Macroeconomic Uncertainty and Stock Returns: Evidence from the Chinese Stock Market
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摘要: 宏观基本面冲击作为股票市场波动的重要原因被广泛认可，但从宏观经济不确定性视角探讨其对中国市场股票超额收益率影响的研究却相对缺乏。利用中国宏观经济和金融的多指标数据，构建2002—2022年中国宏观经济不确定性指数，考察其对A股超额收益率的影响。研究发现宏观经济不确定性暴露的负向溢价显著存在，即具有负的宏观经济不确定性贝塔股票的未来超额收益率更高；不过这种溢价在不同股权性质、规模和行业的股票中存在差异，并且相对于经济上行时期，经济下行时期的宏观不确定性贝塔(beta)溢价更为显著，凸显其异质性和状态依赖性。本研究对于理解宏观经济不确定性对股票市场的影响以及构建相应的资产组合来应对宏观不确定性冲击具有一定的理论意义和现实价值。Abstract: Macrofundamental shocks are widely recognized as an important source of stock market volatility. However, there is a relative lack of research exploring their impact on stock excess returns in the Chinese market from the perspective of macroeconomic uncertainty. This paper utilizes multi-indicator data on China's macroeconomics and finance to construct an index of China's macroeconomic uncertainty from 2002 to 2022. It examines the impact of the uncertainty on the excess returns of A-share stocks. The empirical results show a significant negative premium for macroeconomic uncertainty exposure, i.e., stocks with negativemacroeconomic uncertainty betas have higher future excess returns. However, this premium varies for stocks of different equity nature, size, and industry, and is more pronounced in periods of economic downturn relative to periods of economic upturn, highlighting the heterogeneity and state-dependence of the macroeconomic uncertainty premium. This research has theoretical and practical value for understanding the impact of macroeconomic uncertainty on the stock market and constructing corresponding asset portfolios to cope with macro uncertainty shocks.
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Key words:
- macroeconomic uncertainty /
- stock returns /
- uncertainty premium /
- excessive rate of return /
- portfolio
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表 1 宏观经济不确定性beta的单变量组合分析
等权组合收益情况 加权组合收益情况 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) 组别 βMU RET-RF SR α3 α5 α7 RET-RF SR α3 α5 α7 Low -0.675 1.374
(2.195)0.504 0.030
(0.228)0.079
(0.638)0.095
(0.754)1.015
(1.680)0.402 0.034
(0.217)0.041
(0.260)0.093
(0.754)2 -0.165 1.355
(2.138)0.498 -0.053
(-0.526)0.067
(0.694)0.076
(0.772)0.996
(1.635)0.396 0.001
(0.006)0.006
(0.059)0.026
(0.772)3 -0.014 1.419
(2.234)0.519 -0.054
(-0.492)0.104
(0.971)0.109
(1.034)0.954
(1.580)0.384 -0.097
(-0.686)-0.089
(-0.628)-0.003
(-1.034)4 0.141 1.342
(2.065)0.477 -0.187
(-1.652)0.009
(0.073)0.016
(0.139)0.993
(1.589)0.375 -0.138
(-1.022)-0.144
(-1.080)-0.056
(-0.139)High 0.641 1.042
(1.633)0.374 -0.432
(-3.675)-0.277
(-2.314)-0.265
(-2.190)0.727
(1.196)0.279 -0.320
(-2.294)-0.328
(-2.370)-0.204
(-2.190)High-Low -0.332
(-2.282)-0.461
(-3.282)-0.356
(-2.515)-0.360
(-2.479)-0.378
(-2.418)-0.354
(-1.654)-0.369
(-1.721)-0.297
(-1.541)注：括号内为经Newey-West调整后的t统计量，下同。 
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表 2 主要变量的描述性统计
变量 N Mean SD Min p25 Medium P75 Max R-rf 519 607 0.01 0.15 -0.89 -0.07 0.00 0.07 22.05 MU 255 0.34 0.13 0.25 0.30 0.33 0.45 0.66 βMU 404 010 -0.01 0.91 -187.10 -0.15 0.00 0.14 56.42 βMKT 404 010 96.96 58.08 -4376.70 79.59 96.79 113.96 8 993.46 SIZE 519 607 8 859.10 39 448.38 36.65 1 230.44 3 016.03 6 889.85 2 786 246.75 ILLIQ 519 607 0.37 43.48 0.00 0.02 0.04 0.11 18 181.80 SHREV 512 602 0.01 0.15 -0.89 -0.07 0.00 0.08 22.05 MOM 44 7580 0.13 0.46 -1.72 -0.17 0.06 0.36 21.88 ROE 51 5676 0.02 1.04 -186.56 0.01 0.04 0.08 2.42 PE 474 101 139.12 2 590.65 0.00 21.52 38.74 80.13 420 284.64 BM 474 563 0.66 0.27 0.00 0.48 0.68 0.85 43.59 AG 468 193 0.10 0.56 -1.00 -0.01 0.04 0.13 116.19
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表 3 宏观经济不确定性beta与股票超额收益
变量 (1) (2) (3) (4) (5) (6) (7) βMU -0.188** -0.162* -0.382** -0.180** -0.349* -0.184** -0.383** (-2.122) (-1.695) (-2.085) (-1.969) (-1.943) (-2.142) (-2.164) βMKT 0.001 0.002** 0.003* 0.002* (1.380) (1.995) (1.685) (1.656) SIZE 0.000 0.000 0.000 (0.746) (0.615) (0.799) ILLIQ 9.540*** 9.445*** 9.227*** (3.784) (3.721) (3.692) SHREV -1.705*** -1.858*** -1.727*** (-3.078) (-3.462) (-3.258) MOM 0.602** 0.599** 0.547** (2.225) (2.199) (2.034) ROE 3.725*** 3.635*** 3.723*** (3.194) (3.163) (3.196) PE -0.000 -0.000 -0.000 (-1.141) (-1.064) (-1.162) BM 1.136** 1.153*** 1.231*** (2.571) (2.724) (3.014) AG 0.677*** 0.688*** 0.644*** (3.657) (3.672) (3.625) Constant 1.328** 1.415** -0.255 1.244** -0.290 1.173* -0.038 (2.129) (2.391) (-0.410) (2.018) (-0.488) (1.896) (-0.059) 股权性质效应 不控制 不控制 不控制 控制 控制 不控制 不控制 行业效应 不控制 不控制 不控制 不控制 不控制 控制 控制 N 400 231 400 231 317 963 387 097 308 710 400 223 317 963 Adj. R2 0.003 9 0.014 7 0.084 1 0.012 3 0.089 5 0.042 8 0.115 5 注：括号内为经Newey-West调整后的t统计量；*、**、***分别代表 10%、5%、1%的显著性水平。下表同。
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表 4 宏观经济不确定性beta对股票收益影响的长时间窗口分析
变量 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) n=2 n=3 n=4 n=5 n=6 n=7 n=8 n=9 n=10 n=11 n=12 βMU -0.314** -0.271*** -0.253*** -0.252*** -0.239*** -0.213*** -0.143*** -0.090*** -0.074*** -0.034 -0.036 (-2.371) (-2.742) (-2.781) (-3.093) (-3.708) (-3.597) (-2.956) (-2.800) (-3.176) (-1.383) (-1.514) βMKT 0.002* 0.002* 0.002* 0.002* 0.002 0.002 0.001 0.001* 0.001* 0.001 0.001* (1.714) (1.731) (1.743) (1.659) (1.462) (1.379) (1.620) (1.652) (1.757) (1.628) (1.671) SIZE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 -0.000 -0.000** -0.000*** -0.000*** (0.745) (0.857) (0.835) (0.820) (0.935) (0.899) (0.551) (-0.011) (-2.182) (-2.771) (-2.836) ILLIQ 7.433*** 5.820*** 5.681*** 5.252*** 3.846** 3.382** 3.535** 3.333*** 2.121*** 2.036*** 2.234*** (3.257) (3.070) (3.019) (2.773) (2.431) (2.159) (2.141) (2.983) (2.746) (2.966) (3.234) SHREV -0.936** -0.543* -0.213 0.006 0.147 0.203 0.135 0.174 0.067 0.074 0.070 (-2.179) (-1.710) (-0.928) (0.030) (0.842) (1.305) (0.998) (1.599) (0.793) (0.974) (0.909) MOM 0.484** 0.408* 0.354* 0.283 0.134 0.004 -0.161* -0.235*** -0.216*** -0.181*** -0.186*** (2.113) (1.930) (1.797) (1.552) (0.918) (0.030) (-1.701) (-3.484) (-4.236) (-3.937) (-3.784) ROE 3.224*** 2.240*** 1.831*** 1.648*** 1.133** 1.237* 1.298* 0.972* 0.065 -0.084 -0.113 (3.480) (3.196) (2.801) (2.800) (2.216) (1.966) (1.919) (1.697) (0.135) (-0.266) (-0.381) PE -0.000 -0.000** -0.000** -0.000*** -0.000*** -0.000*** -0.000*** -0.000*** -0.000*** -0.000 -0.000 (-1.622) (-2.255) (-2.509) (-2.878) (-3.786) (-4.027) (-4.974) (-5.195) (-3.595) (-1.354) (-1.226) BM 1.054** 0.988** 0.962** 0.920** 0.895*** 0.919*** 0.931*** 0.718*** 0.286** 0.200* 0.198* (2.539) (2.541) (2.590) (2.571) (2.745) (3.007) (3.097) (3.153) (2.106) (1.735) (1.666) AG 0.610*** 0.483*** 0.440*** 0.420*** 0.261*** 0.102 -0.005 0.016 -0.055 -0.080 -0.078 (3.630) (3.598) (3.507) (3.542) (2.751) (1.203) (-0.069) (0.283) (-0.918) (-1.493) (-1.525) Constant -0.033 0.155 0.220 0.274 0.362 0.397 0.577 0.650** 1.287*** 1.385*** 1.451*** (-0.055) (0.288) (0.430) (0.561) (0.818) (0.977) (1.467) (2.152) (8.091) (12.085) (12.317) N 315 103 312 299 309 584 306 924 304 316 301 728 299 162 296 638 294 164 291 743 289 365 Adj. R2 0.085 4 0.084 4 0.084 8 0.084 3 0.086 9 0.092 5 0.091 1 0.098 4 0.104 0 0.105 7 0.106 6
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表 5 宏观经济不确定性beta对股票收益影响的截面异质性
变量 股权性质 公司规模 国有 民营 外资 其他 较小规模 较大规模 βMU -0.467** -0.338* 0.103 -1.377** -0.550*** -0.593 (-2.084) (-1.924) (0.147) (-2.171) (-2.990) (-1.403) βMKT 0.001 0.004* 0.008 0.001 0.001* 0.001 (1.548) (1.817) (1.271) (0.143) (1.661) (0.104) SIZE 0.000 0.000 0.001* 0.000 -0.002*** -0.000*** (0.656) (0.770) (1.658) (0.120) (-7.327) (-3.119) ILLIQ 10.307*** 13.304*** 16.964*** 18.553** 8.835** 20.686*** (2.773) (5.648) (2.640) (2.135) (2.322) (6.246) SHREV -2.043*** -1.303* -1.313 -4.117** -3.077*** -0.860 (-3.938) (-1.736) (-0.809) (-2.177) (-5.112) (-0.708) MOM 0.506* 0.591** 0.107 1.367 0.092 0.975** (1.705) (2.159) (0.181) (1.617) (0.314) (2.326) ROE 3.858*** 4.867*** 9.529** 18.332*** 3.204** 2.307 (3.144) (3.421) (2.334) (2.926) (2.369) (0.996) PE -0.000 -0.000 0.001 0.001 0.000 0.002 (-1.125) (-0.036) (0.608) (0.553) (0.488) (0.272) BM 0.952** 1.508*** 0.684 2.144* 1.285*** 0.793 (2.207) (3.000) (0.742) (1.806) (3.062) (1.092) AG 0.749*** 0.719*** 1.286 1.729* 0.768*** 0.634 (2.973) (2.881) (1.040) (1.689) (3.580) (1.393) Constant -0.259 -0.451 -1.677 -2.470* 3.771*** 0.654 (-0.407) (-0.678) (-1.331) (-1.869) (3.248) (0.785) N 167 186 124 553 9 749 7 222 152 844 165 119 Adj. R2 0.097 1 0.099 2 0.339 5 0.409 7 0.125 5 0.165 3
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表 6 宏观经济不确定性beta对股票收益影响的分行业情况
行业分类 Low 2 3 4 High High-Low 农、林、牧、渔业 0.416
(0.333)1.085
(0.843)0.512
(0.426)-0.078
(-0.077)1.290
(0.994)0.874
(1.169)采矿业 1.462
(1.618)0.887
(0.992)0.912
(1.078)1.016
(1.256)0.417
(0.537)-1.045
(-2.654)制造业 1.373
(2.255)1.426
(2.259)1.405
(2.214)1.409
(2.170)1.016
(1.597)-0.356
(-2.286)电力、热力、燃气及水生产和供应业 0.729
(1.130)0.546
(0.860)1.133
(1.690)0.538
(0.868)0.159
(0.268)-0.570
(-1.805)建筑业 0.986
(1.275)0.770
(0.976)0.746
(0.861)1.129
(1.395)0.397
(0.542)-0.589
(-2.005)批发和零售业 1.148
(1.792)1.235
(1.931)1.349
(2.182)1.208
(1.811)0.944
(1.492)-0.203
(-0.896)交通运输、仓储和邮政业 0.756
(1.251)0.980
(1.575)0.819
(1.224)0.805
(1.212)0.843
(1.292)0.087
(0.371)信息传播、软件和信息技术服务业 1.340
(2.141)1.240
(1.800)1.471
(2.084)1.697
(2.267)1.221
(1.726)-0.119
(-0.420)房地产业 1.418
(1.881)1.286
(1.770)1.220
(1.651)1.114
(1.579)1.024
(1.434)-0.394
(-1.913)租赁和商务服务业 1.288
(1.596)1.321
(1.639)1.233
(1.669)1.194
(1.505)0.554
(0.815)-0.734
(-1.421)科学研究和技术服务业 3.306
(3.130)0.638
(0.404)0.835
(0.630)1.097
(0.701)-0.266
(-0.208)-3.572
(-5.916)公用事业① 1.294
(1.691)0.981
(1.335)1.558
(2.115)0.736
(1.032)1.214
(1.490)-0.080
(-0.210)文化、体育和娱乐业 0.922
(1.105)0.524
(0.571)0.292
(0.321)0.915
(1.015)-0.044
(-0.045)-0.966
(1.647)综合 -0.534
(-0.256)0.251
(0.113)0.536
(0.282)-0.976
(-0.533)-1.212
(-0.654)-0.678
(-1.221)
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表 7 宏观经济不确定性beta对股票收益影响的时变性
变量 (1) (2) (3) (4) 低不确定性时期 高不确定性时期 不确定性下降时期 不确定性上升时期 βMU -0.104(-0.764) -0.620**(-2.587) -0.100(-0.410) -0.743***(-3.031) βMKT 0.005(1.643) 0.000*(1.675) 0.005*(1.657) 0.003*(1.789) SIZE -0.000(-0.542) 0.000(1.033) 0.000(0.627) 0.000(0.486) ILLIQ 13.540***(3.258) 6.102***(4.599) 10.378***(3.494) 7.569**(2.294) SHREV -1.118(-1.284) -2.209**(-2.375) -2.436**(-2.186) -0.442(-0.493) MOM 0.781*(1.956) 0.449(1.083) 0.484(0.899) 0.734*(1.751) ROE 3.307***(3.169) 4.084**(2.229) 3.780**(2.003) 3.926**(2.179) PE -0.000(-0.805) -0.000(-0.793) -0.000(-0.622) -0.000(-1.207) BM 0.682(1.096) 1.527***(2.865) 1.307*(1.741) 1.190*(1.958) AG 0.602**(2.337) 0.741***(2.746) 0.403(1.404) 0.833***(2.736) Constant -0.037(-0.040) -0.442(-0.559) -0.268(-0.282) -0.292(-0.315) N 155 843 162 120 98 466 149 560 Adj. R2 0.078 9 0.088 7 0.090 4 0.084 7
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表 8 高低不确定性时期的单变量组合分析
组别 βMU 等权组合预期收益率 加权组合预期收益率 RET-RF SR α3 α5 α6 RET-RF SR α3 α5 α6 A栏：高不确定性时期 Low -0.562 1.719
(1.795)0.594 0.197
(1.621)0.288
(1.699)0.314
(1.815)1.295
(1.369)0.480 0.522
(1.579)0.288
(1.699)0.314
(1.815)2 -0.166 1.763
(1.803)0.592 0.104
(0.622)0.275
(1.632)0.277
(1.689)1.307
(1.354)0.455 0.008
(0.050)0.275
(1.632)0.277
(1.689)3 -0.010 1.615
(1.670)0.551 0.015
(0.093)0.155
(0.971)0.166
(1.022)1.241
(1.323)0.444 -0.025
(-0.114)0.155
(0.971)0.166
(1.022)4 0.153 1.607
(1.589)0.518 -0.119
(-0.661)0.105
(0.558)0.107
(0.574)1.312
(1.324)0.435 -0.054
(-0.258)0.105
(0.558)0.107
(0.574)High 0.582 1.239
(1.255)0.408 -0.415
(-2.233)-0.266
(-1.365)-0.257
(-1.316)0.880
(0.919)0.302 -0.387
(-1.944)-0.266
(-1.365)-0.257
(-1.316)High-Low -0.480
(-2.194)-0.561
(-2.993)-0.553
(-2.780)-0.571
(-2.879)-0.414
(-1.677)-0.509
(-1.886)-0.553
(-2.780)-0.571
(-2.879)B栏：低不确定性时期 Low -0.914 0.934
(1.141)0.355 0.026
(0.113)-0.043
(-0.201)-0.031
(-0.145)0.500
(0.643)0.215 -0.031
(-0.117)-0.043
(-0.201)-0.031
(-0.145)2 -0.185 1.043
(1.260)0.410 0.002
(0.016)0.063
(0.420)0.073
(0.492)0.745
(1.014)0.349 0.133
(0.769)0.063
(0.420)0.073
(0.492)3 -0.024 0.958
(1.186)0.386 -0.116
(-1.183)-0.052
(-0.402)-0.045
(-0.354)0.451
(0.619)0.230 -0.006
(-0.042)-0.052
(-0.402)-0.045
(-0.354)4 0.133 0.919
(1.150)0.368 -0.219
(-1.917)-0.123
(-0.958)-0.110
(-0.879)0.550
(0.745)0.254 -0.097
(-0.478)-0.123
(-0.958)-0.110
(-0.879)High 0.766 0.837
(1.045)0.331 -0.401
(-2.412)-0.298
(-1.759)-0.282
(-1.670)0.555
(0.729)0.250 -0.177
(-0.849)-0.298
(-1.759)-0.282
(-1.670)High-Low -0.097
(-0.448)-0.426
(-1.527)-0.256
(-0.998)-0.251
(-0.971)0.055
(0.161)-0.146
(-0.378)-0.256
(-0.998)-0.251
(-0.971)
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表 9 不确定性上升下降时期的单变量组合分析
组别 βMU 等权组合预期收益率 加权组合预期收益率 RET-RF SR α3 α5 α6 RET-RF SR α3 α5 α6 A栏：不确定性上升时期 Low -0.611 1.919
(2.059)0.691 0.099
(0.457)0.178
(0.791)0.185
(0.807)1.507
(1.800)0.597 0.001
(0.006)0.178
(0.791)0.185
(0.807)2 -0.160 1.760
(1.911)0.634 -0.168
(-1.034)-0.042
(-0.256)-0.037
(-0.228)1.509
(1.796)0.592 -0.117
(-0.847)-0.042
(-0.256)-0.037
(-0.228)3 -0.016 1.761
(1.929)0.637 -0.200
(-1.197)-0.036
(-0.218)-0.037
(-0.225)1.370
(1.652)0.533 -0.298
(-1.425)-0.036
(-0.218)-0.037
(-0.225)4 0.130 1.599
(1.722)0.569 -0.370
(-2.068)-0.235
(-1.398)-0.231
(-1.370)1.436
(1.614)0.539 -0.267
(-1.146)-0.235
(-1.398)-0.231
(-1.370)High 0.583 1.236
(1.375)0.444 -0.692
(-3.691)-0.550
(-2.964)-0.529
(-2.711)1.095
(1.321)0.416 -0.545
(-2.634)-0.550
(-2.964)-0.529
(-2.711)High-Low -0.683
(-2.736)-0.791
(-3.392)-0.728
(-3.070)-0.714
(-2.933)-0.412
(-1.458)-0.547
(-1.890)-0.728
(-3.070)-0.714
(-2.933)B栏：不确定性下降时期 Low -0.599 0.904
(0.897)-0.599 0.054
(0.241)0.125
(0.631)0.155
(0.757)0.577
(0.570)0.231 0.253
(0.965)0.125
(0.631)0.155
(0.757)2 -0.157 0.938
(0.960)-0.157 0.041
(0.190)0.241
(1.112)0.262
(1.179)0.428
(0.442)0.177 0.028
(0.106)0.241
(1.112)0.262
(1.179)3 -0.009 1.088
(1.143)-0.009 0.031
(0.133)0.274
(1.495)0.286
(1.587)0.593
(0.682)0.248 -0.053
(-0.213)0.274
(1.495)0.286
(1.587)4 0.142 1.161
(1.175)0.142 -0.052
(-0.237)0.319
(1.743)0.337
(1.921)0.530
(0.564)0.209 -0.197
(-0.768)0.319
(1.743)0.337
(1.921)High 0.567 0.847
(0.899)0.567 -0.183
(-0.794)0.079
(0.400)0.087
(0.451)0.420
(0.473)0.167 -0.043
(-0.156)0.079
(0.400)0.087
(0.451)High-Low -0.057
(-0.279)-0.237
(-0.894)-0.046
(-0.184)-0.069
(-0.257)-0.158
(-0.549)-0.296
(-0.683)-0.046
(-0.184)-0.069
(-0.257)
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表 10 个股宏观经济不确定性beta的持续性
变量 (1) (2) (3) (4) (5) (6) n=3 n=6 n=12 n=24 n=36 n=48 βMU 0.715***(31.577) 0.559***(21.019) 0.370***(14.519) 0.204***(10.176) 0.121***(7.690) 0.040***(6.387) βMKT 0.001(1.015) 0.002(0.753) 0.002(0.580) 0.003**(2.163) 0.002**(2.392) 0.001***(3.920) SIZE -0.000(-0.096) 0.000(0.039) 0.000(0.100) 0.000(1.014) 0.000***(2.698) 0.000***(3.099) ILLIQ 0.193**(2.504) 0.267**(2.538) 0.345**(2.365) 0.340*(1.963) 0.131(1.008) -0.083*(-1.693) SHREV 0.009(0.754) 0.012(0.856) 0.014(0.777) -0.013(-0.510) -0.044(-1.393) -0.083*(-1.964) MOM 0.005(0.504) -0.001(-0.069) -0.026(-0.962) -0.066*(-1.706) -0.067(-1.563) 0.065(0.949) ROE -0.016(-1.329) -0.045***(-3.283) -0.101***(-2.779) -0.061(-1.191) -0.026(-0.691) 0.007(0.228) PE 0.000*(1.814) 0.000***(4.412) 0.000***(5.226) 0.000***(5.230) 0.000***(4.839) 0.000***(3.161) BM 0.037***(3.099) 0.062***(3.318) 0.077***(3.145) 0.057*(1.940) 0.020(0.847) 0.037*(1.786) AG 0.006(0.947) -0.005(-0.512) -0.014(-1.548) -0.018(-1.414) -0.005(-0.278) 0.003(0.328) Constant -0.042**(-2.442) -0.058**(-2.416) -0.059**(-2.319) -0.058**(-2.265) -0.032(-1.466) -0.059**(-2.253) N 306 399 296 128 277 716 246 715 222 599 201 208 Adj. R2 0.706 0 0.547 4 0.234 1 0.233 9 0.192 5 0.170 0
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表 11 未来多期宏观经济不确定性beta的单变量组合分析
组别 βMU 等权组合收益情况 加权组合收益情况 RET-RF SR α3 α5 α7 RET-RF SR α3 α5 α7 A栏：未来3个月宏观经济不确定性beta的组合分析(βMU_h(3)) Low -0.739 1.355
(2.044)0.506 0.035
(0.309)0.069
(0.578)0.084
(0.663)1.047
(1.699)0.429 0.065
(0.432)0.079
(0.491)0.084
(0.511)2 -0.235 1.411
(2.042)0.523 0.017
(0.161)0.152
(1.269)0.160
(1.320)1.110
(1.664)0.451 0.093
(0.717)0.193
(1.225)0.192
(1.240)3 -0.032 1.333
(1.945)0.499 -0.049
(-0.478)0.076
(0.655)0.080
(0.681)0.938
(1.422)0.395 -0.051
(-0.404)0.039
(0.267)0.042
(0.287)4 0.211 1.163
(1.711)0.443 -0.178
(-1.855)-0.063
(-0.600)-0.055
(-0.518)0.824
(1.331)0.356 -0.064
(-0.575)0.002
(0.019)0.008
(0.064)High 0.823 0.964
(1.390)0.361 -0.311
(-2.311)-0.247
(-1.831)-0.245
(-1.828)0.515
(0.756)0.210 -0.337
(-2.090)-0.263
(-1.690)-0.258
(-1.640)High-Low -0.391
(-2.282)-0.346
(-2.535)-0.316
(-2.133)-0.329
(-2.173)-0.532
(-2.535)-0.403
(-2.194)-0.341
(-1.802)-0.342
(-1.782)B栏：未来6个月宏观经济不确定性beta的组合分析(βMU_h(6)) Low -1.158 1.376
(2.074)0.513 0.052
(0.464)0.094
(0.763)0.109
(0.844)1.070
(1.738)0.437 0.084
(0.576)0.113
(0.726)0.120
(0.753)2 -0.241 1.418
(2.045)0.524 0.013
(0.120)0.144
(1.195)0.151
(1.240)1.139
(1.704)0.465 0.114
(0.851)0.196
(1.191)0.198
(1.210)3 -0.013 1.311
(1.907)0.490 -0.074
(-0.727)0.046
(0.397)0.049
(0.424)0.905
(1.377)0.383 -0.065
(-0.543)0.005
(0.038)0.006
(0.043)4 0.236 1.185
(1.750)0.453 -0.150
(-1.513)-0.028
(-0.271)-0.020
(-0.189)0.828
(1.341)0.358 -0.062
(-0.536)0.029
(0.234)0.036
(0.285)High 1.402 0.938
(1.355)0.351 -0.328
(-2.438)-0.266
(-1.967)-0.265
(-1.974)0.503
(0.735)0.204 -0.354
(-2.207)-0.277
(-1.807)-0.275
(-1.779)High-Low -0.438
(-2.744)-0.381
(-2.792)-0.360
(-2.376)-0.374
(-2.429)-0.567
(-2.624)-0.438
(-2.375)-0.390
(-2.084)-0.395
(-2.087)C栏：未来12个月宏观经济不确定性beta的组合分析(βMU_h(12)) Low -1.619 1.383
(2.053)0.510 0.030
(0.255)0.076
(0.594)0.091
(0.683)1.092
(1.744)0.440 0.068
(0.450)0.081
(0.494)0.089
(0.534)2 -0.472 1.401
(2.051)0.521 0.002
(0.018)0.134
(1.107)0.142
(1.157)1.087
(1.685)0.450 0.095
(0.695)0.148
(0.951)0.158
(1.006)3 -0.060 1.306
(1.895)0.493 -0.063
(-0.681)0.060
(0.550)0.065
(0.587)0.938
(1.433)0.403 -0.014
(-0.132)0.049
(0.409)0.466
(0.385)4 0.628 1.202
(1.766)0.456 -0.147
(-1.418)-0.032
(-0.290)-0.024
(-0.219)0.788
(1.256)0.337 -0.118
(-0.895)-0.005
(-0.033)0.003
(0.023)High 1.979 0.935
(1.361)0.351 -0.309
(-2.274)-0.250
(-1.809)-0.250
(-1.837)0.531
(0.774)0.214 -0.321
(-1.957)-0.233
(-1.434)-0.232
(-1.439)High-Low -0.449
(-2.721)-0.339
(-2.400)-0.326
(-2.001)-0.341
(-2.086)-0.560
(-2.564)-0.389
(-2.107)-0.314
(-2.539)-0.322
(-1.686)
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表 12 稳健宏观经济不确定性beta的单变量组合分析
组别 βMU 等权组合预期收益率 加权组合预期收益率 RET-RF SR α3 α5 α6 RET-RF SR α3 α5 α6 A栏：根据公式(4)计算不确定性beta Low -0.678 1.330
(2.128)0.487 0.022
(0.164)0.071
(0.554)0.086
(0.656)1.006
(1.713)0.403 0.049
(0.323)0.071
(0.554)0.086
(0.656)2 -0.172 1.313
(2.104)0.486 -0.048
(-0.475)0.064
(0.643)0.071
(0.714)0.915
(1.510)0.368 -0.058
(-0.510)0.064
(0.643)0.071
(0.714)3 -0.019 1.334
(2.201)0.508 -0.055
(-0.506)0.097
(0.918)0.105
(0.997)0.977
(1.626)0.389 -0.029
(-0.219)0.097
(0.918)0.105
(0.997)4 0.137 1.307
(1.999)0.463 -0.198
(-1.786)0.004
(0.036)0.010
(0.084)0.951
(1.528)0.364 -0.148
(-1.125)0.004
(0.036)0.010
(0.084)High 0.652 1.038
(1.628)0.370 -0.422
(-3.496)-0.267
(-2.151)-0.255
(-2.037)0.711
(1.164)0.269 -0.330
(-0.156)-0.267
(-2.151)-0.255
(-2.037)High-Low -0.292
(-1.966)-0.444
(-3.080)-0.338
(-2.282)-0.341
(-2.252)-0.295
(-1.989)-0.380
(-1.708)-0.338
(-2.282)-0.341
(-2.252)B栏：根据公式(5)计算不确定性beta Low -0.699 1.395
(2.202)0.511 0.038
(0.285)0.087
(0.694)0.101
(0.789)0.971
(1.616)0.390 0.050
(0.323)0.087
(0.694)0.101
(0.789)2 -0.168 1.322
(2.089)0.483 -0.069
(-0.651)0.046
(0.446)0.054
(0.516)0.998
(1.644)0.392 -0.026
(-0.218)0.046
(0.446)0.054
(10.516)3 -0.017 1.354
(2.155)0.496 -0.040
(-0.372)0.121
(1.133)0.125
(1.200)0.989
(1.632)0.398 -0.024
(-0.203)0.121
(1.133)0.125
(1.200)4 0.137 1.298
(2.016)0.461 -0.198
(-1.779)0.003
(0.025)0.012
(0.104)0.966
(1.590)0.367 -0.143
(-1.025)0.003
(0.025)0.012
(0.104)High 0.629 1.004
(1.599)0.362 -0.433
(-3.632)-0.288
(-2.385)-0.275
(-2.233)0.612
(1.010)0.236 -0.398
(-2.939)-0.288
(-2.385)-0.275
(-2.233)High-Low -0.391
(-2.443)-0.471
(-3.248)-0.375
(-2.567)-0.376
(-2.489)-0.359
(-1.827)-0.448
(-2.111)-0.375
(-2.567)-0.376
(-2.489)
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[1] BANSAL R, YARON A. Risks for the long run: a potential resolution of asset pricing puzzles[J]. The Journal of Finance, 2004, 59(4): 1481-1509. doi: 10.1111/j.1540-6261.2004.00670.x [2] MERTON R C. An intertemporal capital asset pricing model[J]. Econometrica: Journal of the Econometric Society, 1973: 867-887. [3] BALI T G, BROWN S J, TANG Y. Is economic uncertainty priced in the cross-section of stock returns?[J]. Journal of Financial Economics, 2017, 126(3): 471-489. doi: 10.1016/j.jfineco.2017.09.005 [4] CARPENTER J N, LU F, WHITELAW R F. The real value of China's stock market[J]. Journal of Financial Economics, 2021, 139(3): 679-696. doi: 10.1016/j.jfineco.2020.08.012 [5] 刘金全, 崔畅. 中国沪深股市收益率和波动性的实证分析[J]. 经济学(季刊), 2002(4): 885-898. https://www.cnki.com.cn/Article/CJFDTOTAL-JJXU200203007.htm [6] 刘伟, 戴冰清. 不确定性如何影响上市公司R&D投入?——基于战略成长期权视角[J]. 金融教育研究, 2022(4): 49-58. [7] 邢红卫, 王汉瑛. 经济政策不确定性贝塔溢价: 基于确定效应的解释[J]. 上海财经大学学报, 2021(3): 64-78. https://www.cnki.com.cn/Article/CJFDTOTAL-SCJB202103005.htm [8] 强国令, 王伟涛, 董雅洁. 全球金融周期加剧了跨境资本流动吗——来自结构视角的跨国样本证据[J]. 广东财经大学学报, 2023(6): 33-53. http://xb.gdufe.edu.cn/article/id/02324f15-78dc-4905-9c94-a90081e5b25b [9] LI T, MA F, ZHANG X, et al. Economic policy uncertainty and the Chinese stock market volatility: novel evidence[J]. Economic Modelling, 2020, 87: 24-33. doi: 10.1016/j.econmod.2019.07.002 [10] JURADO K, LUDVIGSON S C, NG S. Measuring uncertainty[J]. American Economic Review, 2015, 105(3): 1177-1216. doi: 10.1257/aer.20131193 [11] 黄卓, 邱晗, 沈艳, 等. 测量中国的金融不确定性——基于大数据的方法[J]. 金融研究, 2018(11): 30-46. https://www.cnki.com.cn/Article/CJFDTOTAL-JRYJ201811003.htm [12] BAKER S R, BLOOM N, DAVIS S J. Measuring economic policy uncertainty[J]. The Quarterly Journal of Economics, 2016, 131(4): 1593-1636. doi: 10.1093/qje/qjw024 [13] HUSTED L, ROGERS J, SUN B. Monetary policy uncertainty[J]. Journal of Monetary Economics, 2020, 115: 20-36. doi: 10.1016/j.jmoneco.2019.07.009 [14] OZTURK E O, SHENG X S. Measuring global and country-specific uncertainty[J]. Journal of International Money and Finance, 2018, 88: 276-295. doi: 10.1016/j.jimonfin.2017.07.014 [15] BLOOM N. The impact of uncertainty shocks[J]. Econo: Metrica, 2009, 77(3): 623-685. doi: 10.3982/ECTA6248 [16] ALTIG D, BAKER S, BARRERO J M, et al. Economic uncertainty before and during the COVID-19 pandemic[J]. Journal of Public Economics, 2020, 191: 104274-124286. doi: 10.1016/j.jpubeco.2020.104274 [17] MANKIW N G, REIS R, WOLFERS J. Disagreement about inflation expectations[J]. NBER Macroeconomics Annual, 2003, 18: 209-248. doi: 10.1086/ma.18.3585256 [18] 林建浩, 李幸, 李欢. 中国经济政策不确定性与资产定价关系实证研究[J]. 中国管理科学, 2014(S1): 222-226. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGK2014S1036.htm [19] 王晓娟, 郭守亭, 岳晓. 经济政策不确定性和股票收益的联动性——基于子样本滚动窗口估计法的研究[J]. 学习与实践, 2015(5): 26-32. https://www.cnki.com.cn/Article/CJFDTOTAL-XXYS201505003.htm [20] 覃甜雨. 基于经济不确定性视角的资产定价研究[D]. 北京: 对外经济贸易大学, 2022. [21] 祝梓翔, 程翔, 邓翔. 中国宏观经济不确定性的测度[J]. 统计与决策, 2021(16): 110-113. https://www.cnki.com.cn/Article/CJFDTOTAL-TJJC202116025.htm [22] 马丹, 何雅兴, 翁作义. 大维不可观测变量的中国宏观经济不确定性测度研究[J]. 统计研究, 2018(10): 44-57. https://www.cnki.com.cn/Article/CJFDTOTAL-TJYJ201810004.htm [23] 王霞, 郑挺国. 基于实时信息流的中国宏观经济不确定性测度[J]. 经济研究, 2020(10): 55-71. https://www.cnki.com.cn/Article/CJFDTOTAL-JJYJ202010005.htm [24] 李志冰, 杨光艺, 冯永昌, 等. Fama-French五因子模型在中国股票市场的实证检验[J]. 金融研究, 2017(6): 191-206. https://www.cnki.com.cn/Article/CJFDTOTAL-JRYJ201706014.htm [25] FAMA E F, FRENCH K R. A five-factor asset pricing model[J]. Journal of Financial Economics, 2015, 116(1): 1-22. doi: 10.1016/j.jfineco.2014.10.010 [26] 于增彪, 梁文涛. 股票发行定价体制与新上市A股初始投资收益[J]. 金融研究, 2004(8): 51-58. https://www.cnki.com.cn/Article/CJFDTOTAL-JRYJ200408006.htm [27] CARHART M M. On persistence in mutual fund performance[J]. The Journal of Finance, 1997, 52(1): 57-82. doi: 10.1111/j.1540-6261.1997.tb03808.x [28] AMIHUD Y, HAMEED A, KANG W, et al. The illiquidity premium: international evidence[J]. Journal of Financial Economics, 2015, 117(2): 350-368. doi: 10.1016/j.jfineco.2015.04.005 [29] 花拥军, 王冰, 李庆. 企业社会责任, 经济政策不确定性与融资约束——基于社会责任"累积-保险" 效应的研究视角[J]. 南方经济, 2020(11): 116-131. https://www.cnki.com.cn/Article/CJFDTOTAL-NFJJ202011009.htm [30] 钟宁桦, 刘志阔, 何嘉鑫, 等. 我国企业债务的结构性问题[J]. 经济研究, 2016(7): 102-117. https://www.cnki.com.cn/Article/CJFDTOTAL-JJYJ201607009.htm [31] 林毅夫, 刘明兴, 章奇. 政策性负担与企业的预算软约束: 来自中国的实证研究[J]. 管理世界, 2004(8): 81-89. https://www.cnki.com.cn/Article/CJFDTOTAL-GLSJ200408009.htm [32] 赵兴庐, 刘衡, 张建琦. 市场化程度的感知、产权制度与企业创新精神: 国有和民营企业的比较研究[J]. 南方经济, 2014(5): 25-41. https://www.cnki.com.cn/Article/CJFDTOTAL-NFJJ201405003.htm [33] LONDON T, HART S L. Reinventing strategies for emerging markets: beyond the transnational model[J]. Journal of International Business Studies, 2004, 35(5): 350-370. doi: 10.1057/palgrave.jibs.8400099 [34] SHARMA S S, NARAYAN P K, ZHENG X. An analysis of firm and market volatility[J]. Economic Systems, 2014, 38(2): 205-220. doi: 10.1016/j.ecosys.2013.12.003 [35] PEREZ-QUIROS G, TIMMERMANN A. Firm size and cyclical variations in stock returns[J]. The Journal of Finance, 2000, 55(3): 1229-1262. doi: 10.1111/0022-1082.00246 [36] DAHLQUIST M, ROBERTSSON G. Direct foreign ownership, institutional investors, and firm characteristics[J]. Journal of Financial Economics, 2001, 59(3): 413-440. doi: 10.1016/S0304-405X(00)00092-1 [37] BAELE L, BEKAERT G, INGHELBRECHT K, et al. Flights to safety[J]. The Review of Financial Studies, 2020, 33(2): 689-746. -
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