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Table 7 Lag selection procedure

From: Does communication increase investors’ trading frequency? Evidence from a Chinese social trading platform

 

\(Trades_{i,t}\)

\(Turnover_{i,t}\)

 

(1)

(2)

(3)

(4)

\(Y_{i,t-1}\)

0.4220\(^{***}\)

 

0.4688\(^{***}\)

 

(49.86)

 

(38.29)

 

\(Y_{i,t-2}\)

0.1360\(^{***}\)

 

0.1141\(^{***}\)

 

(25.13)

 

(12.63)

 

\(Y_{i,t-3}\)

0.0571\(^{***}\)

 

0.0532\(^{***}\)

 

(12.16)

 

(6.36)

 

\(Y_{i,t-4}\)

0.0336\(^{***}\)

 

0.0356\(^{***}\)

 

(7.60)

 

(4.39)

 

\(Y_{i,t-5}\)

0.0078\(^{*}\)

 

0.0133\(^{*}\)

 

(1.94)

 

(1.87)

 

\(Y_{i,t-6}\)

0.0047

0.1298\(^{***}\)

− 0.0025

0.1407\(^{***}\)

(1.12)

(19.99)

(− 0.38)

(13.16)

\(Y_{i,t-7}\)

0.0023

0.0501\(^{***}\)

0.0055

0.0534\(^{***}\)

(0.66)

(9.96)

(0.72)

(6.45)

\(Y_{i,t-8}\)

0.0031

0.0286\(^{***}\)

− 0.0010

0.0274\(^{***}\)

(0.84)

(5.12)

(− 0.16)

(3.11)

\(Return_{i,t-1}\)

0.9580\(^{***}\)

0.6778\(^{***}\)

0.9424\(^{***}\)

0.1983

(13.92)

(7.15)

(8.67)

(1.33)

\(Return\ SD_{i,t-1}\)

0.0490

0.3879\(^{***}\)

0.1182

0.8011\(^{***}\)

(0.79)

(2.74)

(1.29)

(3.11)

\(No.securities_{i,t-1}\)

0.1315\(^{***}\)

0.3720\(^{***}\)

0.0547\(^{***}\)

0.2353\(^{***}\)

(21.58)

(23.62)

(8.75)

(13.45)

\(No.followers_{i,t-1}\)

0.0091

0.0460\(^{*}\)

0.0085

0.0493\(^{**}\)

(0.85)

(1.95)

(0.90)

(2.27)

\(Portfolio\ age_{i,t-1}\)

− 0.0245\(^{***}\)

− 0.0542\(^{***}\)

− 0.0148

− 0.0239

(− 2.77)

(− 2.89)

(− 1.35)

(− 0.93)

\(No.leaders_{i,t-1}\)

0.0062

0.0417\(^{***}\)

0.0095

0.0388\(^{**}\)

(0.88)

(2.69)

(1.35)

(2.38)

\(Leader\ return_{i,t-1}\)

0.0758

0.1214\(^{*}\)

0.0422

0.2205\(^{**}\)

(1.47)

(1.68)

(0.52)

(2.11)

\(Leader\ SD_{i,t-1}\)

0.0079

0.2596

− 0.1726

0.0997

(0.06)

(1.49)

(− 1.20)

(0.40)

\(Leader\ trades_{i,t-1}\)

0.0089\(^{*}\)

0.0459\(^{***}\)

0.0030

0.0395\(^{***}\)

(1.81)

(5.12)

(0.44)

(2.87)

\(Leader\ Followers_{i,t-1}\)

0.0055\(^{*}\)

0.0120\(^{*}\)

0.0054

0.0076

(1.95)

(1.89)

(1.57)

(0.92)

\(Leader\ securities_{i,t-1}\)

0.0057

0.0110

0.0071

0.0145

(1.18)

(1.05)

(0.99)

(0.91)

\(Leader\ age_{i,t-1}\)

− 0.0073\(^{***}\)

− 0.0206\(^{***}\)

− 0.0070\(^{**}\)

− 0.0184\(^{**}\)

(−2.96)

(−3.65)

(−2.21)

(−2.42)

Time fixed effects

Yes

Yes

Yes

Yes

Observations

252,586

252,586

252,586

252,586

Adjusted R\(^{2}\)

0.5445

0.3596

0.5715

0.3646

  1. This table presents the estimation results of the lag selection procedure specified in Eq. 4.
  2. The dependent variable is either the (log) number of trades of portfolios (Columns 1 and 2) or the turnover ratio of portfolios (Columns 3 and 4). Only real-account portfolios of treated portfolios are included in the regressions. All explanatory variables are lagged by one week. Standard errors are double-clustered at the portfolio level and over time. *, **, and *** denote significance at the 10%, 5%, and 1% level, respectively