Internet Appendix for. Do Stock Markets Catch the Flu? TABLE A.1. Aggregated and Regional Summary Data

Transcription

1 Internet Appendix for Do Stock Markets Catch the Flu? Brian C. McTier, Yiuman Tse, and John K. Wald JOURNAL OF FINANCIAL AND QUANTITATIVE ANALYSIS, Vol. 48, No. 3, June 2013 TABLE A.1 Aggregated and Regional Summary Data This table provides summary statistics in weekly frequencies on the aggregated and regional variables used in this study. Both raw (as collected) and transformed variables are reported. The regions are the nine census regions for which the CDC reports flu data separately. Panel A reports summary statistics for the stock market variables. The sample is drawn from equal-weighted U.S. regional index portfolios formed by aggregating weekly individual NYSE traded stocks over the nine regions from 1998 through Return is the weekly CRSP cum dividend percent return. Turnover is 100 log ( 1 Volume / Shares) +, where Volume refers to the number of shares traded in the given week and Shares equals the average number of shares outstanding during the week. Turnover is the first difference of Turnover. DollarVolume is the weekly dollar volume and NumTrades is the weekly number of trades. LogDVol and LogTrades are the first differences of the logarithm of DollarVolume and the logarithm of NumTrades, respectively. Panel B reports summary statistics for the regional flu variables. The flu variables are the number of flu cases that test positive in a given week. HRegionFlu is the number of positive cases in the given CDC region; NonHRegionFlu is the number of positive cases in all U.S. regions except the region where the company is headquartered. LogHRegionFlu and LogNonHRegionFlu are the percentage change in the corresponding raw flu variables in the subsequent week. This is measured as the change in the log of one plus the raw flu variable. 1

2 Panel A. Aggregated Market Data TABLE A.1 (continued) All Reg. Reg. 1 Reg. 2 Reg. 3 Reg. 4 Reg. 5 Reg. 6 Reg. 7 Reg. 8 Reg. 9 Return Obs Mean Median SD Min Max Turnover Obs Mean Median SD Min Max Turnover Obs Mean Median SD Min Max DollarVolume (billion) Obs Mean Median SD Min Max LogDVol Obs Mean Median SD Min Max NumTrades (thousand) Obs Mean Median SD Min Max

3 TABLE A.1 (continued) All Reg. Reg. 1 Reg. 2 Reg. 3 Reg. 4 Reg. 5 Reg. 6 Reg. 7 Reg. 8 Reg. 9 LogTrades Obs Mean Median SD Min Max Panel B. Regional Flu Data HRegion Flu (hundred) Obs. 4, Mean Median SD Min Max LogHRegionFlu Obs. 4, Mean Median SD Min Max NonHRegion Flu (hundred) Obs. 4, Mean Median SD Min Max LogNonHRegionFlu Obs. 4, Mean Median SD Min Max

4 TABLE A.2 Google Summary Data This table provides summary statistics in weekly frequencies on the regional stock market and Google Flu Trends variables used in this study. Each panel reports data for a subset of the countries, cities, or regions. Both raw (as collected) and transformed variables are reported. Flu and stock market data are reported for the following countries: Argentina MERVAL, Australia S&P ASX200, Austria Austrian Traded, Belgium BEL20, Brazil - IBOVESPA, Bulgaria - SOFIX, Canada S&P TSX Composite, Chile - IPSA, France All Tradable, Germany - DAX, Hungary Hungarian Traded, Japan - Topix, Mexico - IPC, Netherlands AEX General, New Zealand NZX All, Norway OSE All Shares, Peru - IGBVL, Poland - WIG, Russia - MICEX, South Africa JSE Africa, Spain Madrid Index, Sweden OMX Stockholm All Share, Switzerland Swiss Market Index, Ukraine - PFTS, and the United States NYSE Index. Flu and stock market data are also reported for cities/regions: Buenos Aries, Argentina MERVAL; New South Wales, Australia S&P ASX200; Vienna, Austria Austrian Traded Index; Brussels, Belgium BEL20; Sao Paulo, Brazil IBOVESPA; Ontario, Canada S&P TSX Composite; Ile de France, France All Tradable Index; Hessen, Germany DAX; Distrito Federal, Mexico IPC; North Holland, Netherlands AEX General; Lima, Peru IGBVL; Gauteng, South Africa JSE Africa; Madrid, Spain Madrid Index; Zurich, Switzerland Swiss Market Index; and New York City, United States NYSE Index. The upper portion of each panel, labeled Equity Index Data, reports summary statistics for the international market variables. Share Volume is the total index constituent shares traded; Dollar Volume is the total value of the constituent index shares traded; and Return is the weekly cum dividend return. LogSVol and LogDVol are the weekly percentage change in Share Volume and Dollar Volume, respectively, measured as the weekly change in the logarithm of the raw variable. The lower portion of each panel, labeled Google Flu Data, reports summary statistics for the estimated incidence of flu from Google Flu Trends where GoogleFlu is the estimated flu incidence. LogGoogleFlu is defined as the weekly percentage change in GoogleFlu measured as the first difference of the log of GoogleFlu. 4

5 TABLE A.2 (continued) Panel A. Argentina - Buenos Aires Equity Index Data: Argentina Australia Austria Belgium Brazil Brussels Buenos Aires Volume (billion) Obs Mean Median SD Min Max LogSVol Obs Mean Median SD Min Max Dollar Volume (million) Obs Mean Median SD Min Max LogDVol Obs Mean Median SD Min Max Return (%) Obs Mean Median SD Min Max Google Flu Data: Google Flu (hundred): Obs Mean Median SD Min Max LogGoogleFlu: Obs Mean Median SD Min Max

6 TABLE A.2 (continued) Panel B. Bulgaria - Gauteng Bulgaria Canada Chile Distrito Federal France Gauteng Equity Index Data: Volume (billion) Obs Mean Median SD Min Max LogSVol Obs Mean Median SD Min Max Dollar Volume (million) Obs Mean Median SD Min Max LogDVol Obs Mean Median SD Min Max Return (%) Obs Mean Median SD Min Max Google Flu Data: Google Flu (hundred): Obs Mean Median SD Min Max LogGoogleFlu: Obs Mean Median SD Min Max

7 TABLE A.2 (continued) Panel C. Germany - Lima Equity Index Data: Germany Hessen Hungary Ile de France Japan Lima Volume (billion) Obs Mean Median SD Min Max LogSVol Obs Mean Median SD Min Max Dollar Volume (million) Obs Mean , Median , SD Min Max , LogDVol Obs Mean Median SD Min Max Return (%) Obs Mean Median SD Min Max Google Flu Data: Google Flu (hundred): Obs Mean Median SD Min Max LogGoogleFlu: Obs Mean Median SD Min Max

8 TABLE A.2 (continued) Panel D. Madrid - North Holland Equity Index Data: Madrid Mexico Netherlands New S Wales New York City New Zealand North Holland Volume (billion) Obs Mean Median SD Min Max LogSVol Obs Mean Median SD Min Max Dollar Volume (million) Obs Mean Median SD Min Max LogDVol Obs Mean Median SD Min Max Return (%) Obs Mean Median SD Min Max Google Flu Data: Google Flu (hundred): Obs Mean Median SD Min Max LogGoogleFlu: Obs Mean Median SD Min Max

9 TABLE A.2 (continued) Panel E. Norway - South Africa Equity Index Data: Norway Ontario Peru Poland Russia Sao Paulo South Africa Volume (billion) Obs Mean Median SD Min Max LogSVol Obs Mean Median SD Min Max Dollar Volume (million) Obs Mean Median SD Min Max LogDVol Obs Mean Median SD Min Max Return (%) Obs Mean Median SD Min Max Google Flu Data: Google Flu (hundred): Obs Mean Median SD Min Max LogGoogleFlu: Obs Mean Median SD Min Max

10 TABLE A.2 (continued) Panel F. Spain - Zurich Equity Index Data: Spain Sweden Switzerland Ukraine United States Vienna Zurich Volume (billion) Obs Mean Median SD Min Max LogSVol Obs Mean Median SD Min Max Dollar Volume (million) Obs Mean Median SD Min Max LogDVol Obs Mean Median SD Min Max Return (%) Obs Mean Median SD Min Max Google Flu Data: Google Flu (hundred): Obs Mean Median SD Min Max LogGoogleFlu: Obs Mean Median SD Min Max

11 TABLE A.3 CDC Lag Coefficient Tests This table reports coefficients for pooled multivariate regressions using robust standard errors with firm-level clustering. The first row of Panel A repeats the regression reported in the first column of Table 4 with lag LogUSFlu as an additional independent variable and the second row of Panel A repeats the regression reported in the second column of Table 4 with lag LogNYFlu and lag LogNonNYFlu as additional independent variables. The dependent variable is LogDVol, defined as the weekly percentage change in dollar volume measured as the change in the logarithm of dollar volume. The rows of Panels B and C repeat the regressions reported in the third and fourth columns of Table 4 with the addition of the lag flu variables. The dependent variable in Panel B is Turnover, defined as the weekly change in turnover, 100 log ( 1 Volume / Shares) +, where Volume refers to the number of shares traded in the given week and Shares equals the average number of shares outstanding during the week. The dependent variable in Panel C is LogTrades, defined as the weekly percentage change in the number of trades. The rows of Panels D, E, and F repeat the regressions reported in the third and fourth columns of Tables 5, 6, and 7 with the addition of the lag flu variables. The dependent variable in Panel D is LogVolatility, calculated as the weekly change in the logarithm of the average unsigned 10 minute return over the week (see Andersen and Bollerslev, 1998 and Andersen et. al., 2001). The dependent variable in Panel E is Spread, defined as ( Spread ) 100 t Spreadt 1, where Spread is the average weekly time-weighted effective percentage spread calculated as 100 times the difference between the trade price and the midpoint of the active quote divided by the midpoint of the active quote weighted by the time between trades. The dependent variable in Panel F is Return, defined as the weekly CRSP cum dividend percentage return. The flu variables are the percentage change in the number of flu cases in the subsequent week. This is measured as the change in the logarithm of the number of flu cases plus one. β Flu,t+1 (US) is the coefficient on the U.S. flu variable, LogUSFlu and β Flu,t+1 (NY) is the coefficient on LogNYFlu. β Flu,t is the coefficient on the lag flu variable: LogUSFlu in the second row of each panel and LogNYFlu in the third row of each panel. Column 6 reports the sum of the coefficients on the flu variable and lag flu variable, β Flu,t + β Flu,t+1. As in the 11

12 originally reported regressions, dummy variables for the week of the year and the calendar year are included to control for time effects and weather controls are included as in Saunders (1993). The equation fit in the first row of each Panel is:, = +, +, , Where are LogDVol, LogTrades, Turnover, LogVolatility, Spread, and Return. are the dummy variables for Many Clouds and Few Clouds; WDummy are the dummy variables for the week of the year; YDummy are the yearly dummies, and DDummy is a dummy variable equal to one after decimalization. Controls are the controls included in the originally reported regressions. Turnover is the control variable included in the regression in Panel D;. LogDVol, LogVolatility, 1/P, and the first-difference LogMV are the controls included in the regression in Panel E; and OIB, Lagged OIB, and Spread are the controls included in the regression reported in Panel F. The second row of each panel replaces Log with and and their lag values. Robust t-statistics are reported in parentheses below the coefficients. The P-value from an F-Test of the linear hypothesis that the sum of the coefficients on flu and next week s flu is zero is reported in the curly brackets below the summed coefficients reported in column 6. *, **, and *** refer to significance at the 5%, 1%, and 0.1% levels, respectively. 12

13 TABLE A.3 (continued) β Flu,t+1 (US) β Flu,t+1 (NY) β Flu,t R 2 Obs. β Flu,t + β Flu,t+1 Original Coef. Panel A. LogDVol *** *** ,209, *** *** (-10.46) (18.61) {0.0000} (-9.23) *** *** ,209, *** *** (-30.99) (6.79) {0.0000} (-29.51) Panel B. Turnover *** *** ,209, *** (-5.20) (4.98) {0.1375} (-5.06) *** * ,209, *** *** (-13.59) (2.49) {0.0000} (-12.64) Panel C. LogTrades *** *** ,209, *** *** (-8.73) (30.13) {0.0000} (-6.44) *** *** ,209, *** *** (-38.01) (5.88) {0.0000} (-35.13) Panel D. LogVolatility ** *** ,203, (2.66) (-3.86) {0.2215} (1.93) *** *** ,203, ** *** (-9.54) (6.23) {0.0025} (-12.05) Panel E. Spread *** ,203, *** *** (3.75) (0.27) {0.0001} (4.96) *** ,203, *** *** (4.78) (0.55) {0.0000} (3.33) Panel F. Return *** *** ,205, *** *** (-15.67) (6.41) {0.0000} (-16.18) *** ,208, *** *** (-7.53) (0.92) {0.0000} (-7.27) 13

14 TABLE A.4 Google Lag Coefficient Tests This table reports coefficients for multivariate regressions using robust standard errors and multivariate panel regressions using robust standard errors clustered by country or city/region. The All Countries Panel includes flu and stock market data for Argentina, Australia, Austria, Belgium, Brazil, Bulgaria, Canada, Chile, France, Germany, Hungary, Japan, Mexico, Netherlands, New Zealand, Norway, Peru, Poland, Russia, South Africa, Spain, Sweden, Switzerland, Ukraine, and the United States. The All Cities/Regions Panel includes flu and stock market data for Buenos Aries, New South Wales, Vienna, Brussels, Sao Paulo, Ontario, Ile de France, Hessen, Distrito Federal, North Holland, Lima, Gauteng, Madrid, Zurich, and New York City. Each row of the table repeats the regressions reported in Table 3 with next week s GoogleFlu as an additional independent variable. Panel A repeats the regressions reported in first column of Table 3 with the addition of the next week s flu variable and dependent variable, LogSVol, defined as the weekly percentage change in index constituent shares traded measured as the weekly change in the logarithm of index share volume. Panels B and C repeat the regressions reported in the second and third columns of Table 3 with the addition of the next week s flu variable. The dependent variable in Panel B is LogDVol, defined as the weekly percentage change in the value of index constituent shares traded measured as the weekly change in the logarithm of the value of index share volume. The dependent variable in Panel C is Return, measured as the weekly cum dividend return. The flu variables are the weekly percentage change in estimated flu incidence from Google Flu Trends. This is measured as the first difference of the logarithm of the weekly estimate of flu incidence in the country or city/region. LogCountryFlu is the percentage change in each country as a whole, LogCityRegionalFlu is the percentage change in the cities/regions where the main exchange is located, LogUSFlu is the percentage change in the U.S. as a whole, LogNYNJFlu is the percentage change in the combined New York and New Jersey region, and LogNYCityFlu is the percentage change in New York City. β Flu,t is the coefficient on the flu variable, LogGoogleFlu. β Flu,t+1 is the coefficient on next week s flu variable. Column 6 reports the sum of the coefficient on the flu variable and next week s flu variable, β Flu,t + β Flu,t+1. Dummy variables for the calendar year are included to control for time effects. 14

15 The equation fit in each row is:, = +, +, + +, Where are LogSVol, LogDVol, and Return. YDummy are the yearly dummies. Robust t-statistics are reported in parentheses below the coefficients. The P-value from an F-Test of the linear hypothesis that the sum of the coefficients on flu and next week s flu is zero is reported in the curly brackets below the summed coefficients reported in column 6. *, **, and *** refer to significance at the 10%, 5%, and 1% levels, respectively. 15

16 TABLE A.4 (continued) β Flu,t β Flu,t+1 R 2 Obs. β Flu,t + β Flu,t+1 Original Coef. Panel A. LogSVol All Countries: LogCountryFlu * * , ** (-2.51) (2.13) {0.2104} (-2.29) Northern Hemisphere Countries: LogCountryFlu * ** , * (-2.54) (2.75) {0.6592} (-1.82) Southern Hemisphere Countries: LogCountryFlu , (-0.82) (-0.59) {0.0610} (-1.14) US Flu: LogCountryFlu ** ** *** (-3.23) (2.78) {0.1555} (-2.72) All Cities/Regions: LogCityRegionalFlu ** , * *** (-2.89) (1.82) {0.0280} (-2.92) Northern Hemisphere Cities/Regions: LogCityRegionalFlu * , ** (-2.45) (1.46) {0.0610} (-2.43) Southern Hemisphere Cities/Regions: LogCityRegionalFlu ** * , * *** (-2.82) (2.13) {0.0196} (-2.81) NY/NJ Flu: LogCityRegionalFlu ** * ** (-2.86) (2.30) {0.0978} (-2.51) NY City Flu: LogCityRegionalFlu ** *** (-2.92) (1.25) {0.1335} (-2.89) 16

17 TABLE A.4 (continued) β Flu,t β Flu,t+1 R 2 Obs. β Flu,t + β Flu,t+1 Original Coef. Panel B. LogDVol All Countries: LogCountryFlu ** * , * *** (-2.64) (2.09) {0.0418} (-2.67) Northern Hemisphere Countries: LogCountryFlu * * , ** (-2.39) (2.19) {0.1462} (-2.14) Southern Hemisphere Countries: LogCountryFlu , (-1.18) (0.42) {0.1499} (-1.32) US Flu: LogCountryFlu *** ** *** (-3.34) (2.96) {0.1499} (-2.74) All Cities/Regions: LogCityRegionalFlu ** * , ** *** (-3.22) (2.29) {0.0030} (-3.39) Northern Hemisphere Cities/Regions: LogCityRegionalFlu ** , ** *** (-2.73) (1.76) {0.0096} (-2.91) Southern Hemisphere Cities/Regions: LogCityRegionalFlu *** *** , * *** (-4.54) (3.77) {0.0129} (-3.63) NY/NJ Flu: LogCityRegionalFlu ** * ** (-2.87) (2.41) {0.0846} (-2.47) NY City Flu: LogCityRegionalFlu ** *** (-2.92) (1.13) {0.1299} (-2.89) 17

18 TABLE A.4 (continued) β Flu,t β Flu,t+1 R 2 Obs. β Flu,t + β Flu,t+1 Original Coef. Panel C. Return All Countries: LogCountryFlu , *** (-1.62) (-0.49) {0.0574} (-2.80) Northern Hemisphere Countries: LogCountryFlu , ** (-1.35) (0.30) {0.2829} (-2.20) Southern Hemisphere Countries: LogCountryFlu ** , ** (-1.60) (-2.60) {0.0052} (-1.63) US Flu: LogCountryFlu *** (0.36) (-0.86) {0.0001} (-0.32) All Cities/Regions: LogCityRegionalFlu , (1.35) (-0.53) {0.6339} (0.24) Northern Hemisphere Cities/Regions: LogCityRegionalFlu , (0.63) (0.85) {0.0663} (0.34) Southern Hemisphere Cities/Regions: LogCityRegionalFlu *** , * (1.92) (-4.18) {0.0117} (0.60) NY/NJ Flu: LogCityRegionalFlu *** (0.75) (-0.98) {0.0000} (0.28) NY City Flu: LogCityRegionalFlu *** (0.47) (-0.87) {0.0000} (0.17) 18