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27 EM151010 2016 1 18

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1 4 2 6 3 8 4 10 5 12 5.1.......................................... 12 5.2 Comtemporary regression................................... 13 5.3........................................ 15 6 20 6.1............................................... 20 6.2........................................... 20 20 A 23 B : 69 32 1

A.1 textream ( : ).......... 23 A.2 textream ( )........................... 24 A.3 textream ( )........................... 24 2

A.1 insample accuracy(c=buy, Hold or Sell)........................... 25 A.2 out of sample accuracy(3-fold cross validation, C=Buy, Hold or Sell)........... 25 A.3 out of sample accuracy(4-fold cross validation, C=Buy, Hold or Sell)........... 25 A.4 insample accuracy(c=buy or Sell).............................. 25 A.5 out of sample accuracy(3-fold cross validation, C=Buy or Sell).............. 26 A.6 out of sample accuracy(4-fold cross validation, C=Buy or Sell).............. 26 A.7 ( ):................................. 26 A.8 ( : Large)................................ 27 A.9 ( : Mid)................................. 27 A.10 ( : Small)................................ 27 A.11 (Large)................................... 28 A.12 (Mid).................................... 28 A.13 (Small)................................... 28 A.14 ( ):............................... 29 A.15 ( ):................................. 29 A.16 ( )............................... 30 A.17 ( )................................ 31 3

1 SNS( ) SNS 1996 2001 ( 1/7 ) SNS SNS SNS SNS ( ) SNS SNS 2 textream Twitter 2 1999 5 1 2 1 ( ) 2 1 Twitter textream 1998 7 Yahoo! 2013 3 textream 2 2 Yahoo! Japan ID 2 textream ( textream ) 4

textream 2 Twitter 2006 7 140 web Twitter 2 textream ( ) ( ) ( ) ( ) Twitter 2 textream ( ) 2 textream Twitter Twitter 2 textream textream textream 2 3 4 5 6 5

2 Wysocki(1999) Wysocki(1999) Yahoo! 1997 3478 ROE NYSE Tumarkin and Whitelaw(2001) 1999 4 2002 2 Raging Bull Antweiler and Frank(2004) 45 150 Yahoo! Raging Bull Sabherwal et al.(2011) 2005 6 2006 6 64 Leung and Ton(2015) 2142 (HotCopper) 2003 1 2008 12 250 Fama and Macbeth(1992) Mackinlay(1997) (2005) (2008) (2012) (2005) (2005) Yahoo! 2003 (2008) Yahoo! 50 (2005-2006 ) 110 (2012) Yahoo! 1 1501 (2003-2008 ) 390 Fama and French(1992) 6

Tetlock(2007) Tetlock et al.(2008) Tirunillia and Tellis(2012) Yu et al.(2013) (2013) Tetlock(2007) 1984 1999 Wall Street Journal column Tetlock et al.(2008) S&P500 1980 2004 35 Tirunillia and Tellis(2012) 15 Amazon.com Eopinion.com Yahoo!shopping web 2005 6 2010 1 35 Yu et al.(2013) 2011 7 1 9 30 6 824 Twitter 52747 (2013) 1986 2010 22 25 17 1 6 7 12 1: 2: 3: 1,2 Leung and Ton(2015) Antweiler and Frank(2004) Sabherwal et al.(2011) 3 7

3 (Naive Bayes classifier) Antweiler and Frank(2004), Das and Chen(2007), Sabherwal et al.(2011), Leung and Ton(2015) (corpus) (training data) 3000 948 1428 624 W k k K (Message ) Message = {W k } K k=1 (3.1) 6 C C W k P (W k C) = m kc /n c (3.2) m kc C W k n c C C {,, } C {, } 2 P (C Message) = P (C) P (Message C) P (Message) = P (C) K k=1 P (W k C) P (Message) (3.3) (Naive) (Message) P (C Message) C P (Message) C P (C) K k=1 P (W k C) C P (W k C) = 0 P (C) K k=1 P (W k C)=0 (3.2) P (W k C) = n c/n + m kc n c /n + n c (3.4) 8

n Mecab Mecab Mecab B 69 B 69 2 10 12, 27 30 31 33 36 41 49 58 60 67 (2008), (2012) textream 9

4 textream(http://textream.yahoo.co.jp/) A.1 textream 2015 7 textream textream twitter ( ) ( 6758) ( ) ( ) 1 1 5 ( ) 319 320 1 (2008), (2012) Antweiler and Frank(2004), Leung and Ton(2015) ( A.1 320 ) Python textream Web HTML Python Web HTML MySQL MySQL MySQL Python Mecab 3 Mecab Mecab 2 -ifinance(http://www.ifinance.ne.jp/glossary/) (http://investment-word.com/) Python MySQL ( ) 4.1 Yahoo! (http://finance.yahoo.co.jp/) NEEDS FinancialQUEST 10

1 4.2 (http://www.jpx.co.jp/) ( ) (http://kabutan.jp/) MySQL 2013 1 2015 1 0 ( 1 ) 1 2217 2 A.2 6173883 1 2013 5 23 1 5942 1 4483 1143 A.3 3 847788( ) 1102305( ) 1138405( ) 886717( ) 788597( ) 811098( ) 598973( ) 1 2 5.2, 5.3 2217 5.3 3 15:00-15:00 1 15:00-15:00 11

5 5.1 4 3 3 3000 1 3 K- (K-fold cross-validation) K- K 1 K-1 ( ) K K K A.1 3000 3000 (in sample accuracy) (0- ) Buy Hold Sell 948 909 (95.9%) 23 (2.4%) 16 (1.7%) 1428 160 (11.2%) 1186 (83.1%) 82 (5.7%) 624 23 (3.7%) 16 (2.6%) 585 (93.7%) A.2 3 (out of sample accuracy) 948 623 (65.7%) 231 (24.4%) 94 (9.9%) 1428 437 (30.6%) 796 (55.7%) 195 (13.7%) 624 174 (27.9%) 212 (34.0%) 238 (38.1%) A.3 4 3 K 2 A.4 2 3000 3000 (in sample accuracy) 12

1802 1728 (95.9%) 74 (4.1%) 1198 140 (11.7%) 1058 (88.3%) A.5 2 3 (out of sample accuracy) 1802 1443 (80.1%) 359 (14.9%) 1198 572 (47.7%) 626 (52.3%) A.6 4 3 5.2 Comtemporary regression 2 1 2 R i,t = α + β 1 Message i,t + β 2 Bullishness i,t + β 3 MarketRet i,t + β 4 R i,t 1 + ε i,t (5.1) V olume i,t = α + β 1 Message i,t + β 2 Bullishness i,t + β 3 Market i,t + β 4 V olume i,t 1 + ε i,t (5.2) R i,t i t V olume i,t 1 Message i,t i t ( (15:00) 15:00 ) Bullishness i,t i t MarketRet t t ( ) Market t t ( ) Market t A.2 2013 5 23 Antweiler and Frank(2004) i t C {,, } Mi,t C (Bullishness index) Bullishness i,t = M i,t M i,t + M i,t + M i,t (5.3) Antweiler and Frank(2004), Sabherwal et al.(2011), Leung and Ton(2015) Bullishness i,t = M i,t M i,t M i,t + M i,t ln (1 + M i,t + M i,t + M i,t ) (5.4) 5.1 out of sample 1/3 (5.4) 1 Message i,t (5.3) 5.1 2 Bullishness Measurement Error 2 Measurement Error 13

( : 3386) ( : 4661) ips 1 2015 1 86.9 5705 1 1 2015 1 2 5924 6896 Measurement Error 1 (5.3) A.7 Bullishness t 0.0185, 2.331 0.0137, 1.666 0.026 0.021 Bullishness t 0.0107, 3.410 0.0081, 2.715 0.019 0.011 0.476 0.633 5.1 5.2 1000 4 2217 (Large) 100 (Mid) 200 (Small) 700 Leung and Ton(2015) A.8 A.9 A.10 (Large) (Mid) (Small) Bullishness Median 25%quantile 0 0 A.11 A.12 A.13 (Large) (Mid) (Small) Return 1 1 A.11, 12 1 4 14

A.14 (Large) (Mid) (Small) (5.1) (t =-2.95) (t =16.98) (Large: t =11.23, Medium: t =12.71, Small: t =11.91) A.15 (Large) (Mid) (Small) (5.2) 2 (Large: t =18.74, Medium: t =39.98, Small: t =52.70) (Large: t =5.04, Medium: t =4.30, Small: t =8.29) t Large: -1.74, Medium: t =-7.04, Small: t =-0.10 2013 10,605 2015 1 30 17,674 5.3 Machinlay(1997) 2 3 6 (event window) 5 ( ) 5 11 15:00 24:00 (estimation window) 2 (5.5) R i = X i θ i + ε i (5.5) R iτ i, τ ι 1 120 1 R m,τ τ α i, β i, σε 2 i R i = [R it 125,..., R it 6 ] (5.6) X i = [ι, R m ] R m = [R mt 125,..., R mt 6 ] (5.7) 2 120 15

θ i = [α i, β i ] (5.8) ε i = [ε it 125,..., ε it 6 ] (5.9) E(ε iτ ) = 0 V ar(ε iτ ) = σε 2 i (5.10) 120 OLS ˆθ i = (X ix i ) 1 X ir i (5.11) ˆσ 2 ε i = 1 120 2 ˆε iˆε i (5.12) ˆε i = R i ˆα i ι ˆβ i R m = R i X i ˆθ i (5.13) R i = [R it 5,..., R it+5 ] (5.14) X i = [ι, R m] R m = [R mt 5,..., R mt+5 ] (5.15) ˆθ i = [ˆα i, ˆβ i ] (5.16) (Cumulative Abnormal Return) E[ˆε i X i ] = E[R i X ˆθ i i X i ] = E[(R i X i θ i ) X i (ˆθ i θ i ) X i ] = 0 (5.17) V i = E[ˆε i ˆε i X i ] = E[ε i ε i ε i (ˆθ i θ i ) X i X i (ˆθ i θ i )ε i X i (ˆθ i θ i )(ˆθ i θ i ) X i X i ] (5.18) = Iσ 2 ε i + X i (X ix i ) 1 X i σ 2 ε i ˆε i N (0, V i ) (5.19) 16

γ τ 1 τ 2 1 0 (11 1) τ 1 τ 2 3 ĈAR i (τ 1, τ 2 ) γ ˆε i (5.20) V ar[ĉar i (τ 1, τ 2 )] = σi 2 (τ 1, τ 2 ) = γ V i γ (5.21) ĈAR i (τ 1, τ 2 ) N (0, σi 2 (τ 1, τ 2 )) (5.22) 1 4 (5.13) ˆε i N N ε = 1 N N i=1 ˆε i V ar[ ε ] = V = 1 N 2 N V i (5.23) i=1 CAR(τ 1, τ 2 ) γ ε (5.24) V ar[car(τ 1, τ 2 )] = σ 2 (τ 1, τ 2 ) = γ V γ (5.25) N (5.20) (5.21) (5.26) (5.27) CAR(τ 1, τ 2 ) = 1 N N ĈAR i (τ 1, τ 2 ) (5.26) i=1 V ar[car(τ 1, τ 2 )] = σ 2 (τ 1, τ 2 ) = 1 N 2 N σi 2 (τ 1, τ 2 ) (5.27) 0 σ 2 (τ 1, τ 2 ) i=1 CAR(τ 1, τ 2 ) N (0, σ 2 (τ 1, τ 2 )) (5.28) ˆ σ 2 (τ 1, τ 2 ) = 1 N 2 N ˆσ i 2 (τ 1, τ 2 ) (5.29) 3 τ 1 t 5 τ 2 t 5 t + 5 4 11 i=1 17

J 1 = CAR(τ 1, τ 2 ) [ˆ σ 2 (τ 1, τ 2 )] 1 2 a N (0, 1) (5.30) γ 1 1 3 30 3 1099 8628 5 (Large) 100 (Mid) 200 (Small) 799 3 5.2 i t C {,, } M C i,t Bullishness i,t = M i,t M i,t + M i,t (5.3) 1 ln (1 + M + M i,t + M i,t + M i,t ) (5.31) i,t A.16 Bull, Mid, Bear L, M, S Large, Mid, Small All L,M,S Bull, Mid, Bear *, **, *** 5% 1% 0.1% t-1 0.1% t t+1 0.1% t t+5 0.1% All L, M, S t Large 1% t Mid 0.1% t t+1 Small 0.1% t-1 Small 0.1% Small t t+5 0.1% Small 6 Bull, Mid, Bear t t+1 Bull 0.1% t Mid 0.1% t Bear 5 2013 2013 1 ( ) 2013 1 2 30 6 2013 1 87.32 2015 1 30 1 117.44 2013 5 23 2013 5 15 18

Bull t t+5 0.1% Bull All Small Mid Bull L, M, S t Large Mid t t+1 Small 0.1% t+2 Small 1% Small t t+5 0.1% Bull Small A.17 t (Post-Earnings-Announcement Drift) Ball and Brown 1968) Bull Mid L, M, S t Large 5% Mid 1% t Small 0.1% Small t t+3 5% Bear L, M, S t Large 0.1% Mid 0.1% t Small 0.1% t-1 Small 0.1% Bear Small t t Small t Large, Mid( ) A.17 A.16 Bull A.16 A.17 A.16 19

6 6.1 textream 5.2 1( ) 2( ) 3 5.3 3( ) Mackinlay(1997) Antweiler and Frank(2004) Sabherwal et al.(2011) 6.2 Support Vector Machine 20

[1] Antweiler, W., and Frank, M. Z., (2004). Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards. Journal of Finance 59 (3), 1259-1294. [2] Ball, R., and P. Brown, (1968). An Empirical Evaluation of Accounting Numbers. Journal of Accounting Research 6 (2), 159-178. [3] Das, S. R., Chen, M. Y., (2007). Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web. Management Science 53 (9), 1375-1388. [4] Fama, E. and French, K.R. (1992). The cross-section of expected stock returns. Journal of Finance 47, 427-465. [5] Leung, H., and Ton T., (2015). The impact of internet stock message boards on cross-sectional returns of small-capitalization stocks. Journal of Banking and Finance 55, 37-55. [6] MacKinlay, A.C., (1997). Event Studies in Economics and Finance. Journal of Economic Literature 35 (1), 13-39. [7] Sabherwal, S., Sarkar, S.K., and Zhang. Y., (2011). Do Internet Stock Message Boards Influence Trading? Evidence from Heavily Discussed Stocks with No Fundamental News. Journal of Business Finance & Accounting 38 (9-10), 1209-1237. [8] Tetlock, P. C., (2007). Giving content to investor sentiment: The role of media in the stock market Journal of Finance 62 (3), 1139-1168. [9] Tetlock, P. C., Saar-Tsechansky, M., and Macskassy, S., (2008). More Than Words: Quantifying Language to Measure Firms Fundamentals. Journal of Finance 63 (3), 1437-1467. [10] Tirunillai, S., and Tellis, G. J., (2012). Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance, Marketing Science 31 (2), 198-215. [11] Tumarkin, R. and Whitelaw, R.F., (2001). News or Noise? Internet Postings and Stock Prices. Financial Analysts Journal 57, 41-51. [12] Wysocki, P., (1999). Cheap Talk on the Web: The Determinants of Postings on Stock Message Boards, Working paper, University of Michigan. [13] Yu, Y., Duan. W., and Can, Q., (2013). The impact of social and conventional media on firm equity value: A sentiment analysis approach, Decision Support Systems 55 (4), 919-926. [14],,, (2013). - -,, 51 (12), 96-105. [15],, (2012).,, 53 (1), 117-125. 21

[16],,, (2008).,, 46 (11-12), 110-127. [17],, (2005)., 20, 237-240. 22

A A.1: textream ( : ) 23

A.2: textream ( ) A.3: textream ( ) 24

A.1: insample accuracy(c=buy, Hold or Sell) % Buy Hold Sell Buy 948 909 23 16 Hold 1428 160 1186 82 Sell 624 23 16 585 3000 3000 1092 1225 683 A.2: out of sample accuracy(3-fold cross validation, C=Buy, Hold or Sell) % Buy Hold Sell Buy 948 628 233 87 Hold 1428 445 779 204 Sell 624 181 199 244 3000 3000 1254 1211 535 A.3: out of sample accuracy(4-fold cross validation, C=Buy, Hold or Sell) % Buy Hold Sell Buy 948 623 231 94 Hold 1428 437 796 195 Sell 624 174 212 238 3000 3000 1234 1239 527 A.4: insample accuracy(c=buy or Sell) % Buy Sell Buy 1802 1728 74 Sell 1198 140 1058 3000 3000 1868 1132 25

A.5: out of sample accuracy(3-fold cross validation, C=Buy or Sell) % Buy Sell Buy 1802 1427 375 Sell 1198 574 624 3000 3000 1254 1211 A.6: out of sample accuracy(4-fold cross validation, C=Buy or Sell) % Buy Sell Buy 1802 1443 359 Sell 1198 572 626 3000 3000 1254 1211 A.7: ( ): Return t : 3386 Return t : 4661 t t t t 0.0118 2.612 0.0103 2.302 0.0005 0.309 0.0007 0.394 Message t 0.0051 2.328 0.0050 2.267 0.0005 0.765 0.0005 0.734 Bullishness t 0.0185 2.331 0.0137 1.666 0.0107 3.410 0.0081 2.715 MarketRet t 0.2588 1.516 0.2390 1.396 0.0348 0.766 0.0380 0.831 Return t 1 0.0475 1.055 0.0498 1.104 0.0421 0.882 0.0542 1.136 AdjustedR 2 0.026 0.021 0.019 0.011 26

A.8: ( : Large) Return M essage Bullishness M Return M arket V olume Mean 0.0013 1.1033 0.2103 0.0012 9.5831 15.002 SD 0.0211 1.2542 0.3090 0.0149 0.1147 1.440 Skewness 0.6031 1.4367 1.4178 0.3789 0.7700 0.220 Kurtosis 6.7963 2.2169 0.9239 1.9913 0.6682 1.233 Max 0.2421 7.6123 1.0000 0.0553 9.7945 20.780 75th 0.0118 1.7918 0.3333 0.0094 9.6459 17.558 Median 0.0006 0.6931 0.0000 0.0011 9.5959 15.546 25th 0.0099 0.0000 0.0000 0.0067 9.5412 14.372 Min 0.2149 0.0000 0.0000 0.0732 9.2579 8.007 A.9: ( : Mid) Return M essage Bullishness M Return M arket V olume Mean 0.0015 0.9654 0.2063 0.0012 9.5831 14.092 SD 0.0278 1.2932 0.3191 0.0149 0.1147 1.652 Skewness 1.1833 1.8783 1.4123 0.3789 0.7700 0.045 Kurtosis 12.8138 3.8803 0.7803 1.9913 0.6682 0.008 Max 0.3718 8.5977 1.0000 0.0553 9.7945 19.714 75th 0.0131 1.3863 0.3750 0.0094 9.6459 17.092 Median 0.0000 0.6931 0.0000 0.0011 9.5959 14.703 25th 0.0118 0.0000 0.0000 0.0067 9.5412 13.314 Min 0.2879 0.0000 0.0000 0.0732 9.2579 6.399 A.10: ( : Small) Return M essage Bullishness M Return M arket V olume Mean 0.0021 0.8782 0.2130 0.0012 9.5831 11.716 SD 0.0424 1.19279 0.3259 0.0149 0.1147 1.897 Skewness 2.2149 1.6670 1.3232 0.3789 0.7700 0.218 Kurtosis 21.6829 2.8811 0.4546 1.9913 0.6682 0.026 Max 1.0468 8.3260 1.0000 0.0553 9.7945 20.333 75th 0.0144 1.3863 0.4160 0.0094 9.6459 15.295 Median 0.0000 0.6931 0.0000 0.0011 9.5959 12.366 25th 0.0153 0.0000 0.0000 0.0067 9.5412 10.773 Min 0.3396 0.0000 0.0000 0.0732 9.2579 4.615 27

A.11: (Large) Return Message Bullishness MReturn Return 1 Return 1.000 0.008 0.055 0.126-0.003 Message 1.000 0.356 0.003-0.010 Bullishness 1.000 0.019 0.052 MReturn 1.000 0.138 Return 1 1.000 A.12: (Mid) Return Message Bullishness MReturn Return 1 Return 1.000 0.023 0.066 0.097-0.004 Message 1.000 0.410 0.012 0.025 Bullishness 1.000 0.009 0.059 MReturn 1.000 0.107 Return 1 1.000 A.13: (Small) Return Message Bullishness MReturn Return 1 Return 1.000 0.096 0.086 0.082 0.038 Message 1.000 0.479 0.007 0.122 Bullishness 1.000 0.012 0.052 MReturn 1.000 0.087 Return 1 1.000 28

A.14: ( ): Return t Small Medium Large t t t 0.0027 1.04 0.0000 0.00 0.0002 0.26 Message t 0.0038 16.98 0.0002 1.07 0.0002 2.95 Bullishness t 0.0082 11.91 0.0046 12.71 0.0039 11.23 MarketRet t 0.3775 25.14 0.2439 32.72 0.1765 27.64 Return t 1 0.0219 4.88 0.0156 3.78 0.0087 4.72 AdjustedR 2 0.0274 0.0218 0.0173 A.15: ( ): V olume t Small Medium Large t t t 3.5832 15.36 5.4441 32.61 4.7300 26.54 Message t 0.2255 52.70 0.1463 39.98 0.0517 18.74 Bullishness t 0.0910 8.29 0.0315 4.30 0.0388 5.04 Market t 0.0024 0.10 0.1139 7.04 0.0295 1.74 V olume t 1 0.6694 223.41 0.6961 228.02 0.7088 188.68 AdjustedR 2 0.8556 0.9232 0.9267 29

A.16: ( ) Day t t-5 t-4 t-3 t-2 t-1 t t+1 t+2 t+3 t+4 t+5 Abnormal All -0.055-0.001-0.001-0.045 0.225-0.704-0.302-0.104-0.109 0.008-0.004 Average Returns *** *** *** * * L 0.297 0.091 0.131 0.073 0.125 0.390-0.146 0.298-0.139-0.126-0.024 * ** * M -0.084 0.022 0.021 0.161 0.052 0.354-0.154-0.004 0.011 0.010-0.025 *** S -0.020 0.015-0.021-0.013 0.279-1.086-0.356-0.173-0.135 0.023 0.003 *** *** *** ** * Bull -0.101 0.018 0.063-0.014 0.207-1.627-0.623-0.263-0.141-0.126-0.100 *** *** * L -0.650 0.027 0.363 0.095 0.116 0.200-0.525 0.261-0.263 0.090-0.118 * * M -0.286 0.236 0.090 0.182 0.018 0.112-0.404-0.141 0.045-0.070-0.093 * S -0.022 0.009-0.000-0.000 0.231-2.161-0.691-0.369-0.146-0.122-0.140 *** *** ** Mid -0.090 0.028-0.067-0.044 0.245-0.312-0.139 0.061-0.080 0.054 0.080 *** L -0.236 0.022 0.100 0.270 0.377 0.511-0.164 0.463-0.160-0.401 0.009 * * M -0.016 0.099 0.093 0.205 0.117 0.398-0.027 0.038 0.103 0.069-0.092 ** S -0.070 0.030-0.049 0.009 0.311-0.610-0.200 0.018-0.144 0.046 0.161 *** *** * Bear 0.038-0.055 0.006-0.080 0.222-0.151-0.141-0.124-0.109 0.102 0.001 * L 0.005 0.228 0.077 0.046 0.121 0.875 0.264 0.167 0.009-0.069 0.039 *** M 0.059 0.210 0.074 0.091 0.057 0.806-0.028 0.096-0.127 0.031 0.123 *** S 0.040 0.001-0.010-0.053 0.293-0.478-0.175-0.188-0.114 0.153-0.029 *** *** * * Cumulative All -0.055-0.055-0.056-0.101 0.124-0.580-0.882-0.986-1.095-1.087-1.091 Abnormal Returns *** *** *** *** *** *** L -0.297-0.388-0.258-0.331-0.206 0.184 0.039 0.336 0.197 0.071 0.047 * * M -0.084-0.105-0.084-0.246-0.193 0.161 0.007 0.003 0.014 0.024-0.000 S -0.020-0.006-0.027-0.040 0.239-0.847-1.203-1.376-1.511-1.489-1.486 *** *** *** *** *** *** Bull -0.101-0.083-0.020-0.034 0.173-1.454-2.076-2.339-2.481-2.607-2.707 *** *** *** *** *** *** L -0.650-0.677-0.315-0.219-0.104-0.304-0.829-0.568-0.831-0.741-0.859 * M -0.286-0.051 0.039-0.142-0.161-0.273-0.677-0.818-0.773-0.843-0.936 S -0.022-0.012-0.012-0.012 0.219-1.942-2.633-3.002-3.147-3.269-3.409 *** *** *** *** *** *** Mid -0.090-0.062-0.129-0.172 0.073-0.239-0.379-0.318-0.397-0.343-0.263 L -0.236-0.257-0.158-0.427-0.051 0.460 0.296 0.759 0.599 0.198 0.207 *** M -0.016-0.116-0.209-0.414-0.297 0.100 0.073 0.111 0.214 0.283 0.191 *** S -0.070-0.039-0.089-0.079 0.232-0.378-0.578-0.561-0.705-0.659-0.498 * * * * Bear 0.038-0.017-0.010-0.090 0.132-0.019-0.159-0.284-0.392-0.290-0.289 L 0.005 0.224 0.301 0.347 0.468 0.407 0.671 0.837 0.847 0.779 0.818 *** M 0.059 0.151-0.078-0.169-0.112 0.693 0.665 0.761 0.634 0.665 0.787 * S 0.040 0.041 0.031-0.023 0.271-0.208-0.382-0.570-0.684-0.531-0.561 * ** 30

A.17: ( ) Day t t-5 t-4 t-3 t-2 t-1 t t+1 t+2 t+3 t+4 t+5 Abnormal All -0.055-0.001-0.001-0.045 0.225-0.704-0.302-0.104-0.109 0.008-0.004 Average Returns *** *** *** * * L 0.297 0.091 0.131 0.073 0.125 0.390-0.146 0.298-0.139-0.126-0.024 * ** * M -0.084 0.022 0.021 0.161 0.052 0.354-0.154-0.004 0.011 0.010-0.025 *** S -0.020 0.015-0.021-0.013 0.279-1.086-0.356-0.173-0.135 0.023 0.003 *** *** *** ** * -0.086 0.015 0.017-0.012 0.276-1.530-0.569-0.211-0.145-0.080-0.067 ** *** *** * L -0.256-0.100 0.227 0.027-0.076-0.111-0.475 0.334-0.221-0.055-0.200 * M -0.218 0.200-0.012-0.195 0.039 0.031-0.434-0.057 0.019-0.138 0.030 * S 0.028-0.010-0.044 0.026 0.340-2.105-0.659-0.329-0.157-0.074-0.057 ** *** *** * -0.108-0.010-0.032-0.006 0.116-0.460-0.199-0.035-0.084 0.049 0.011 *** ** L -0.501 0.058 0.207 0.064 0.454 0.534 0.087 0.391-0.159-0.151 0.141 * * M -0.157-0.199-0.046-0.063 0.078-0.002-0.033 0.063 0.090 0.146-0.143 S -0.115 0.035-0.017 0.011 0.122-0.703-0.216-0.098-0.145 0.079 0.005 *** * 0.025-0.007 0.010-0.113 0.278-0.127-0.137-0.064-0.098 0.057 0.043 *** * L -0.136-0.231-0.042-0.310 0.001 0.750-0.046 0.168-0.037-0.172-0.011 ** M 0.089-0.091 0.098-0.202 0.046 0.896 0.008-0.005-0.052 0.044 0.011 *** S 0.017 0.020-0.002-0.071 0.359-0.438-0.186-0.090-0.106 0.067 0.058 *** *** * Cumulative All -0.055-0.055-0.056-0.101 0.124-0.580-0.882-0.986-1.095-1.087-1.091 Abnormal Returns *** *** *** *** *** *** L -0.297-0.388-0.258-0.331-0.206 0.184 0.039 0.336 0.197 0.071 0.047 * * M -0.084-0.105-0.084-0.246-0.193 0.161 0.007 0.003 0.014 0.024-0.000 S -0.020-0.006-0.027-0.040 0.239-0.847-1.203-1.376-1.511-1.489-1.486 *** *** *** *** *** *** -0.086-0.071-0.054-0.066 0.210-1.320-1.889-2.100-2.245-2.325-2.393 *** *** *** *** *** *** L -0.256-0.357-0.129-0.102-0.179-0.289-0.764-0.431-0.651-0.706-0.906 M -0.218-0.018-0.030-0.226-0.186-0.155-0.589-0.646-0.627-0.765-0.734 *** S 0.028 0.018-0.026-0.001 0.340-1.765-2.424-2.753-2.911-2.984-3.042 *** *** *** *** *** *** -0.108-0.118-0.150-0.156-0.040-0.500-0.699-0.734-0.818-0.770-0.759 * ** ** *** ** ** L -0.501-0.443-0.235-0.171 0.283 0.818 0.905 1.296 1.137 0.985 1.127 * *** M -0.157-0.357-0.403-0.466-0.387-0.390-0.423-0.360-0.270-0.123-0.267 *** S -0.115-0.080-0.098-0.087 0.035-0.668-0.884-0.982-1.127-1.048-1.043 ** ** *** *** ** ** 0.025 0.018 0.029-0.084 0.194 0.068-0.069-0.133-0.231-0.174-0.131 L -0.136-0.366-0.409-0.719-0.718 0.032-0.013 0.155 0.117-0.055-0.065 M 0.089-0.002 0.096-0.106-0.060 0.836 0.844 0.838 0.786 0.830 0.841 ** * * * * S 0.017 0.038 0.035-0.036 0.323-0.116-0.301-0.391-0.497-0.430-0.372 31

B : 69 0,, 1 ( ), 2, 3,, 4,, 5,, 6,, 7,, 8,, 9,, 10,, 11,, 12,, 13,,, 14,,, 15,,, 16,, 17,, 18,, 19,, 20,, 21,, 22,, 23,, 24,, 25, 26, 27,, 28,, 29,, 30,, 31,, 32,, 33,, 34,, 35,, 36,, 37,, 38,, 39,, 40,, 41,,, 42,,,, 43,,,, 44,,,, 45,, ( ), 46,,,, 47,,,, 48,, 49,, 50,,, 51,,, 52,,, 53,,, 54,,, 55,,, 56,,,, 57,,, 58,,, 59,,, 60,,, 61,, 62,,, 63,,, 64,,, 65,,, 66,,, 67,, 68 32