0.6056* 95 -0.4896 -0.3992* -0.4326 -0.3384 -0.3898 -0.4503 -0.5422 -0.6533 -0.8745 -0.8195* D95−5 -0.4137 -0.3295* -0.4445 -0.3451 -0.4473 -0.4826 -0.4322 -0.5965 -0.8908 -0.7675* SG 5 -0.5431* -0.4192* -0.3198 -0.2992 -0.2781 -0.2468 -0.3135 -0.3699 -0.4336 -0.4423 25 0.4904* 0.3892* 0.3189 0.4275 0.3434 0.3162 0.2972 0.3599 0.4047 0.4737 50 0.4073* 0.3267* 0.2747 0.4066 0.3154 0.2932 0.2515 0.3073 0.3404 0.4178 75 0.3063* 0.2508* 0.2211 0.3812 0.2814 0.2653 0.1959 0.2435 0.2623 0.3498 95 0.0904* 0.0886* 0.1063 0.3268 0.2088 0.2055 0.0771 0.1071 0.0953 0.2045 D95−5 0.6335* 0.5077* 0.4261 0.6260 0.4868 0.4523 0.3905 0.4770 0.5289 0.6468

3.6 Empirical Results 63

proach also helps re-investigate whether investor sentiment is systematically priced in portfolio returns. Similar to what has been done by Baker and Wurgler (2006), to form a long-short portfolio, I long stocks with high values and then short on stocks with low values.

Table 3.8 reports the empirical results of long-short regressions on investor senti- ment. The results show that the coefficient estimates of investor sentiment for size, risk, earnings and dividends are statistically significant at the 1% level. Moreover, the signs for the parameter estimates of these portfolios strictly follow the hypothesis that the relationship is negative for size and risk, while positive for earnings and divi- dends. The magnitudes of the coefficient for predicting returns of volatility portfolio, for example, demonstrates that one unit increase in sentiment results in a -0.8295% (unorthogonalised) lower monthly return on the high minus low volatility portfolio. In terms of tangibility, the portfolio for PPE shows significant parameter estimates (at the 10% significance level) with expected signs; but either regression does not support the impact of investor sentiment on returns for the RD portfolio. In addition to the findings described above, the most important finding from Table 3.6 is the predictive power of investor sentiment on book-to-market and sales growth portfolios. Specifi- cally, the results from Panel D, E and F suggest three distinct impacts of sentiment on subsequent portfolio returns. First, investor sentiment barely has any predictive power on returns of high minus low portfolios for the book-to-market portfolio. For instance, the parameter estimate βj,sentSentt−1 for the high minus low book-to-market

portfolio is 0.0032 (with a p-value of 0.82), indicating that neither is statistically significant at any acceptable significance level. This pattern is strongly consistent across all parameter estimates in Panel D. Second, Panel E and F display the sentiment performance on the relative overvalued and undervalued portfolios, respectively.19 Taking the book-to-market portfolio as an example, the coefficient estimates for the medium minus low book-to-market portfolio is positive but turns negative for the high minus medium portfolio. Additionally, the corresponding p-values indicate that the impact is only statistically significant for undervalued portfolios. For example, the average p-value for the parameter estimates of the medium minus low book-to-market portfolio is 0.16, while for the high minus low portfolio, this is approximately 0.07. The absolute magnitudes of coefficient estimates are also larger for the undervalued

19_{As revealed by results in Section 3.6.2, for both book-to-market and sales growth portfolios,}

portfolios in the middle are less affected by investor sentiment than portfolios at the extremes. Hence, the construction in Panels E and F helps identify the predictive power of investor sentiment on each extreme of the portfolio.

64

Cross-Sectional Variations in Stock Returns with Respect to Firm Opacity and Investor Sentiment group of portfolios. The coefficient estimates for the sales growth portfolio suggest a similar pattern. Hence, the test results from Panels D, E and F indicate that within the sample period, investor sentiment has a comparatively strong predictive power on subsequent returns of undervalued portfolios relative to overvalued stocks. This outcome suggests that stocks with high book-to-market ratios or low growth rates tend to be more sensitive to investor sentiment. In contrast to Baker and Wurgler’s (2006) argument that growth stocks are more prone to investor sentiment, my findings

indicate an opposite direction of the impact.