什么叫股权风险溢价「股权溢价是什么意思」

发表于河南

一、ERP是什么：

1.股权风险溢价ERP(equity risk premium)又叫股债利差，指市场投资组合或具有市场平均风险的股票收益率与无风险收益率的差额。差额越大，未来权益类投资潜在收益偏高，适合超配股票。差额越小，未来权益类投资潜在收益偏低，适宜降低股票仓位。我们用股权风险溢价指标来反应投资者的风险偏好，可以作为市场风险偏好指标。

2.公式：股权风险溢价=1/PE-r 注: PE用上证指数的历史TTM市盈率代替，1/PE代表股票市场整体潜在的盈利收益率；r代表市场无风险利率，用盈利收益率与十年期国债收益率比值(上证)代替。

3.结论：历史上4 个底部股权风险溢价情况来看，市场见底时，市场风险偏好高位滞涨，且市场处在低位(股权风险溢价处在高位)。当市场见底后，股票市场处于底部震荡，而市场风险偏好也在高位震荡。当市场突破底部区间震荡上行时，风险偏好也会快速下行。二、股债比是什么：1.股债比是指市场投资组合或具有市场平均风险的股票收益率与无风险收益率的比值。我们用股债比指标来反应投资者的风险偏好，可以作为市场风险偏好指标。2.公式：股债比=1/PE:r

三、股债性价比:该模型由美联储FED提出，也叫FED模型或股债风险溢价率。我们用指数市盈率的倒数(即EPS/Price)来代表持有股市的预期收益率，用十年期国债收益率代表持有债券的预期收益率。二者差值大于0代表股市预期收益更好，反之亦然。该差值与其长期均值的偏离度。代表当前股市性价比的高低程度。正向偏离越多则股市越有价值，应该高配，反之亦然

四，股息率溢价

股票安全性:我们股票指数的股息率来代表持有股市的预期收益率，用十年期国债收益率代表持有债券的预期收益率。二者差值大于0代表股市安全性更好，反之亦然。该差值与其长期均值的偏离度，代表当前股市安全性的高低程度。正向偏离越多则股市安全性越高，可以高配，反之亦然。

如何自己画图

股债比值与上证指数走势绘图步骤

参考网站：http://www.woniu500.com/zsbk/erp.html

1.用电脑在浏览器里打开以下地址：

https://echarts.apache.org/examples/zh/editor.html?c=line-simple

2清空左边输入框里面全部内容，

3.用记事本打开“02股债比值与上证指数走势图txt”文件，然后按”Ctrl A”键选中“02股债比值与上证指数走势图txt”里面全部内容，接着按”Ctrl C”键复制“02股债比值与上证指数走势图以下所有代码，里面全部内容，最后切换到步骤2中清空的输入框，并按”Ctrl V”键将复制的内容复制到步骤2中清空的输入框里面，并按”运行按”钮,显示见下图：

option = {

tooltip: {

trigger: 'axis',

axisPointer: {

type: 'cross',

crossStyle: {

color: '#999'

}

}

},

toolbox: {

feature: {

dataView: {show: true, readOnly: false},

magicType: {show: true, type: ['line', 'bar']},

restore: {show: true},

saveAsImage: {show: true}

}

},

legend: {

data: ['股债比', '上证指数']

},

xAxis: [

{

type: 'category',

data: ['200201', '200202', '200203', '200204', '200205', '200206', '200207', '200208', '200209', '200210', '200211', '200212', '200301', '200302', '200303', '200304', '200305', '200306', '200307', '200308', '200309', '200310', '200311', '200312', '200401', '200402', '200403', '200404', '200405', '200406', '200407', '200408', '200409', '200410', '200411', '200412', '200501', '200502', '200503', '200504', '200505', '200506', '200507', '200508', '200509', '200510', '200511', '200512', '200601', '200602', '200603', '200604', '200605', '200606', '200607', '200608', '200609', '200610', '200611', '200612', '200701', '200702', '200703', '200704', '200705', '200706', '200707', '200708', '200709', '200710', '200711', '200712', '200801', '200802', '200803', '200804', '200805', '200806', '200807', '200808', '200809', '200810', '200811', '200812', '200901', '200902', '200903', '200904', '200905', '200906', '200907', '200908', '200909', '200910', '200911', '200912', '201001', '201002', '201003', '201004', '201005', '201006', '201007', '201008', '201009', '201010', '201011', '201012', '201101', '201102', '201103', '201104', '201105', '201106', '201107', '201108', '201109', '201110', '201111', '201112', '201201', '201202', '201203', '201204', '201205', '201206', '201207', '201208', '201209', '201210', '201211', '201212', '201301', '201302', '201303', '201304', '201305', '201306', '201307', '201308', '201309', '201310', '201311', '201312', '201401', '201402', '201403', '201404', '201405', '201406', '201407', '201408', '201409', '201410', '201411', '201412', '201501', '201502', '201503', '201504', '201505', '201506', '201507', '201508', '201509', '201510', '201511', '201512', '201601', '201602', '201603', '201604', '201605', '201606', '201607', '201608', '201609', '201610', '201611', '201612', '201701', '201702', '201703', '201704', '201705', '201706', '201707', '201708', '201709', '201710', '201711', '201712', '201801', '201802', '201803', '201804', '201805', '201806', '201807', '201808', '201809', '201810', '201811', '201812', '201901', '201902', '201903', '201904', '201905', '201906', '201907', '201908', '201909', '201910', '201911', '201912', '202001', '202002', '202003', '202004', '202005', '202006', '202007', '202008'],

axisPointer: {

type: 'shadow'

}

}

],

yAxis: [

{

type: 'value',

name: '%',

},

{

type: 'value',

name: '上证指数',

}

],

series: [

{

name: '股债比',

type: 'line',

// stack: '总量1',

data: ['0.94', '0.93', '0.94', '1.01', '1.09', '0.87', '0.82', '0.77', '0.81', '0.86', '0.79', '0.91', '0.86', '0.85', '0.90', '0.92', '0.93', '0.91', '0.95', '1.01', '0.90', '0.93', '0.78', '0.71', '0.69', '0.66', '0.61', '0.58', '0.78', '0.86', '0.82', '0.75', '0.73', '0.82', '0.73', '0.87', '0.89', '0.83', '1.04', '1.07', '1.71', '1.71', '1.84', '1.66', '1.84', '2.08', '1.92', '1.89', '1.92', '1.90', '1.91', '1.69', '1.66', '1.56', '1.53', '1.52', '1.54', '1.48', '1.28', '0.99', '0.85', '0.80', '0.66', '0.52', '0.57', '0.52', '0.45', '0.39', '0.35', '0.31', '0.41', '0.38', '0.48', '0.49', '0.63', '0.58', '0.92', '1.07', '1.07', '1.29', '1.42', '2.28', '2.17', '2.42', '1.99', '1.85', '1.60', '1.55', '1.43', '1.19', '0.95', '1.23', '1.18', '1.04', '1.00', '0.95', '1.06', '1.10', '1.04', '1.17', '1.54', '1.65', '1.53', '1.56', '1.51', '1.20', '1.17', '1.19', '1.15', '1.13', '1.12', '1.13', '1.60', '1.56', '1.53', '1.58', '1.82', '1.78', '1.95', '2.17', '2.09', '1.90', '2.06', '1.92', '2.36', '2.53', '2.69', '2.67', '2.57', '2.50', '2.64', '2.28', '2.14', '2.16', '2.32', '2.45', '2.46', '2.80', '2.62', '2.29', '2.24', '2.16', '2.0', '2.0', '2.1', '2.10', '2.08', '2.18', '2.52', '2.51', '2.22', '2.21', '2.19', '2.26', '2.16', '1.73', '1.79', '1.79', '1.44', '1.32', '1.27', '1.33', '1.60', '1.90', '2.05', '1.96', '1.93', '2.01', '2.56', '2.60', '2.33', '2.34', '2.34', '2.44', '2.44', '2.36', '2.43', '2.32', '2.05', '2.09', '1.83', '1.80', '1.81', '1.73', '1.68', '1.65', '1.58', '1.53', '1.54', '1.40', '1.42', '1.42', '1.33', '1.43', '1.50', '1.59', '1.82', '2.04', '2.01', '2.06', '1.96', '2.19', '2.30', '2.48', '2.49', '2.13', '2.10', '1.91', '2.28', '2.24', '2.28', '2.39', '2.30', '2.18', '2.28', '2.16', '2.28', '2.52', '2.82', '2.77', '2.8', '2.45', '2.17', '2.03']

},

{

name: '上证指数',

type: 'line',

// stack: '总量2',

yAxisIndex: 1,

data: ['1491.67', '1524.70', '1603.91', '1667.75', '1515.73', '1732.76', '1651.59', '1666.62', '1581.62', '1507.50', '1434.18', '1357.65', '1499.82', '1511.93', '1510.58', '1521.44', '1576.26', '1486.02', '1476.74', '1421.98', '1367.16', '1348.30', '1397.23', '1497.04', '1590.73', '1675.07', '1741.62', '1595.59', '1555.91', '1399.16', '1386.20', '1342.06', '1396.70', '1320.54', '1340.77', '1266.50', '1191.82', '1306.00', '1181.24', '1159.15', '1060.74', '1080.94', '1083.03', '1162.80', '1155.61', '1092.82', '1099.26', '1161.06', '1258.05', '1299.03', '1298.30', '1440.22', '1641.30', '1672.21', '1612.73', '1658.64', '1752.42', '1837.99', '2099.29', '2675.47', '2786.34', '2881.07', '3183.98', '3841.27', '4109.65', '3820.70', '4471.03', '5218.83', '5552.30', '5954.77', '4871.78', '5261.56', '4383.39', '4348.54', '3472.71', '3693.11', '3433.35', '2736.10', '2775.72', '2397.37', '2293.78', '1728.79', '1871.16', '1820.81', '1990.66', '2082.85', '2373.21', '2477.57', '2632.93', '2959.36', '3412.06', '2667.75', '2779.43', '2995.85', '3195.30', '3277.14', '2989.29', '3051.94', '3109.11', '2870.61', '2592.15', '2398.37', '2637.50', '2638.80', '2655.66', '2978.84', '2820.18', '2808.08', '2790.69', '2905.05', '2928.11', '2911.51', '2743.47', '2762.08', '2701.73', '2567.34', '2359.22', '2468.25', '2333.41', '2199.42', '2292.61', '2428.49', '2262.79', '2396.32', '2372.32', '2225.43', '2103.63', '2047.52', '2086.17', '2068.88', '1980.12', '2269.13', '2385.42', '2365.59', '2236.62', '2177.91', '2300.6', '1979.21', '1993.80', '2098.38', '2174.67', '2141.61', '2220.50', '2115.98', '2033.08', '2056.30', '2033.31', '2026.36', '2039.21', '2048.33', '2201.56', '2217.2', '2363.87', '2420.18', '2682.83', '3234.68', '3210.36', '3310.30', '3747.90', '4441.65', '4611.74', '4277.22', '3663.73', '3205.99', '3052.78', '3382.56', '3445.40', '3539.18', '2737.6', '2687.98', '3003.92', '2938.32', '2916.62', '2929.61', '2979.34', '3085.49', '3004.70', '3100.49', '3250.03', '3103.64', '3159.17', '3241.73', '3222.51', '3154.66', '3105.54', '3192.43', '3273.03', '3360.81', '3348.94', '3393.34', '3317.19', '3307.17', '3462.08', '3259.41', '3168.90', '3082.23', '3095.47', '2847.42', '2876.4', '2725.25', '2821.35', '2602.78', '2588.19', '2493.9', '2584.57', '2940.95', '3090.76', '3078.34', '2898.70', '2978.88', '2932.51', '2886.24', '2905.19', '2929.06', '2871.98', '3050.12', '2976.53', '2880.3', '2750.3', '2860.08', '2852.35', '2984.67', '3310.01', '3395.68']

}

]

};

4.最终绘图结果见下图：

5.简单介绍一下代码所对应绘图的位置：

6.补充：自己怎样填充数据呢？我拿填充9月22日的数据剧烈说明

A.用浏览器器打开上证证券交易所官网：

http://www.sse.com.cn/market/stockdata/overview/day/

找到以下图片平均市盈率数据，结果显示是PE：15.52

B.用浏览器打开查询十年期国债收益率的网站：

https://cn.investing.com/rates-bonds/china-10-year-bond-yield

查到22日数据是3.115，那么22日的股债比=100/15.52/3.115=2.07

C.用浏览器打开查看指数点数的网站

查到22日的点数是：3274.30

http://quote.eastmoney.com/zs000001.html

这个数字，在哪里都可以找到，就不多说了

D.用记事本打开“02股债比值与上证指数走势图txt”文件，在以下三个区域分别加上数据，加完后按“Ctrl S”保存，保存后按“Ctrl C”复制记事本里面内容到步骤2-3里面的输入框里，并按执行后，显示如下图：

注意：1.我的网站http://www.woniu500.com是每个月的月底生成数据，所以大家也可以用每个月月底的最后一天当做当月数据，2.加数据时记得把你的输入法切换到英文，加数据格式是：逗号 单引号，单引号里面放数据。

不懂的话，私聊我吧

其实很简单，就是看看这个阶段，投股票划算还是债券划算？