Modeling Overlapped Mutual Funds’ Portfolios: A Bipartite Network Approach
Table 1
Bipartite Network Models. This table summarizes the results of the following model: = α + β∗+ γ∗ + + . The dependent variable is and represent the variation in the topological variables of the bipartite networks. corresponds to the independent variables. corresponds to the control variables. are monthly fixed effects to control for seasonality. All models are estimated with robust standard errors.
(4)
(5)
(6)
(7)
(8)
(9)
vdegfon
vstrengthb
vdiversity
ln_mcap
0.0104
-0.000299
-0.0372
-0.0217
0.00857
-0.00878
(0.248)
(0.964)
(0.356)
(0.444)
(0.378)
(0.266)
ln_liq
-0.0127∗
-0.00336
-0.0573∗∗
-0.0559∗∗
-0.00455
0.00477
(0.072)
(0.616)
(0.033)
(0.023)
(0.561)
(0.496)
ln_book
0.0212
0.00632
-0.249∗∗
-0.144∗∗∗
0.0551∗∗
0.0134
(0.382)
(0.641)
(0.019)
(0.002)
(0.041)
(0.369)
ln_to
0.0198∗∗∗
0.00509
-0.0583
-0.0752∗∗
0.0210∗∗
0.00636
(0.003)
(0.488)
(0.144)
(0.033)
(0.012)
(0.412)
ln_as
0.0185
-0.0158
0.0159
0.0186
0.0483∗∗
0.00522
(0.327)
(0.293)
(0.813)
(0.745)
(0.015)
(0.737)
ln_stocks
0.155∗∗∗
0.101∗∗∗
0.172
0.169
0.120∗∗
0.0380
(0.000)
(0.000)
(0.320)
(0.176)
(0.021)
(0.314)
ln_funds
-0.0344
0.0102
-0.0199
-0.0289
-0.0459∗
0.000722
(0.135)
(0.333)
(0.837)
(0.583)
(0.058)
(0.958)
ln_investor
-0.0314∗∗
-0.0323∗∗∗
-0.109∗∗
-0.0457
-0.00678
-0.0153
(0.019)
(0.001)
(0.045)
(0.193)
(0.648)
(0.154)
L.performance
0.166∗∗∗
0.124∗∗∗
0.129
0.210
0.166∗∗∗
0.103∗∗∗
(0.000)
(0.000)
(0.571)
(0.370)
(0.000)
(0.006)
ipsa_ret
0.0829∗
0.0327
0.0893∗
1.075∗∗∗
1.190∗∗∗
1.200∗∗∗
0.0638
-0.0175
0.0367
(0.095)
(0.425)
(0.065)
(0.000)
(0.000)
(0.000)
(0.306)
(0.735)
(0.567)
varvix
0.0139
0.0144
0.0173
0.00385
-0.000578
0.00691
-0.00301
-0.00342
-0.00150
(0.235)
(0.164)
(0.156)
(0.908)
(0.987)
(0.841)
(0.847)
(0.811)
(0.923)
varcu
0.0132
0.00151
-0.0131
-0.0239
0.0148
-0.0426
0.0232
0.00314
0.00393
(0.544)
(0.946)
(0.623)
(0.818)
(0.895)
(0.680)
(0.438)
(0.912)
(0.893)
varclp
0.0394
0.0326
-0.0255
0.292
0.297
0.287
0.0813
0.0586
0.0291
(0.395)
(0.478)
(0.640)
(0.409)
(0.404)
(0.404)
(0.175)
(0.286)
(0.611)
varmsci
0.0155
0.0255
0.00213
0.179
0.0846
0.183
0.111∗∗
0.113∗∗
0.101∗∗
(0.690)
(0.500)
(0.962)
(0.373)
(0.687)
(0.363)
(0.021)
(0.022)
(0.043)
varpe
0.00272
0.00612
0.0195
0.0549
0.0811
0.0716
-0.0224
-0.0129
-0.0111
(0.883)
(0.719)
(0.329)
(0.549)
(0.403)
(0.439)
(0.318)
(0.531)
(0.612)
spx_ret
0.0931
0.104∗
0.0917
0.0661
0.200
0.0194
-0.0317
-0.0124
-0.0254
(0.134)
(0.096)
(0.249)
(0.841)
(0.539)
(0.952)
(0.708)
(0.886)
(0.781)
L.vdegfon
-0.133∗
-0.120
0.0435
(0.071)
(0.133)
(0.609)
L.vstrengthb
0.0447
0.0524
0.105
(0.742)
(0.712)
(0.313)
L.vherfindahl
L.ventropy
-0.0483
-0.0207
0.0411
(0.556)
(0.800)
(0.627)
_cons
-0.293
-0.141∗∗
-0.00470
0.159
-0.179
-0.286
-0.212
-0.0221
0.160
(0.139)
(0.049)
(0.957)
(0.837)
(0.622)
(0.443)
(0.378)
(0.814)
(0.156)
N
158
158
158
158
158
158
158
158
158
R2
0.364
0.289
0.142
0.521
0.466
0.504
0.254
0.160
0.122
adj. R2
0.226
0.167
-0.013
0.417
0.374
0.415
0.092
0.016
-0.037
P-value
0.00
0.00
0.58
0.00
0.00
0.00
0.05
0.34
0.77
F
3.522
3.172
1.394
9.500
6.630
9.581
1.935
1.813
1.099
LR-Chi2
17.77
47.38
17.13
5.45
18.73
25.73
Prob>Chi2
0.00
0.00
0.00
0.24
0.00
0.00
Nonstandardized coefficients. p-values in parentheses. ∗p < 0.1, ∗∗p < 0.05, and ∗∗∗p < 0.01.
