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The choice of industrial classification scheme can determine the outcomes of empirical research (Bhojraj, Lee, and Oler (2003)). Additionally, the returns of industry portfolios comprising a few firms or a few dominant firms may merely represent idiosyncratic risk. The results may therefore misestimate the effect of investor sentiment predictability on industry values. For additional robustness, the analysis compares results for the Fama and French industries with results for alternative sector and industry groups. Specifically, the analysis maps the Fama and French 49 industry portfolios to the Kacperczyk, Sialm, and Zheng (2005) and GICS sector and industry classifications. Kacperczyk, Sialm, and Zheng (2005) map the Fama and French 48

extra software industry included in the Fama and French 49 industry classification to the Kacperczyk, Sialm, and Zheng (2005) business equipment and services sector. The analysis also uses the GICS 10 sector and 24 industry mappings. Analysts widely follow the GICS classification. Bhojraj, Lee, and Oler (2003) find that intra-industry return correlations are higher for the GICS classification than other popular industry classifications, such as the Standard Industrial Classification (SIC). Table 2.20 details the mapping of the original Fama and French 49 industry portfolios to the Kacperczyk, Sialm, and Zheng (2005) and GICS sector and industry portfolios.

Table 2.20 Alternative sector and industry mappings

Notes: Table 2.20 provides a mapping of the Fama and French 49 industry portfolios to Kacperczyk, Sialm, and Zheng (2005) 10 sector, GICS 10 sector, and GICS 24 industry portfolios.

Kacperczyk, Sialm, Zheng 10 Sectors

Group Description Group Description Group Description Group Description

01 Agriculture 01 Consumer Non-Durable 30 Consumer Staples 3020 Food, Beverages, & Tobacco

02 Food Products 01 Consumer Non-Durable 30 Consumer Staples 3010 Food & Staples Retailing

03 Candy & Soda 01 Consumer Non-Durable 30 Consumer Staples 3020 Food, Beverages, & Tobacco

04 Beer & Liquor 01 Consumer Non-Durable 30 Consumer Staples 3020 Food, Beverages, & Tobacco

05 Tobacco Products 01 Consumer Non-Durable 30 Consumer Staples 3020 Food, Beverages, & Tobacco

06 Recreation 02 Consumer Durable 25 Consumer Discretionary 2520 Consumer Durables & Apparel

07 Entertainment 01 Consumer Non-Durable 25 Consumer Discretionary 2540 Media

08 Printing & Publishing 01 Consumer Non-Durable 25 Consumer Discretionary 2540 Media

09 Consumer Goods 02 Consumer Durable 25 Consumer Discretionary 2530 Consumer Services

10 Apparel 01 Consumer Non-Durable 25 Consumer Discretionary 2520 Consumer Durables & Apparel

11 Healthcare 03 Healthcare 35 Healthcare 3510 Healthcare

12 Medical Equipment 03 Healthcare 35 Healthcare 3510 Healthcare

13 Pharmaceutical 03 Healthcare 35 Healthcare 3520 Pharmaceuticals

14 Chemicals 04 Manufacturing 15 Materials 1510 Materials

15 Rubber & Plastic 04 Manufacturing 25 Consumer Discretionary 2550 Retailing

16 Textiles 01 Consumer Non-Durable 25 Consumer Discretionary 2520 Consumer Durables & Apparel

17 Construction Material 04 Manufacturing 15 Materials 1510 Materials

18 Construction 04 Manufacturing 25 Consumer Discretionary 2550 Retailing

19 Steel Works 04 Manufacturing 15 Materials 1510 Materials

20 Fabricated Products 04 Manufacturing 20 Industrials 2010 Capital Goods

21 Machinery 04 Manufacturing 20 Industrials 2010 Capital Goods

22 Electrical Equipment 04 Manufacturing 20 Industrials 2010 Capital Goods

23 Automobiles & Truck 02 Consumer Durable 25 Consumer Discretionary 2510 Automobiles & Components

24 Aircraft 04 Manufacturing 20 Industrials 2010 Capital Goods

25 Shipbuilding & Railroad 04 Manufacturing 20 Industrials 2010 Capital Goods

26 Defence 04 Manufacturing 20 Industrials 2010 Capital Goods

27 Precious Metals 05 Energy 15 Materials 1510 Materials

28 Mining 05 Energy 15 Materials 1510 Materials

29 Coal 05 Energy 10 Energy 1010 Energy

30 Petroleum & Natural 05 Energy 10 Energy 1010 Energy

31 Utilities 06 Utilites 55 Utilities 5510 Utilities

32 Communication 07 Telecom 50 Telecommunication Services 5010 Telecommunication Services

33 Personal Services 01 Consumer Non-Durable 25 Consumer Discretionary 2530 Consumer Services

34 Business Services 08 Business Equipment & Services 20 Industrials 2020 Commercial Services & Supplies 35 Computers 08 Business Equipment & Services 45 Information Technology 4520 Technology Hardware & Equipment 36 Computer Software 08 Business Equipment & Services 45 Information Technology 4510 Software & Services

37 Electronic Equipment 08 Business Equipment & Services 45 Information Technology 4530 Semiconductors & Equipment 38 Measuring & Control 08 Business Equipment & Services 45 Information Technology 4520 Technology Hardware & Equipment

39 Business Supplies 04 Manufacturing 20 Industrials 2020 Commercial Services & Supplies

40 Shipping Containers 04 Manufacturing 20 Industrials 2030 Transportation

41 Transportation 04 Manufacturing 20 Industrials 2030 Transportation

42 Wholesale 09 Wholesale & Retail 25 Consumer Discretionary 2550 Retailing

43 Retail 09 Wholesale & Retail 25 Consumer Discretionary 2550 Retailing

44 Restaurants & Hotels 09 Wholesale & Retail 25 Consumer Discretionary 2530 Consumer Services

45 Banking 10 Finance 40 Financials 4010 Banks

46 Insurance 10 Finance 40 Financials 4030 Insurance

47 Real Estate 10 Finance 40 Financials 4040 Real Estate

48 Trading 10 Finance 40 Financials 4020 Diversified Financials

49 Miscellaneous 04 Manufacturing 99 Miscellaneous 9999 Miscellaneous

Table 2.21 reports investor sentiment predictability of alternative sector and industry portfolio returns. Equation 2.2 runs a regression of excess industry returns on a constant,

investor sentiment, and the market-risk premium. The table reports the a1 regression

coefficients from Equation 2.2 for the indicated k-week lags. Bold indicates statistical significance of 10 percent or greater estimated with White (1980) standard errors. The bottom two rows of the table report the total number of statistically significant coefficients for all sector and industry groups. The results reported in Table 2.21 compare directly with results previously reported for the Fama and French 49 industries in Table 2.4. Results for investor sentiment predictability of alternative industry returns remain fundamentally unaltered from the previous analysis. All sector and industry groups have significantly positive predictability at a one-week lag. Predictability at 8-week and 13-week lags remains mostly negative. Longer-term predictability at 26 and 52 weeks is almost non-existent. Analysis of alternative industry classifications continues to support the main results.

Table 2.21 Investor sentiment predictability using alternative industries

Notes: Table 2.21 reports the a1 slope coefficients estimated with Equation 2.2. The analysis runs a regression of excess sector/industry returns on a constant, the indicated sentiment measures at different k-week lags, and the market-risk premium. The table reports results for sector and industry groups formed by mapping the Fama and French 49 industries alternatively to the Kacperczyk, Sialm, and Zheng (2005), GICS sector and GICS industry classifications, as Table 2.20 details. Sentiment measures are from the American Association of Independent Investors (AAII), Investors Intelligence (II), and Baker and Wurgler (BW). Bold indicates 10 percent or greater statistical significance estimated with White (1980) standard errors.