Table 5

Fund network centrality and performance of hard-to-value portfolio

WOiOpOiroi
VU = Idiovol
Centrality0.864***−0.125−0.922***−0.226
(0.181)(0.232)(0.293)(0.200)
Idiovol2.567***2.318***1.838***1.922***
(0.295)(0.259)(0.180)(0.173)
Centrality*Idiovol−0.0759−0.3592.184***1.666***
(0.377)(0.575)(0.814)(0.505)
VU = Turnover_stock
Centrality0.671***−0.314−0.960***−0.0358
(0.152)(0.201)(0.233)(0.160)
Turnover_stock1.907***1.383***1.148***1.365***
(0.327)(0.271)(0.181)(0.181)
Centrality*Turnover_stock−0.2410.4902.891***1.307***
(0.440)(0.594)(0.758)(0.432)
VU = Stockage
Centrality1.614***0.879**2.553***1.026***
(0.321)(0.432)(0.591)(0.358)
Stockage−0.369−0.318−0.1880.154
(0.416)(0.308)(0.232)(0.213)
Centrality*Stockage1.863***1.482***4.090***0.929*
(0.478)(0.562)(0.844)(0.494)
No. of Obs18,47618,47618,47618,476
Control variablesyesyesyesyes
Fund FEyesyesyesyes
Time FEyesyesyesyes

Note(s): Table 5 shows the coefficients of the panel regression result of the equation below. All models include fund characteristics(⁠X⁠), value uncertainty measures (⁠VU⁠), fund(⁠αi⁠) and year-month(⁠γt⁠) fixed effect. All variables except Top30 and value uncertainty measures are lagged variables. We use the logarithm of Netasset, Familysize and Fundage variables as used in the regression model. All variables are winsorized at a 1% level for both tails to mitigate the effect of outliers. Detailed variable definitions are in Table 1. Standard errors clustered at the firm level are in parentheses. ***, ** and * denote significance at the 1, 5 and 10% level, respectively

4factoralphait=β0+β1centralityit−1+β2VUit+β3centralityit−1*VUit+Xβ+αi+γt+eit

Source(s): Authors' work

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