Table 6

Investor trading behavior and ST

ST quintile
12345DiffFF3FF4
Panel A. Individual investors
Low0.380.380.390.430.22−0.16−0.07−0.20
(0.88)(1.07)(0.92)(0.95)(0.44)(−0.55)(−0.23)(−0.70)
High0.881.131.251.12−0.14−1.03−1.22−1.35
(2.36)(2.91)(2.62)(2.64)(−0.25)(−3.22)(−3.89)(−4.71)
Panel B. Institutional investors
Low0.740.980.970.960.36−0.37−0.43−0.57
(1.85)(2.47)(2.42)(2.15)(0.70)(−1.26)(−1.36)(−1.94)
High0.260.230.500.480.340.080.120.01
(0.63)(0.61)(1.29)(1.17)(0.72)(0.27)(0.41)(0.04)
Panel C. Foreign investors
Low0.821.011.000.89−0.24−1.07−1.26−1.37
(2.08)(2.58)(2.29)(2.06)(−0.47)(−3.89)(−4.71)(−5.20)
High0.350.550.510.47−0.18−0.53−0.49−0.66
(0.90)(1.43)(1.20)(1.04)(−0.38)(−1.92)(−1.58)(−2.29)

Note(s): This table examines how the return predictability of the salience measure (ST) varies with investor-type net buying (Netbuy). Netbuy is defined as (buy volume − sell volume) divided by shares outstanding and is expressed as a percentage. Each month, stocks are independently double-sorted into quintiles based on Netbuy and ST. We focus on stocks in the lowest and highest Netbuy quintiles and report the average next-month returns of the ST quintile portfolios (columns 1 to 5). Panels A, B, and C present results separately for individual, institutional, and foreign investors, respectively. The column “Diff” reports the return spread between the highest and lowest ST quintiles (Q5 − Q1) within the bottom and top Netbuy quintiles, capturing the strength of ST-based return predictability conditional on investor trading intensity. Columns “FF3” and “FF4” report the corresponding alphas from the Fama–French three-factor and four-factor models. Newey and West (1987) t-statistics with 12 lags are reported in parentheses. The sample includes all common stocks listed on KOSPI and KOSDAQ from March 2005 to December 2024

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