Table 2 The IE prediction regressions...

Table 2

The IE prediction regressions

Model	$β_{0, t}$	${I E}_{i, t - T}$	${I S}_{i, t - T}$	${I V}_{i, t - T}$	${I K}_{i, t - T}$	${M K T}_{i, t - T}$	${S M B}_{i, t - T}$	${H M L}_{i, t - T}$	${M O M}_{i, t - T}$	${C o s k e w}_{i, t - T}$	${L I Q}_{i, t - T}$	${MAX}_{i, t - T}$	${MIN}_{i, t - T}$	Adj.R²
Panel A: descriptive statistics
1	0.039 (0.95)	0.62 (1.00)												7.01%
2	0.062 (0.79)		0.17 (0.79)											1.55%
3	0.035 (0.90)			6.88 (0.942)										38.15%
4	0.10 (0.93)				−0.038 (0.792)									3.99%
5	0.030 (0.89)	0.31 (0.891)	0.14 (0.696)	3.89 (0.865)	−0.007 (0.244)									44.29%
6	0.025 (0.71)	0.21 (0.712)	0.20 (0.511)	3.88 (0.782)	0.0011 (0.397)	−0.072 (0.622)	−0.016 (0.555)	0.012 (0.788)	−0.042 (0.572)	0.055 (0.533)	0.66 (0.733)	−0.059 (0.522)	0.012 (0.332)	50.11%
Panel B: robustness on different formation periods
7 (30 days)	0.033 (0.94)	0.39 (0.892)	0.27 (0.782)	3.52 (0.782)	−0.010 (0.314)	−0.076 (0.601)	−0.022 (0.566)	0.024 (0.829)	−0.071 (0.758)	0.034 (0.402)	0.48 (0.611)	−0.068 (0.602)	0.016 (0.398)	61.03%
8 (90 days)	0.022 (0.68)	0.13 (0.667)	0.075 (0.526)	3.90 (0.630)	−0.004 (0.200)	−0.038 (0.521)	0.0096 (0.101)	0.012 (0.388)	−0.032 (0.536)	0.055 (0.533)	0.74 (0.869)	−0.033 (0.441)	0.010 (0.301)	35.11%
9 (150 days)	0.019 (0.59)	0.025 (0.569)	0.063 (0.482)	3.11 (0.601)	−0.005 (0.211)	−0.035 (0.473)	0.027 (0.76)	0.008 (0.277)	−0.022 (0.506)	0.083 (0.791)	0.84 (0.98)	−0.021 (0.298)	0.007 (0.211)	23.26%
10 (365 days)	0.010 (0.44)	0.035 (0.501)	0.022 (0.273)	1.36 (0.324)	0.007 (0.38)	0.013 (0.282)	0.016 (0.49)	0.004 (0.112)	0.069 (0.322)	0.13 (0.977)	0.90 (1.00)	−0.015 (0.112)	0.005 (0.109)	13.29%

Model	$β_{0, t}$	${I E}_{i, t - T}$	${I S}_{i, t - T}$	${I V}_{i, t - T}$	${I K}_{i, t - T}$	${M K T}_{i, t - T}$	${S M B}_{i, t - T}$	${H M L}_{i, t - T}$	${M O M}_{i, t - T}$	${C o s k e w}_{i, t - T}$	${L I Q}_{i, t - T}$	${MAX}_{i, t - T}$	${MIN}_{i, t - T}$	Adj.R²
Panel A: descriptive statistics
1	0.039 (0.95)	0.62 (1.00)												7.01%
2	0.062 (0.79)		0.17 (0.79)											1.55%
3	0.035 (0.90)			6.88 (0.942)										38.15%
4	0.10 (0.93)				−0.038 (0.792)									3.99%
5	0.030 (0.89)	0.31 (0.891)	0.14 (0.696)	3.89 (0.865)	−0.007 (0.244)									44.29%
6	0.025 (0.71)	0.21 (0.712)	0.20 (0.511)	3.88 (0.782)	0.0011 (0.397)	−0.072 (0.622)	−0.016 (0.555)	0.012 (0.788)	−0.042 (0.572)	0.055 (0.533)	0.66 (0.733)	−0.059 (0.522)	0.012 (0.332)	50.11%
Panel B: robustness on different formation periods
7 (30 days)	0.033 (0.94)	0.39 (0.892)	0.27 (0.782)	3.52 (0.782)	−0.010 (0.314)	−0.076 (0.601)	−0.022 (0.566)	0.024 (0.829)	−0.071 (0.758)	0.034 (0.402)	0.48 (0.611)	−0.068 (0.602)	0.016 (0.398)	61.03%
8 (90 days)	0.022 (0.68)	0.13 (0.667)	0.075 (0.526)	3.90 (0.630)	−0.004 (0.200)	−0.038 (0.521)	0.0096 (0.101)	0.012 (0.388)	−0.032 (0.536)	0.055 (0.533)	0.74 (0.869)	−0.033 (0.441)	0.010 (0.301)	35.11%
9 (150 days)	0.019 (0.59)	0.025 (0.569)	0.063 (0.482)	3.11 (0.601)	−0.005 (0.211)	−0.035 (0.473)	0.027 (0.76)	0.008 (0.277)	−0.022 (0.506)	0.083 (0.791)	0.84 (0.98)	−0.021 (0.298)	0.007 (0.211)	23.26%
10 (365 days)	0.010 (0.44)	0.035 (0.501)	0.022 (0.273)	1.36 (0.324)	0.007 (0.38)	0.013 (0.282)	0.016 (0.49)	0.004 (0.112)	0.069 (0.322)	0.13 (0.977)	0.90 (1.00)	−0.015 (0.112)	0.005 (0.109)	13.29%

Note(s): This table presents the average of risk coefficients over time, derived from monthly cross-sectional regression analyses as outlined in Equation (11). Panel A details regression results for 3,100 firms listed in Datastream, with all idiosyncratic risk measures calculated based on a 60-day period from January 1988 to June 2019. Panel B provides robustness checks for Equation (11), using various formation periods of 30, 90, 150, and 365 days for the idiosyncratic risk factors. Below each coefficient estimate, the table shows the percentage of coefficients that are statistically significant at the 5% level and have the same direction as the average coefficient

Source(s): Created by the author

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