MBA智库文档金融证券投资股票随机贴现因子方差界与股权溢价之谜——来自中国股市的经验分析.doc

随机贴现因子方差界与股权溢价之谜——来自中国股市的经验分析.doc

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随机贴现因子方差界与股权溢价之谜 ——来自中国股市的经验分析肖俊喜1 王庆石2 （辽宁大连东北财经大学，1数量经济系，2国际商学院，116025）内容摘要：本文在市场是否存在摩擦以及有无条件信息情形下，使用随机贴现因子方差界对具有可加的时间可分离的常数相对风险规避系数的期望效用的标准的基于消费的资本资产定价模型和具有递归的非期望效用的基于消费的资本资产定价模型进行了模拟分析，发现：（1）中国股票市场不像美国等发达国家资本市场那样存在股权溢价之谜现象；（2）在同样的情形下，具有递归的非期望效用的基于消费的资本资产定价模型在证实和解释目前中国股票市场经验上不存在股权溢价之谜方面基本上优于具有可加的时间可分离的常数相对风险规避系数的期望效用的标准的基于消费的资本资产定价模型；（3）在条件信息下中国股票市场上代表性投资者或消费者对偏好于早期不确定性，但在无条件信息下对不确定性的解的偏好是不确定的。关键词：随机贴现因子方差界股权溢价之谜基于消费的资本资产定价模型常数相对风险规避系数中图分类号：F830 文献标识码：C15、G12 一、引言在国外，研究人员使用Hansen与Jagannathan(1991)随机贴现因子方差界或Hansen与Singleton(1982)广义矩法（GMM）对最常见的具有可加的时间可分离的常数相对风险规避系数的期望效用的基于消费的资本资产定价模型（或标准的基于消费的资本资产定价模型）进行经验检验中，发现一个重要问题就是美国等发达国家资本市场存在“股权溢价之谜（Equity Premium Puzzle）①” （最早提出“股权溢价之谜”之说的是Mehra与Prescott(1985)）。在国内，李治国与唐国兴(2002)利用我国1994年1季度至2001年4季度股市数据和消费数据，采用工具变量（IV）回归法估计了线性的具有可加的时间可分离的常数相对风险规避系数的期望效用的基于消费的资本资产定价模型，经验上证实了中国股票市场存在股权溢价之谜现象。但肖俊喜与王庆石(2004)利用中国1993年7月至2003年12月月度数据使用广义矩法（GMM）估计了非线性的具有可加的时间可分离的常数相对风险规避系数的期望效用的基于消费的资本资产定价模型，经验上证实中国股票市场并不像美国等发达国家资本市场那样存在股权溢价之谜现象。本文试图在肖俊喜与王庆石(2004)所使用的数据基础上，在市场是否存在摩擦以及有无条件信息情形下利用随机贴现因子方差界对具有可加的时间可分离的常数相对风险规避系数的期望效用的基于消费的资本资产定价模型（或标准的基于消费的资本资产定价模型）和具有递归的非期望效用的基于消费的资本资产定价模型（或Epstein-Zin-Weil模型）进行模拟分析，并围绕着中国股票市场经验上是否存在股权溢价之谜现象这一论题展开全文，获得了一些有意义的经验结论。本文余下部分安排如下：第二部分给出了本文所研究的理论模型；第三部分给出了随机贴现因子方差界（Hansen-Jagannathan方差界和倍增方差界）；第四部分介绍了样本数据并对其进行了描述性统计分析；在第五部分，给出了标准的基于消费的资本资产定价模型和Epstein-Zin-Weil模型的模拟结果；最后一部分对全文进行总结。二、理论模型 1. 一般的资产定价方程根据一价律②，在无摩擦市场，存在某个随机变量，使得任意金融资产在时刻价格等于在时刻的可获得的信息下与时刻收入（Payoff）之积的条件期望，即 (1) 在金融经济学中，将方程(1)称之为一般的资产定价方程（在具体条件下，由方程(1)可推导诸如股票、债券、期权、期货等资产的定价公式）。满足于方程(1)的随机变量被称之为随机贴现因子(SDF)。可将方程(1)等价地变换为 (2) 这里，是金融资产在时刻总收益。方程(2)表明在无摩擦市场，存在随机贴现因子，使得任意金融资产在时刻总收益在时刻的可获得的信息下与之积的条件期望等于1。考虑个金融资产，可用向量形式将方程(2)表示为 (3) 这里，是个金融资产在时刻总收益率列向量；是每个元素都为1的维列向量。如果考虑到市场存在摩擦，那么一般的资产定价方程(3)可用下列方程代替： (4) 这里，是维常数列向量，而且但。于是，不论市场是否存在摩擦，可将方程(3)与(4)合并为 (5) 这里，维常数列向量。将累期望法则作用于方程(5)，便有 (6) 2. 具有可加的时间可分离的常数相对风险规避系数的期望效用的基于消费的资本资产定价模型假定在纯交换经济中同质的代表性投资者在非线性预算约束下追求个人期望效用最大化。代表性投资者在时刻效用函数和预算约束分别是 (7) ， (8) 这里，是代表性投资者在时刻关于消费二次可微的连续效用函数；是代表性投资者在时刻的总财富；是资产在时刻的实际总收益；是时刻资产在市场组合中所占份额；是资产数； ()是时间贴现因子。将期间效用函数设定为 (9) 其中，是常数相对风险规避系数。如果以式(7)为目标函数，那么连同期间效用函数(9)在非线性方程(8)预算约束下，二次规划最优解满足下列一阶条件或欧拉方程：， (10) 一般地，将方程(10)称之为具有可加的时间可分离的常数相对风险规避系数的期望效用的基于消费的资本资产定价模型或标准的基于消费的资本资产定价模型。如果将设定为，那么就是通常所定义的随机贴现因子(SDF)（或跨期边际消费替代率()）。于是，标准的基于消费的资本资产定价模型所导出的随机贴现因子满足于方程(2)或(3)。 3. 具有递归的非期望效用的基于消费的资本资产定价模型在可加的时间可分离的常数相对风险规避系数的期望效用函数假设下，代表性投资者跨期替代弹性系数等于相对风险规避系数的倒数。但Hall (1988) 认为跨期替代弹性系数与相对风险规避系数二者之间这种关系是不适当的。因为跨期替代弹性系数涉及投资者平滑其不同时期消费的意愿，即使不存在不确定性，跨期替代弹性系数也富有一定经济含义，而常数相对风险规避系数关系到投资者平滑自然状态之间消费的意愿，甚至在静态模型中常数相对风险规避系数也富有一定经济含义。Epstein与Zin(1989，1991) 和Weil(1989)提出了比可加的时间可分离的常数相对风险规避系数的期望效用函数更灵活的函数——递归的非期望效用函数（或广义效用函数）。递归的非期望效用函数不仅保留了可加的时间可分离的常数相对风险规避系数的期望效用函数的规模不变性，还打破了跨期替代弹性系数与相对风险规避系数二者之间互为倒数的关系。 Epstein与Zin(1989，1991)以及Weil(1989)将代表性投资者目标函数设定为 (11) 这里，是跨期消费波动厌恶程度的测度，是相对风险规避系数，而且与都是非负的且不为1的常数；；是时间贴现因子。根据式(11)，可导出跨期替代弹性系数。 Epstein与Zin(1989，1991)以及Weil(1989)使用较复杂的动态规划证明了式(11)以及方程(8)隐含着 (12) 这里，可将随机贴现因子设定为，其中是市场组合在时刻的实际总收益。通常，将方程(12)称之为具有递归的非期望效用的基于消费的资本资产定价模型或Epstein-Zin-Weil模型。三、随机贴现因子方差界 1. Hansen-Jagannathan方差界如果将随机贴现因子无条件投影到个风险资产总收益和常数向量所张成的线性空间，那么其最小二乘投影方程为 (13) 其中， (14) 具有零均值，且与总收益正交，即，；是个维列向量；。这意味着。因此，根据投影随机贴现因子的构造，。于是，便有 (15) 不等式(15)表明随机贴现因子方差的下界就是的方差。这就是所谓的Hansen-Jagannathan方差界（Hansen-Jagannathan Variance Bounds），它是无条件信息下随机贴现因子方差界。将方程(14)两边同时减去后，同乘以并取无条件期望，可有 (16) 其中，是风险资产增量收益的协方差阵，并假定是正定的。由于，因此， (17) 由方程(16)与(17)，可解得为 (18) 也就是说，满足于方程(6)的随机贴现因子得到式(18)所给出的投影系数。因此，于是，随机贴现因子满足于下列不等方程： (19) (20) 因此，不等式(19)或(20)就给出了随机贴现因子方差下界，通常将其简称为HJ方差界。 2. 倍增方差界考虑在条件信息下，随机贴现因子方差界问题。假设且具有单位方差阵。现将以克罗内克积（Kronecker Product）作用于方程(5)，并取无条件期望，可获得 (21) 这里，“”是克罗内克积算子（Kronecker Product Operator）。于是，可将随机贴现因子无条件投影到“管理组合”总收益和所张成的线性空间，类似地可获得 (22) (23) 这里，是风险资产总收益用条件信息标度后的“管理组合”总收益的协方差阵，即。一般地，将不等式(22)或(23)称之为倍增方差界（Multiplicative Variance Bounds），它是条件信息下随机贴现因子方差界一种表示形式。四、数据及其描述性统计分析 1. 数据选取及处理由于我国股市自1990年以来，才度过十多个春秋，只有十几年的年度数据。如果使用年度数据，那么样本数据显得过少。为了便于研究，因此本文使用月度数据。又由于在1993年7月之前我国股市还处于不规范的初期发展阶段，当时股市中的股票数量少，上市规模也不大，股市经常处于大起大落的状态，这些不规范数据对于分析整个股市的特征会造成扭曲，因此将检验样本期选取为1993年7月至2003年12月，共126个月。从我国国家统计局网站，获得了我国居民消费价格指数(CPI)月度数据、社会商品零售总额数据（由于没有月度最终消费数据，于是用社会商品零售总额数据代替）。以2000年12月居民消费价格指数(CPI)为100，对居民消费价格指数进行了调整，得到了定基比的CPI数据。将年度总人口数以人口净增长率按照指数增长方式计算得到月度总人口数。将社会商品零售总额经CPI调整后再除以月度总人口数得到人均实际消费或代表性投资者消费。代表性投资者消费增长。从分析家股票软件系统获得还权后的上证综合指数和深圳成分指数月度收盘指数数据。首先将收盘指数经CPI调整，然后取对数，再进行一阶差分，便得到上证综合指数实际收益率和深圳成分指数实际收益率。从中银网获得三个月定期存款利率数据，把它作为相对无风险利率，按几何平均数方法折算月复利利率，并经CPI调整得到实际相对无风险利率。本文以、与的一阶滞后变量、与以及常数变量作为条件信息。 2. 数据描述性统计分析由表1可知，实际相对无风险利率均值在所研究的样本期()是负的。这与我国1993年至1996年通货膨胀率居高不下不无关系。风险资产实际收益及其风险溢价均值都是正的，但数值偏小（例如，月风险溢价均值约为13个基点）。风险资产的波动性与消费增长的波动性差异性不大，而以现有国外数据来看，风险资产的波动性与消费增长的波动性差异性特别大，无法用消费增长的波动性解释风险资产的波动性。这表明我国消费增长的波动性也许能够用来解释风险资产的波动性。作为相对无风险资产，实际相对无风险利率的波动性要比风险资产低得多。风险资产与消费增长协方差基本上是负的，但相对无风险资产与消费增长协方差基本上却是正的。表1 时间序列、、与描述性统计均值 -05 标准误协方差 -05 注：表1中表示两个随机变量的协方差。五、模拟结果 1. 标准的基于消费的资本资产定价模型模拟结果 (1) 不存在市场摩擦情形下随机贴现因子方差界与常数相对风险规避系数图1 不存在市场摩擦情形下随机贴现因子方差界与常数相对风险规避系数注：图1中“”与“”分别表示不存在市场摩擦（）情形下由资产组合所生成的HJ方差界与倍增方差界；“▲”表示当将时间贴现因子设定为时，由不同的常数相对风险规避系数的值（从以速度递增至）所刻画的标准的基于消费的资本资产定价模型所导出的随机贴现因子样本均值与标准差之间关系。由图1可知，从随机贴现因子所对应的模型定价能力角度来看，将时间贴现因子设定为，当常数相对风险规避系数的值在与之间变动时，标准的基于消费的资本资产定价模型无法在条件信息下正确地定价资产组合；但当常数相对风险规避系数的值在与之间变动时，标准的基于消费的资本资产定价模型可以在无条件信息下正确地定价资产组合。经济学上，要求时间贴现因子应小于才是合理可行的。由于标准的基于消费的资本资产定价模型所导出的随机贴现因子，随机贴现因子的均值和标准差分别为，，那么相对于时间贴现因子情形而言，当时间贴现因子减少时，对应的标准的基于消费的资本资产定价模型所导出的随机贴现因子样本均值和标准差点的轨迹或抛物线（图1中三角形符号“▲”）便向左下方移动；当时间贴现因子增加时，则向右上方移动。于是，变动时间贴现因子，图1中曲线未必会落在HJ方差界的上方。因而，上文经验结论未必是成立的。例如，如果将时间贴现因子设定为，那么由不同的常数相对风险规避系数的值（从以速度递增至）所刻画的标准的基于消费的资本资产定价模型所导出的参数化随机贴现因子样本均值和标准差点的轨迹整体向左下方移动，使得曲线落在HJ方差界的下方（如图2所示）；也就是说，当常数相对风险规避系数的值在与之间变动时，标准的基于消费的资本资产定价模型无法在无条件信息下正确地定价资产组合。但原先落在HJ方差界下方的点现在却落在其上方（如图2所示）。因此，在时间贴现因子设定为情形下，当常数相对风险规避系数时，标准的基于消费的资本资产定价模型能够在无条件信息下正确地定价资产组合。当然，时间贴现因子设定得足够地小，小于的常数相对风险规避系数所对应的标准的基于消费的资本资产定价模型所导出的随机贴现因子样本均值和标准差点未必会落在HJ方差界的上方。但只要时间贴现因子满足于经济学上要求，并在合理地范围变动③，一定存在小于的常数相对风险规避系数使其所对应的标准的基于消费的资本资产定价模型所导出的随机贴现因子样本均值和标准差点落在HJ方差界的上方。此外，图1中点落在HJ方差界的下方，要使点对应的常数相对风险规避系数的标准的基于消费的资本资产定价模型在无条件信息下也能够正确地定价资产组合，那么点必须向右上方移动，使得点对应的新坐标点必须落在HJ方差界的上方。此时，时间贴现因子必须大于才能满足这一要求。图2就描绘了当时间贴现因子时，由不同的常数相对风险规避系数的值（从以速度递增至）所刻画的标准的基于消费的资本资产定价模型所导出的参数化随机贴现因子样本均值和标准差点的轨迹或抛物线。在此情形下，由常数相对风险规避系数对应的标准的基于消费的资本资产定价模型所导出的随机贴现因子样本均值和标准差点就落在HJ方差界的上方。而且，还存在更小的常数相对风险规避系数的值（例如，）对应的标准的基于消费的资本资产定价模型所导出的随机贴现因子样本均值和标准差点（例如，点）也落在HJ方差界的上方。因而，就如Kocherlakota(1990)所证明的，在可加的时间可分离的期望效用均衡的增长经济中，存在时间贴现因子大于这一情形。那么，从这个角度来看，间贴现因子小于这一假设可被放宽④。因此，在可加的时间可分离的期望效用函数所隐含的常数相对风险规避系数与跨期替代弹性系数之间关系中，经济学上间贴现因子大于似乎也很合理。这样的话，如果时间贴现因子不同于其真实值，那么它不仅测度了时间偏好，而且还包含了对所选择的跨期替代弹性的补偿。从而，有必要研究递归的非期望效用函数，考察一下常数相对风险规避系数与跨期替代弹性系数分离开情形。这将是本部分第二小部分所要研究的主题。 (2) 存在市场摩擦情形下随机贴现因子方差界与常数相对风险规避系数图2 存在市场摩擦情形下随机贴现因子方差界与常数相对风险规避系数注：图2中“”、“”与“”分别表示当、与时由资产组合所生成的倍增方差界，“”、“”与“”分别表示当、与时由资产组合所生成的HJ方差界（图3、图4与图5中随机贴现因子方差界与此是一样的）；“●”、“▲”与“-”分别表示将时间贴现因子设定为、与时，由不同的常数相对风险规避系数的值（从以速度递增至）所刻画的标准的基于消费的资本资产定价模型所导出的随机贴现因子样本均值与标准差之间关系。图3 倍增方差界与常数相对风险规避系数注：图3中“●”、“▲”、“-”与“■”分别表示当将时间贴现因子设定为、、与时，由不同的常数相对风险规避系数的值（从以速度递增至）所刻画的标准的基于消费的资本资产定价模型所导出的随机贴现因子样本均值与标准差之间关系。上文经验分析隐含的假设是市场上不存在摩擦。然而，事实并不像这样，市场上总是存在这样或那样摩擦（例如，买卖价差、卖空约束、借贷约束以及偿付能力约束等）。由图2可知，相对于不存在市场摩擦（）而言，当市场存在摩擦（）时，其对应的随机贴现因子方差界整体向左上方或左下方移动。如果将时间贴现因子分别设定为与，那么对应的常数相对风险规避系数应取较小的值与（或），使其对应的标准的基于消费的资本资产定价模型所导出的随机贴现因子样本均值和标准差点与点（或点）将落在HJ方差界的上方（如图2所示）。另一方面，当市场存在摩擦（）时，其对应的随机贴现因子方差界整体向右上方或右下方移动，因此，相对于不存在市场摩擦（）而言，当将时间贴现因子设定为、与时，常数相对风险规避系数分别应取较大的值、与，对应的标准的基于消费的资本资产定价模型所导出的随机贴现因子样本均值和标准差点、点与点才能够落在存在市场摩擦（）情形下HJ方差界的上方（如图2所示）。图2与图1一样，标准的基于消费的资本资产定价模型所导出的随机贴现因子样本均值和标准差点的轨迹或抛物线都位于倍增方差界的下方；也就是说，在此情形下，标准的基于消费的资本资产定价模型无法在条件信息下正确定价资产组合。为此，根据随机贴现因子样本均值和标准差点的轨迹或抛物线移动规律，进一步适当地减少时间贴现因子，使得对应的标准的基于消费的资本资产定价模型所导出的随机贴现因子样本均值和标准差点的轨迹或抛物线与倍增方差界相交。在图3中点、点、点与点都位于倍增方差界的上方；也就是说，当市场存在摩擦时，将时间贴现因子设定为（或），存在小于的正常数相对风险规避系数（例如，或(或或)），使得对应的标准的基于消费的资本资产定价模型能够在条件信息下正确地资产组合。相对于不存在市场摩擦（或点与点分别对应的常数相对风险规避系数的值与）而言，这里常数相对风险规避系数的值变大了或变小了。图4 市场摩擦、HJ方差界与常数相对风险规避系数注：图4中“●”、“-” 与“▲”分别表示当跨期边际消费替代弹性系数，将时间贴现因子设定为、与时，由不同的常数相对风险规避系数的值（从以速度递增至）所刻画的Epstein-Zin-Weil模型所导出的随机贴现因子样本均值与标准差之间关系。 2. Epstein-Zin-Weil模型模拟结果 (1) HJ方差界与常数相对风险规避系数由图4可知，当考虑市场存在摩擦时，相对于图1与图2而言，当时间贴现因子、与时，存在更小的小于的常数相对风险规避系数的值（例如，图4中点对应的、点对应的、点对应的、点对应的、点对应的、点对应的与点对应的）对应的Epstein-Zin-Weil模型就能够在无条件信息下正确地定价资产组合。 2. 倍增方差界与常数相对风险规避系数图5 市场摩擦、倍增方差界与常数相对风险规避系数注：图5中“●”、“◆”、“▲”、“－”与“-”分别表示当跨期边际消费替代弹性系数，将时间贴现因子设定为、、、与时，由不同的常数相对风险规避系数的值（从以速度递增至）所刻画的Epstein-Zin-Weil模型所导出的随机贴现因子样本均值与标准差之间关系。由图5可知，当考虑市场存在摩擦时，相对于图3而言，当时间贴现因子与时，存在更小的小于的常数相对风险规避系数的值（例如，点对应的、点对应的、点对应的与点对应的）所对应的具有递归的非期望效用的基于消费的资本资产定价模型能够在条件信息下正确地定价资产组合；而且当时间贴现因子时，也存在小于的常数相对风险规避系数的值（例如，点对应的、点对应的与点对应的）所对应的具有递归的非期望效用的基于消费的资本资产定价模型能够在条件信息下正确地定价资产组合。六、结论本文使用随机贴现因子方差界评价了具有可加的时间可分离的常数相对风险规避系数的期望效用的基于消费的资本资产定价模型与具有递归的非期望效用的基于消费的资本资产定价模型所导出的随机贴现因子参数化模型，并对这两个基于消费的资本资产定价模型（CCAPM）定价能力进行了比较，可获得以下经验结论： 1. 存在合理的相对风险规避系数的值（），使得对应的标准的基于消费的资本资产定价模型和具有递归的非期望效用的基于消费的资本资产定价模型所导出的随机贴现因子参数化模型满足于随机贴现因子方差界要求。与Mehra与Prescott(1985) 发现常数相对风险规避系数的值至少等于、Cochrane与Hansen(1992)发现常数相对风险规避系数的值至少等于以及Meyer(1999)发现常数相对风险规避系数的值至少等于才使得随机贴现因子满足于HJ方差界要求相比，本文此处所获得的经验结论表明常数相对风险规避系数的值似乎合理得多。如果以Mehra与Prescott(1985) 界定的常数相对风险规避系数的估计值不应超过（或者以Hall(1988) 界定的常数相对风险规避系数的估计值不应超过）判断不存在股权溢价之谜为基准，那么本文此处的经验发现表明中国股票市场并不像美国等发达国家股票市场那样存在股权溢价之谜。这和肖俊喜与王庆石(2004)使用广义矩法（GMM）估计标准的基于消费的资本资产定价模型中的参数——相对风险规避系数所获得的经验结论一致。 2. 在具有可加的时间可分离的常数相对风险规避系数的期望效用的基于消费的资本资产定价模型和具有递归的非期望效用的基于消费的资本资产定价模型在相同约束条件下同时能够对资产组合正确定价情形中，前者所对应的常数相对风险规避系数值基本上要比后者所对应的值大。这表明了具有递归的非期望效用的基于消费的资本资产定价模型在证实和解释目前中国股票市场经验上不存在股权溢价之谜方面基本上优于具有可加的时间可分离的常数相对风险规避系数的期望效用的基于消费的资本资产定价模型。 3. 对具有递归的非期望效用的基于消费的资本资产定价模型所导出的随机贴现因子参数化模型而言，当将时间贴现因子分别设定为、与，跨期边际消费替代弹性系数时，满足于倍增方差界要求的常数相对风险规避系数的倒数都小于，这表明了在条件信息下中国股票市场上代表性投资者或消费者对风险规避程度高于跨期消费波动厌恶程度，因而，他们偏好于早期不确定性。但当将时间贴现因子分别设定为、与，跨期边际消费替代弹性系数时，满足于HJ方差界要求的常数相对风险规避系数的倒数可能小于，也有可能大于，这表明了在无条件信息下中国股票市场上代表性投资者或消费者对不确定性的解的偏好是不确定的。参考文献 [1] 肖俊喜与王庆石：《交易成本、基于消费的资产定价与股权溢价之谜——来自中国股市的经验分析》，《管理世界》[J]，2004年第12期。 [2] 李治国与唐国兴：《消费、资产定价与股票溢酬之谜》，《经济科学》[J]，2002年第6期。 [3] B. Meyer (1999): Interteporal Asset Pricing: Evidence from Germany [M], Physica-Verlag Heidelberg. [4] Cochrane, . and Hansen L. P. (1992): Asset Pricing Explorations for Macroeconomics, NBER Macroeconomics Annual 1992 [C], Cambridge, MA: MIT Press, 115-165. [5] Epstein L. G., and S. E. Zin (1989): Substitution, Risk Aversion, and the Temporal Behavior of Consumption Growth and Asset ReturnsⅠ: The Theoretical Framework, Econometrica [J], , 937-969. [6] Epstein L. G., and S. E. Zin (1991): Substitution, Risk Aversion, and the Temporal Behavior of Consumption Growth and Asset Returns: An Empirical Analysis, the Journal of Political Economy [J], , 263-286. [7] Hall, R. (1988): Intertemporal Substitution in Consumption, Journal of Political Economy [J], , 221-273. [8] Hansen L. P. (1982): Large Sample Properties of Generalized Method of Moments Estimators, Econometrica [J], , 1029-1054. [9] Hansen L. P. and Jagannathan R. (1991): Implications of Security Market Data for Models of Dynamic Economies, the Journal of Political Economy [J], , 225-262. [10] John Y. Campbell, Andrew W. Lo and A. Craig Mackinlay (1997): The Econometrics of Financial Markets [M], Princeton University Press. [11] Kocherlakota N. (1990): On the “Discount Factor” in Growth Economies, Journal of Monetary Economics [J], Vol. 25, 43-47. [12] P. Weil (1989): The Equity Premium Puzzle and the Risk-Free Rate Puzzle, Journal of Monetary Economics [J], , 401-421. [13] R. Mehra and E. C. Prescott (1985): The Equity Premium: A Puzzle, Journal of Monetary Economics [J], , 145-161. 作者简介: 肖俊喜，男，1975年12月生，汉族,安徽无为人，东北财经大学数量经济学专业博士生。王庆石，男，1961年2月生，汉族,辽宁辽阳人，东北财经大学国际商学院院长，教授，经济学博士，博士生导师。联系方式: 通信地址：辽宁大连东北财经大学数量经济系，肖俊喜邮编：116025 E-mail：shawchunhy@ 电话：0411-84711076(D)，13889585880(M) 通信地址：辽宁大连东北财经大学国际商学院，王庆石邮编：116025 E-mail：wqingshi@ 电话：0411-84712852(H)，84712988(O)， 13322277222(M) Stochastic Discount Factor Variance Bounds and Equity Premium Puzzle: Empirical Analysis from China’s Stocks Market Junxi Xiao 1 Qingshi Wang 2 (1Department of Quantitative Economics, 2 School of International Business, DongBei University of Finance & Economics, Dalian, 116025) Abstract：The paper simulates and analyzes the standard consumption-based asset pricing model with the time-additive expected utility and the consumption-based asset pricing model with the recursive non-expected utility by utilizing the stochastic discount factor variance bounds in the absence/ present of market frictions and in the un-conditioning/ conditioning information, and finds (1) that unlike the developed capital markets (., .’s capital market), the equity premium puzzle doesn’t exist in China’s stocks market; (2) that the consumption-based asset pricing model with the recursive non-expected utility dominates the standard consumption-based asset pricing model in verifying and explaining no puzzle of the equity premium in China’s stocks market; (3) that the typical investor/ consumer in China’s stocks market prefers the early resolution of uncertainty in the conditioning information, but the resolution of the preference uncertainty is mixed in the un-conditioning information. Keywords: Stochastic Discount Factor Variance Bounds/ Equity Premium Puzzle/ Consumption-Based Capital Asset Pricing Model/ Constant Relative Risk-aversion Coefficient ① 如果股权溢价大得无法用具有可加的时间可分离的常数相对风险规避系数的期望效用的基于消费的资本资产定价模型（或标准的基于消费的资本资产定价模型）进行解释；也就是说，如果用具有可加的时间可分离的常数相对风险规避系数的期望效用的基于消费的资本所预测的股权溢价与真实的历史股权溢价不相匹配（现有的国外文献表明后者比前者要大好几百个基点），那么就称这个现象为“股权溢价之谜（Equity Premium Puzzle）”（Mehra与Prescott，1985）。 ② 一价律（Law of One Price）要求具有同样收益的资产必须按同样的价格进行交易。 ③ 至于时间贴现因子 EMBED 应为多大才为合理，经济学上并未给出具体数值，但起码它不应在违背经济学原理范围内波动。 ④ 当然，时间贴现因子 EMBED 小于 EMBED 这一假设不能被任意放宽。但它不能大得不存在常数相对风险规避系数 EMBED 对应的标准的基于消费的资本资产定价模型所导出的随机贴现因子样本均值和标准差点落在HJ方差界的上方。 PAGE PAGE 1 图表1 1 1 1 UCPUF CPUF UCPF1 CPF1 UCPF2 CPF2 β＝ β＝1 β＝随机贴现因子均值随机贴现因子标准差 Sheet1 UCPUF CPUF UCPF1 CPF1 UCPF2 CPF2 β＝ β＝1 β＝ 1 Sheet1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 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0 0 0 0 0 0 0 0 0 0 0 0 0 0 UCPF1 CPF1 UCP CP UCPF2 CPF2 β＝ β＝ β＝1 β＝ β＝ β＝ β＝随机贴现因子均值随机贴现因子标准差 obs RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR Aug-93 Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 Oct-00 Nov-00 Dec-00 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 Mar-02 Apr-02 May-02 Jun-02 Jul-02 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 obs 1 2 3 4 5 Aug-93 Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 1 1 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 1 1 1 1 1 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 1 1 1 1 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 1 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 Oct-00 Nov-00 Dec-00 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 1 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 Mar-02 Apr-02 May-02 Jun-02 Jul-02 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 mean 1 1 variance 0 0 图表3 1 1 1 UCPF1 UCPUF UCPF2 β＝ β＝1 β＝随机贴现因子均值随机贴现因子标准差 condition IH IZH IF IHHS IZHHS IFHS IHZHS IZHZHS IFZHS IHFS IZHFS IFFS IHCS IZHCS IFCS Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 Oct-00 Nov-00 Dec-00 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 Mar-02 Apr-02 May-02 Jun-02 Jul-02 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 covariance 1 1 1 1 reverse 1 1 13748 -111 1 102 102 -111 1v1 1vr rvr 13, 13, 13, e(m) 1 uncondition r obs RSHH RSHZH RFR RCR Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 Oct-00 Nov-00 Dec-00 1 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 Mar-02 Apr-02 May-02 Jun-02 Jul-02 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 1+r Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 Oct-00 Nov-00 1 Dec-00 1 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 Mar-02 Apr-02 May-02 Jun-02 Jul-02 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 1 1 1 mean 1 1 1 1 covariance 1 reverse 1v1 1vr rvr 8, 8, 8, e(m) condition UCP CP β＝1 1 1 0 1 2 3 Sheet4 obs RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR Aug-93 Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 Oct-00 Nov-00 Dec-00 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 Mar-02 Apr-02 May-02 Jun-02 Jul-02 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh Aug-93 Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 Oct-00 Nov-00 Dec-00 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 Mar-02 Apr-02 May-02 Jun-02 Jul-02 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 1 2 1 2 3 4 5 Aug-93 Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 1 1 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 1 1 1 1 1 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 1 1 1 1 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 1 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 Oct-00 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Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 1 2 3 4 5 Aug-93 1 2 3 4 5 Sep-93 1 2 3 4 5 Oct-93 1 2 3 4 5 Nov-93 1 2 3 4 5 Dec-93 1 2 3 4 5 Jan-94 1 2 3 4 5 Feb-94 1 2 3 4 5 Mar-94 1 2 3 4 5 Apr-94 1 2 3 4 5 May-94 1 2 3 4 5 Jun-94 1 2 3 4 5 Jul-94 1 2 3 4 5 Aug-94 1 2 3 4 5 Sep-94 1 2 3 4 5 Oct-94 1 2 3 4 5 Nov-94 1 2 3 4 5 Dec-94 1 2 3 4 5 Jan-95 1 2 3 4 5 Feb-95 1 2 3 4 5 Mar-95 1 2 3 4 5 Apr-95 1 2 3 4 5 May-95 1 2 3 4 5 Jun-95 1 2 3 4 5 Jul-95 1 2 3 4 5 Aug-95 1 2 3 4 5 Sep-95 1 2 3 4 5 Oct-95 1 2 3 4 5 Nov-95 1 2 3 4 5 Dec-95 1 2 3 4 5 Jan-96 1 2 3 4 5 Feb-96 1 2 3 4 5 Mar-96 1 2 3 4 5 Apr-96 1 2 3 4 5 May-96 1 2 3 4 5 Jun-96 1 2 3 4 5 Jul-96 1 2 3 4 5 Aug-96 1 2 3 4 5 Sep-96 1 2 3 4 5 Oct-96 1 2 3 4 5 Nov-96 1 2 3 4 5 Dec-96 1 2 3 4 5 Jan-97 1 2 3 4 5 Feb-97 1 2 3 4 5 Mar-97 1 2 3 4 5 Apr-97 1 2 3 4 5 May-97 1 2 3 4 5 Jun-97 1 2 3 4 5 Jul-97 1 2 3 4 5 Aug-97 1 2 3 4 5 Sep-97 1 2 3 4 5 Oct-97 1 2 3 4 5 Nov-97 1 2 3 4 5 Dec-97 1 2 3 4 5 Jan-98 1 2 3 4 5 Feb-98 1 2 3 4 5 Mar-98 1 2 3 4 5 Apr-98 1 2 3 4 5 May-98 1 2 3 4 5 Jun-98 1 2 3 4 5 Jul-98 1 2 3 4 5 Aug-98 1 2 3 4 5 Sep-98 1 2 3 4 5 Oct-98 1 2 3 4 5 Nov-98 1 2 3 4 5 Dec-98 1 2 3 4 5 Jan-99 1 2 3 4 5 Feb-99 1 2 3 4 5 Mar-99 1 2 3 4 5 Apr-99 1 2 3 4 5 May-99 1 2 3 4 5 Jun-99 1 2 3 4 5 Jul-99 1 2 3 4 5 Aug-99 1 2 3 4 5 Sep-99 1 2 3 4 5 Oct-99 1 2 3 4 5 Nov-99 1 2 3 4 5 Dec-99 1 2 3 4 5 Jan-00 1 2 3 4 5 Feb-00 1 2 3 4 5 Mar-00 1 2 3 4 5 Apr-00 1 2 3 4 5 May-00 1 2 3 4 5 Jun-00 1 2 3 4 5 Jul-00 1 2 3 4 5 Aug-00 1 2 3 4 5 Sep-00 1 2 3 4 5 Oct-00 1 2 3 4 5 Nov-00 1 2 3 4 5 Dec-00 1 2 3 4 5 Jan-01 1 2 3 4 5 Feb-01 1 2 3 4 5 Mar-01 1 2 3 4 5 Apr-01 1 2 3 4 5 May-01 1 2 3 4 5 Jun-01 1 2 3 4 5 Jul-01 1 2 3 4 5 Aug-01 1 2 3 4 5 Sep-01 1 2 3 4 5 Oct-01 1 2 3 4 5 Nov-01 1 2 3 4 5 Dec-01 1 2 3 4 5 Jan-02 1 2 3 4 5 Feb-02 1 2 3 4 5 Mar-02 1 2 3 4 5 Apr-02 1 2 3 4 5 May-02 1 2 3 4 5 Jun-02 1 2 3 4 5 Jul-02 1 2 3 4 5 Aug-02 1 2 3 4 5 Sep-02 1 2 3 4 5 Oct-02 1 2 3 4 5 Nov-02 1 2 3 4 5 Dec-02 1 2 3 4 5 Jan-03 1 2 3 4 5 Feb-03 1 2 3 4 5 Mar-03 1 2 3 4 5 Apr-03 1 2 3 4 5 May-03 1 2 3 4 5 Jun-03 1 2 3 4 5 Jul-03 1 2 3 4 5 Aug-03 1 2 3 4 5 Sep-03 1 2 3 4 5 Oct-03 1 2 3 4 5 Nov-03 1 2 3 4 5 Dec-03 1 2 3 4 5 β 1 m Aug-93 Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 1 Mar-95 Apr-95 May-95 Jun-95 Jul-95 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 1 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 1 1 1 Aug-98 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 1 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 1 Sep-00 Oct-00 1 1 Nov-00 Dec-00 1 Jan-01 Feb-01 Mar-01 Apr-01 1 May-01 1 Jun-01 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 1 Mar-02 Apr-02 May-02 Jun-02 Jul-02 1 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 1 1 1 1 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 mean std 图表2 1 1 1 1 1 CPF1 CPUF CPF2 β＝ β＝ β＝ β＝ β＝1 随机贴现因子均值随机贴现因子标准差 condition IH IZH IF IHHS IZHHS IFHS IHZHS IZHZHS IFZHS IHFS IZHFS IFFS IHCS IZHCS IFCS Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 Oct-00 Nov-00 Dec-00 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 Mar-02 Apr-02 May-02 Jun-02 Jul-02 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 covariance 1 1 1 1 reverse 1 1 13748 -111 1 102 102 -111 1v1 1vr rvr 13, 13, 13, e(m) 1 uncondition r obs RSHH RSHZH RFR RCR Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 Oct-00 Nov-00 Dec-00 1 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 Mar-02 Apr-02 May-02 Jun-02 Jul-02 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 1+r Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 Oct-00 Nov-00 1 Dec-00 1 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 Mar-02 Apr-02 May-02 Jun-02 Jul-02 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 1 1 1 mean 1 1 1 1 covariance 1 reverse 1v1 1vr rvr 8, 8, 8, e(m) condition UCP CP β＝1 1 1 0 1 2 3 Sheet4 obs RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR Aug-93 Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 Oct-00 Nov-00 Dec-00 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 Mar-02 Apr-02 May-02 Jun-02 Jul-02 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh Aug-93 Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 Oct-00 Nov-00 Dec-00 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 Mar-02 Apr-02 May-02 Jun-02 Jul-02 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 1 2 1 2 3 4 5 Aug-93 Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 1 1 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 1 1 1 1 1 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 1 1 1 1 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 1 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 Oct-00 Nov-00 Dec-00 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 1 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 Mar-02 Apr-02 May-02 Jun-02 Jul-02 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 mean 1 1 variance 0 0 Sheet7 2 UCPF1 UCPUF UCPF2 β＝ β＝1 β＝ β＝ 1 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 Sheet7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 UCPF1 UCPUF UCPF2 β＝ β＝1 β＝ β＝随机贴现因子均值随机贴现因子标准差 Sheet6 2 CPF1 CPUF CPF2 β＝ β＝ β＝ β＝ β＝1 β＝ β＝ 1 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 Sheet6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 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0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 UCP CP β＝ β＝ β＝ β＝ β＝1 β＝ β＝随机贴现因子均值随机贴现因子标准差 Sheet3 obs RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR RCR Aug-93 Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 Oct-00 Nov-00 Dec-00 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 Mar-02 Apr-02 May-02 Jun-02 Jul-02 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh rshh Aug-93 Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 Sep-00 Oct-00 Nov-00 Dec-00 Jan-01 Feb-01 Mar-01 Apr-01 May-01 Jun-01 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 Mar-02 Apr-02 May-02 Jun-02 Jul-02 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 1 2 3 4 5 Aug-93 1 2 3 4 5 Sep-93 1 2 3 4 5 Oct-93 1 2 3 4 5 Nov-93 1 2 3 4 5 Dec-93 1 2 3 4 5 Jan-94 1 2 3 4 5 Feb-94 1 2 3 4 5 Mar-94 1 2 3 4 5 Apr-94 1 2 3 4 5 May-94 1 2 3 4 5 Jun-94 1 2 3 4 5 Jul-94 1 2 3 4 5 Aug-94 1 2 3 4 5 Sep-94 1 2 3 4 5 Oct-94 1 2 3 4 5 Nov-94 1 2 3 4 5 Dec-94 1 2 3 4 5 Jan-95 1 2 3 4 5 Feb-95 1 2 3 4 5 Mar-95 1 2 3 4 5 Apr-95 1 2 3 4 5 May-95 1 2 3 4 5 Jun-95 1 2 3 4 5 Jul-95 1 2 3 4 5 Aug-95 1 2 3 4 5 Sep-95 1 2 3 4 5 Oct-95 1 2 3 4 5 Nov-95 1 2 3 4 5 Dec-95 1 2 3 4 5 Jan-96 1 2 3 4 5 Feb-96 1 2 3 4 5 Mar-96 1 2 3 4 5 Apr-96 1 2 3 4 5 May-96 1 2 3 4 5 Jun-96 1 2 3 4 5 Jul-96 1 2 3 4 5 Aug-96 1 2 3 4 5 Sep-96 1 2 3 4 5 Oct-96 1 2 3 4 5 Nov-96 1 2 3 4 5 Dec-96 1 2 3 4 5 Jan-97 1 2 3 4 5 Feb-97 1 2 3 4 5 Mar-97 1 2 3 4 5 Apr-97 1 2 3 4 5 May-97 1 2 3 4 5 Jun-97 1 2 3 4 5 Jul-97 1 2 3 4 5 Aug-97 1 2 3 4 5 Sep-97 1 2 3 4 5 Oct-97 1 2 3 4 5 Nov-97 1 2 3 4 5 Dec-97 1 2 3 4 5 Jan-98 1 2 3 4 5 Feb-98 1 2 3 4 5 Mar-98 1 2 3 4 5 Apr-98 1 2 3 4 5 May-98 1 2 3 4 5 Jun-98 1 2 3 4 5 Jul-98 1 2 3 4 5 Aug-98 1 2 3 4 5 Sep-98 1 2 3 4 5 Oct-98 1 2 3 4 5 Nov-98 1 2 3 4 5 Dec-98 1 2 3 4 5 Jan-99 1 2 3 4 5 Feb-99 1 2 3 4 5 Mar-99 1 2 3 4 5 Apr-99 1 2 3 4 5 May-99 1 2 3 4 5 Jun-99 1 2 3 4 5 Jul-99 1 2 3 4 5 Aug-99 1 2 3 4 5 Sep-99 1 2 3 4 5 Oct-99 1 2 3 4 5 Nov-99 1 2 3 4 5 Dec-99 1 2 3 4 5 Jan-00 1 2 3 4 5 Feb-00 1 2 3 4 5 Mar-00 1 2 3 4 5 Apr-00 1 2 3 4 5 May-00 1 2 3 4 5 Jun-00 1 2 3 4 5 Jul-00 1 2 3 4 5 Aug-00 1 2 3 4 5 Sep-00 1 2 3 4 5 Oct-00 1 2 3 4 5 Nov-00 1 2 3 4 5 Dec-00 1 2 3 4 5 Jan-01 1 2 3 4 5 Feb-01 1 2 3 4 5 Mar-01 1 2 3 4 5 Apr-01 1 2 3 4 5 May-01 1 2 3 4 5 Jun-01 1 2 3 4 5 Jul-01 1 2 3 4 5 Aug-01 1 2 3 4 5 Sep-01 1 2 3 4 5 Oct-01 1 2 3 4 5 Nov-01 1 2 3 4 5 Dec-01 1 2 3 4 5 Jan-02 1 2 3 4 5 Feb-02 1 2 3 4 5 Mar-02 1 2 3 4 5 Apr-02 1 2 3 4 5 May-02 1 2 3 4 5 Jun-02 1 2 3 4 5 Jul-02 1 2 3 4 5 Aug-02 1 2 3 4 5 Sep-02 1 2 3 4 5 Oct-02 1 2 3 4 5 Nov-02 1 2 3 4 5 Dec-02 1 2 3 4 5 Jan-03 1 2 3 4 5 Feb-03 1 2 3 4 5 Mar-03 1 2 3 4 5 Apr-03 1 2 3 4 5 May-03 1 2 3 4 5 Jun-03 1 2 3 4 5 Jul-03 1 2 3 4 5 Aug-03 1 2 3 4 5 Sep-03 1 2 3 4 5 Oct-03 1 2 3 4 5 Nov-03 1 2 3 4 5 Dec-03 1 2 3 4 5 β 1 m Aug-93 Sep-93 Oct-93 Nov-93 Dec-93 Jan-94 Feb-94 Mar-94 Apr-94 May-94 Jun-94 Jul-94 Aug-94 Sep-94 Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 1 Mar-95 Apr-95 May-95 Jun-95 Jul-95 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 1 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 1 1 1 Aug-98 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99 Jul-99 Aug-99 1 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00 May-00 Jun-00 Jul-00 Aug-00 1 Sep-00 Oct-00 1 1 Nov-00 Dec-00 1 Jan-01 Feb-01 Mar-01 Apr-01 1 May-01 1 Jun-01 Jul-01 Aug-01 Sep-01 Oct-01 Nov-01 Dec-01 Jan-02 Feb-02 1 Mar-02 Apr-02 May-02 Jun-02 Jul-02 1 Aug-02 Sep-02 Oct-02 Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 1 1 1 1 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 mean std 图表1 1 UCP CP β＝1 随机贴现因子均值随机贴现因子标准差 Sheet1 UCP CP β＝1 1 Sheet1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 UCP CP β＝1 随机贴现因子均值随机贴现因子标准差 Sheet2 Sheet3

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随机贴现因子方差界与股权溢价之谜——来自中国股市的经验分析.doc

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