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道琼斯指数的内在价值是什么.doc

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道琼斯指数的内在价值是什么? What is the Intrinsic Value of the Dow? 摘要 We model the time-series relation between price and intrinsic value as a cointegrated system, so that price and value are long-term convergent. In this frame-work, we compare the performance of alternative estimates of intrinsic value for the Dow 30 stocks. During 1963–1996, traditional market multiples have little predictive power. However, a V0P ratio, where V is based on a residual income valuation model, has statistically reliable predictive. Further analysis shows time-varying interest rates and analyst forecasts are important to the success of V. Alternative forecast horizons and risk premia are less important. 我们在价格和内在价值之间建立了时间序列模型作为一个协整的系统,以便使价格和内在价值处于一个长期收敛的状态。在此框架内,我们比较了30支道琼斯股票内在价值的替代估计表现。从1963-1996年,传统市场乘数几乎没有预测能力。(例如B/P,E/P,D/P比率)然而, V/P这个公式在统计学上有可靠的预测能力,其中V 是基于剩余收益估价模型。进一步的分析显示,时变利率以及分析师的预测对于V的预测成功非常重要。预测界限的改变以及风险溢价并不是很重要。 MOST FINANCIAL ECONOMISTS AGREE that a stock’s intrinsic value is the present value of its expected future dividends (or cash f lows) to common shareholders, based on currently available information. However, few academic studies have focused on the practical problem of measuring intrinsic value.1 Perhaps the scant attention paid to this important topic reflects the standard academic view that a security’s price is the best available estimate of intrinsic value. Consequently, many researchers regard fundamental analysis, the study of public financial information to arrive at an independent measure of in- trinsic value, as a futile exercise. 大多数经济学家认为基于当前可用的信息,对于普通股股东,股票的内在价值是其预期未来股息 (或现金流量) 的现值。然而,有一些学术研究侧重于测量内在价值的实用问题。也许对这个重要的主题的不太重视反映了标准的学术观点,债券价格是内在价值的最佳可用估计值。因此,许多研究者认为研究公共财务信息以达成一项独立措施本身内在价值的基本面分析徒劳无功。 The case for the equality of price and value is based on an assumption of insignificant arbitrage costs.2 When information and trading costs are trivial, stock prices should be bid and offered to the point where they fully reflect intrinsic values. However, when intrinsic values are difficult to measure and0or when trading costs are significant, the process by which price adjusts to intrinsic value requires time, and price does not always perfectly reflect intrinsic value. In such a world, a more realistic depiction of the relation between price and value is one of continuous convergence rather than static equality.3 价格和价值平等的情况是基于忽略套利成本的假设。当信息和交易费用都可以忽略时,股票价格应该达到充分反映内在价值的点。然而,当内在值很难衡量和 (或) 时交易成本非常巨大,价格调整到内在价值的过程需要的时间,而且价格并不总是完全反映内在价值。在这样一种情况下,对价格与价值之间更逼真的描绘是一种连续的趋同关系,而非静态的相等。 Once we admit the possibility that price may diverge from value, the measurement of intrinsic value becomes paramount. Aside from an emerging set of studies in the accounting literature which we discuss later, few academic studies to date have directly addressed the many practical problems associated with implementing a comprehensive valuation model. Nor has much attention been paid to the appropriate empirical benchmarks! for assessing alternative empirical value estimates when price itself is a noisy measure of intrinsic value. 一旦我们承认这个价格偏离价值的可能性,内在价值的测量变得至关重要。除了我们稍后将会讨论的一系列会计新兴的研究,到目前为止的一些学术研究探讨了建立全面的估价模型相关联的很多实际性问题。人们也开始大量关注当价格本身是嘈杂的内在价值衡量基准时,用适当的实证评估替代经验值估计。 In this study, we empirically evaluate several alternative measures for the intrinsic value of the 30 stocks in the Dow Jones Industrial Average ~DJIA!. As a departure from the current literature, we do not require price to equal intrinsic value at all times.4 Instead, we model the time-series relation between price and value as a cointegrated system, so that price and value are long-term convergent.5 In this framework, we compare alternative empirical estimates of intrinsic value using two criteria: ~i! their relative ability to track price variation in the DJIA over time, and ~ii! their ability to predict market returns. We show that, under reasonable assumptions, superior empirical estimates of intrinsic value can perform better on either, or even both, dimensions. 在该研究中,我们根据经验评估几个替代措施在道琼斯工业平均指数的 30 只股票的内在价值。因为和当前的文献相背离,我们不要求在任何时候价格都等于价值。相反,我们将价格和价值之间的时间序列关系模型化为一个协整的系统,以便使价格和价值都长期收敛。在此框架内,我们比较内在价值的替代性实证估计时使用了两个条件:(1)他们能够随着时间的变化追踪道琼斯工业指数的价格变化;(2)他们可以预测市场的回应我们可以看到,在合理的假设下,优越的内在价值的实证估计可以更好地表现其中一种或两种规模。 The ability to predict market returns is important in tactical asset allocation decisions, in which portfolio weights across broad asset classes are determined on the basis of their relative value. The ability to track price variations over time is also important, because it captures the responsiveness of the valuation model to economic forces that affect prices of publicly traded stocks. Valuation models with superior tracking ability can be ap- plied with greater confidence to nontraded stocks—for example, in valuing initial public offerings, or mergers and acquisitions. 预测市场的回报能力对资产配置策略的决定非常重要,在这种资产配置策略中,各类资产组合的权重由他们的的相对价值决定。随着时间的推移跟踪价格变化的能力也很重要,因为它捕捉到在估值模型中影响公开交易股票价格的经济力量。具有优越的跟踪能力的估价模型可以更有信心地应用于非交易性的股票 ——例如,用于首次公开发行或并购获得的股票估值。 道琼斯指数的内在价值是什么? This study is related to two streams of literature in accounting and finance. First, our work extends prior studies in finance that examine the relation between market multiples such as the book-to-market ratio ~B0P! or the dividend yield ~D0P! and subsequent market returns ~e.g., Rozeff ~1984!,Fama and French ~1988a, 1989!, Campbell and Shiller ~1988!, Hodrick ~1992!, MacBeth and Emanuel ~1993!, and Kothari and Shanken ~1997!!. These studies evaluate the predictability of market returns using simple valuation heuristics, and they focus on return forecasting rather than valuation issues. The evidence suggests that these simple valuation heuristics may not hold in recent years. For example, the price-to-book ratio ~P0B! for the Dow stocks increased from an average of approximately 1.0 in 1979 to more than 3.2 by June 1996. The dividend yield on the Dow stocks has decreased from more than 6 percent to less than 2 percent over the same time period. Whether these trends are due to structural changes ~such as lower interest rates, decreased dividend payouts, or growth expectations!, or are indicative of market mispricings, is difficult to determine without a more complete valuation model. 这项研究涉及到会计和财务两个方面的文献首先,我们的工作延伸到检验市场倍数之间的关系等财务方面之前的研究,例如,市场比率(B/P)或者股息收益率 (D/P) 和随后的市场回报。(eg.)这些研究用简单的估价方法评估市场回报的可预见性,而且他们将精力集中在对回报预测而不是估价问题。有证据表明这些简单的估价方法近些年来可能不再适用。例如,本书中的道琼斯股票价格比率(P/B),从1979 年 到1996 年 6 月由平均约 1.0 增至超过 3.2 。而在相同时间段内,道琼斯股票的股息收益率从 6%以下降至不足 2%。不管这些趋势是由于结构性的更改,如较低的利率、 股利支付的减少或期望的增加,还是表明了市场定价的不准确。如果没有一个更完整的估值模型,都很难去确定。 We use a richer valuation model to address this question. Our results show that time-varying interest rates are an essential part of valuation models in time-series applications. In the post-1963 period, traditional market ratios that omit time-varying interest rates ~such as B0P, D0P,and E0P ratios! do not predict U.S. market returns. However, during the same time period, a V0P ratio, in which “V” is estimated using a residual income formula, has reliable predictive power for U.S. market returns. Using a vector- autoregressive ~VAR! simulation technique, we show that this result is robust to the inclusion of many factors in the regression, including B0P, D0P, and E0P, as well as the short-term interest rate, the ex ante default risk premium, the ex ante term structure risk premium, and past market returns. 我们将用一个更加丰富的估值模型来解决这一问题。我们的研究结果显示,利率随着时间的变化是估价模型在时间系列应用过程中的重要组成部分。从1963年之后,忽略利率时间变化的传统比率 (如 B/P、 D/P 和 E/P 比率) 不能预测市场回报。然而,在同一时间期间,V/P 比率,其中"V"的估计使用剩余收益公式,对美国市场的回报有可靠的预测。我们使用矢量-自回归 (VAR) 模拟技术,发现这个包含许多因素的回归结果是强健的,包括 B/P、 D/P 和 E/P,以及短期利率,许多因素列入 ex 安特默认风险溢价,事后安特一词结构风险溢价与过去的市场回报。 Our study is also related to a recent line of research in the accounting literature that explores the empirical properties of the residual-income formula. The valuation equation we implement in this paper is similar to models appearing in recent studies by Abarbanell and Bernard ~1995!, Frankel and Lee ~1997, 1998!, Penman and Sougiannis ~1997!, and Dechow, Hutton, and Sloan ~1997!. However, these empirical studies examine the ability of the model to explain cross-sectional prices and0or expected returns, whereasour investigation focuses on the time-series relation between value and price. 我们的研究还与最近一系列实证性研究剩余收入公式属性的会计文献相关联。我们在本文中实施的估价方程类似于出现在一些最近的研究中的模型,像 Abarbanell 和伯纳德 (1995 年) ,弗兰克尔和李 (1997 年、 1998年),Penman 和 Sougiannis (1997 年),和 Dechow、 赫顿和斯隆 (1997 年)。然而,这些实证研究检验了这些模型解释横断面价格和(或)预期的回报的可能性,而我们的调查重点是价值与价格之间的时间关系序列模型。 We provide evidence on the sensitivity of this valuation model to various key input parameters for time-series applications. Specifically, we document the effect of altering the forecast horizon ~3 years to 18 years!, the choice of earnings forecasting method ~a historical time-series model versus a model based on analyst consensus forecasts!, the choice of risk premia ~a market-wide time-varying risk premium, a Fama–French one-factor industry risk premium, or a Fama–French three-factor industry risk premium!, and the choice of the riskless rate ~short-term T-bill yield versus the long-term Treasury bond yield!. 我们对此估价模型对各种关键的输入参数的时间系列应用敏感性进行了证实。具体来说,我们记录了改变预测时间范围 (3 岁到 18 岁)、 盈利预测方法 (与基于分析师的共识预测模型的历史时间序列模型) 的选择、 风险溢价 (全球性时变风险溢价、 Fama–French 单因子行业风险溢价或 Fama–French 三因素行业风险溢价)的选择 和无风险率 (短期国库券收益与长期国债收益率)选择造成的的影响。 Our results show that the inclusion of a time-varying discount rate component is essential to the success of V. Intrinsic value estimates that do not include time-varying discount rates have little predictive power for returns. The choice of the riskless rate is also important. Specifically, value estimates based on short-term T-bill rates outperform value estimates based on long-term Treasury bond rates. Once time-varying interest rates have been incorporated into the estimation process, the addition of analyst forecasts further improves the performance of the value estimate. Specifically, we find that using I0B0E0S consensus forecasts rather than forecasts based on a time-series model enhances both the tracking ability of V and the predictive power of the V0P ratio. In contrast, the choice of alternative forecast horizons and risk premia has little effect on our results. 我们的研究结果显示将随着时间变化的折扣率组件列入,对"V"价值重要。内在价值的估计不认为包含随时间变化的折扣率对回报有预测能力。无风险利率的选择也很重要。具体而言,基于短期国库券利率的价值估计性能优于值估计基于长期国债利率。一旦时变利率被纳入估算过程,分析师的预测进一步增加提高了价值估计的性能。具体而言,我们发现使用 I/B/E/S 共识预测而不是基于时间序列模型的预测,提高了"V"的跟踪能力和 V/P 比率的预测能力。相比之下,选择改变预测的界限和风险溢价对我们的结果几乎没有影响。 Finally, our findings suggest a framework for reconciling the valuation literature in accounting and the returns prediction literature in finance. Traditionally, the accounting literature has emphasized the importance of fundamental value measures that track contemporaneous returns ~and prices!, and the finance literature has emphasized the ability of these fundamentalmeasures to predict future returns. We suggest that when price is a noisy proxy for intrinsic value, it is reasonable to expect better value measures to perform better on both dimensions. 最后,我们的研究结果显示出一个调和会计文献中的股价和财务中预测回报率文献的框架。传统上,会计文献强调了追踪同期回报 (和价格)的基本估价价值措施的重要性而财物文献则强调了这些基本的措施能够预测未来的收益能力。我们认为当价格是内在价值的干扰变量时,可以合理地期望更好的价值措施在两个维度上更好地执行。 The remainder of the paper is organized as follows. In Section I, we discuss the cointegration of price and value. Section II introduces the residual- income valuation model. Section III describes the data and research methodology. Section IV compares the various value proxies in terms of their ability to track the level of the Dow index over time. Section V compares the predictive ability of V0P to other market value indicators. Finally, Section VI concludes with a discussion of the implications of our analysis for the valuation literature and for the market efficiency debate. 本文的其余部分组织如下。在第一节,我们讨论的价格和价值的整合。第二节介绍了剩余收益估价模型。第三节描述的数据和研究方法。第四节将随着时间的推移各种变量跟踪道琼斯指数的水平的能力进行比较。第五节比较 V/P模型 对其他市场价值指标的预测能力。最后,第六节包含了我们对估价文献分析方面和市场效率的一些讨论。 I. Convergence of Price and Value I. 收敛的价格和价值 A stock’s intrinsic value is typically defined as the present value of itsexpected future dividends based on all currently available information. Notationally, 一只股票的内在价值通常被定义为基于当前可用的所有信息及其预期未来股息的现值 In this definition, Vt* is the stock’s intrinsic value at time t, Et ~Dt i ! is the expected future dividends for period t i conditional on information available at time t, and re is the cost of equity capital based on the information set at time t. This definition assumes a f lat term-structure of discount rates. 在这个公式中,是在t时间股票的内在价值,是在时间t时可用的信息基础上对未来t+i 期间的股利期望,是基于 t 时间信息的股权资本的成本。这一定义假定平期限结构的折扣率。(This definition assumes a flat term-structure of discount rates.这句不太会翻译,怕给大家造成误解)。尽管不可观测,但是经济学家普遍认为在经验研究中一个公司的股票价格是的最好替代变量。确实,很对财务和会计方面的研究都是基于价格等于未来股利的现值这一假设进行的,即=。根据这一假设,价格中的所有更改都代表未来股息或折现率,市场期望对未来股息或折现率的修改。 大前提是,股票价格相当于预期的未来的股息现值,即Pt 恒等于V*。在这种假设下,所有的价格变动表示对未来姑息或折扣率的市场预期的修正。在市场价格代表修正对未来的预期股息或折扣利率。 在这项研究中我们考虑另一个框架,在这个框架中价格可以偏离内在价值。这些可能发生的偏差要么因为噪声交易(如,希勒(1984 )和德龙等(1990))或因为在一个嘈杂的理性预期设置的不知情的交易(王( 1993 ))。偏差的程度和持续性依赖于套利成本(广义的定义包括信息采集和处理成本,以及交易和持有成本)。从长远来看,套利力量使价格趋向于价值。然而,在短期内,套利的成本可能足够大,可以防止这种趋同瞬间的发生。 这框架的一个含义为Pt仅仅是v *的一个估计,它可以与其他经验估计的V*作比较。为了解释,让 Log(Pt)=log(Vt*)+єt, (2a). Log(Vt)=log(Vt*)+ωt, (2b). 这些方程表达一个在时间t的价格Pt和在时间t的内在价值Vt*之间的关系,并且是我们指定为Vt的内在价值的经验估计。具体来说,Pt的对数用定价误差来测量Vt*的对数。同样,Vt是一个内在价值看得见的估计,Vt对数用测量误差ωt来测量Vt*的指数。 在这个框架内,可替代的V测量的相对精度反映误差项的时间序列属性。理想情况下,如果V测量V*没有误差,对于所有的t ,ωt等于零。这个想象的缺陷是,优越的V测量是有ωt项,并有第一第二时间和快速均值回归。换句话说,我们想构建一个V计量,测量的误差尽可能小。具体来说,我们就像误差ωt项为零,一个较低的标准差,和快速均值回归(即,每当ωt从均值偏离时,我们希望它快速恢复)。 6 噪声交易者的情况下价格偏离价值,是因为一些交易员遵循“伪信号”(与价值相关的新闻的信号,是现象,而不是物质的)。伪信号的例子包括华尔街的建议“专家”和技术和锦上添花的策略,不考虑内在价值。在某种程度上,不知情交易者使系统估计错误,价格还可以偏离价值,在一个噪声的理性预期框架(王(1993))。 7 在处理比率我们使用对数转换来简化阐述。注意,Log(Pt)和log( Vt)可能不稳定,但如果一个这两个变量的线性组合是回归均值,然后协整它们。 因为ωt是不能直接观测的,我们必须通过经验结构的时间序列特质,对不同V测量的相对精度进行推导,比如V/P。考虑到(2a)与(2b)之间的不同: Log(Vt/Pt)=ωt-єt, (3) 这个方程表示Log(Vt/Pt)作为两个误差项的差距。误差єt的时间序列属性是由市场(套利)压力来决定的,而不在我们的控制中。然而,假如P是V*的无偏估计,则єt应该意味着零。例如,єt可能根据一个AR(1),AR(2),或者更一般的ARMA过程。假如我们增加假设为ωt和єt并不是完全相关,然后我们可以用V/P比值来估计可替代的V的测量。 这个研究表明我们可以用这两个维度来估计V*的可替代的经验估计: 1. 跟踪能力:更好的内在价值估计超额的V/P比值,它有低标准差和快速均值回归。根据给定的єt,一个更好的内在价值V,因为V/P能导致低标准差。然后,当ωt从均值偏离时,我们想让它快速回到均值。ωt 和єt之间有特定的关系结构,在ωt范围内快速均值回归表明在V/P范围内快速均值回归。 2. 预测能力:更好的内在价值估计超过的V/P比值,它对未来回报有更强的预测能力。在我们的框架中,假如价格很好地测量内在价值,换句话说假如对于所有的t 时间єt=0 ,,则任何均值回归在V/P中是完全是因为ωt 。除非ωt 代理时变预期收益,V0P对随后的回报没有预测能力。注意,如果ωt 是一个时变的预期收益的代理,即使所有t时єt,=0,ωt 仍然可以预测未来回报率。它不可能完全排除这种可能性。然而,在后续的测试中,我们包含控制变量,这个变量代理时变的预期收益,包括短期利率,预期项风险,事前违约风险,和滞后市场回报。 8 如果ωt和єt是完全相关的,然后Vt会完全的追踪Pt。根据经验,没有我们的价值估计符合这样的描述。 9 要知道V/P均值回归本身就足以证明V是速度内在价值的一个更准确的估计。如果ωt和єt是高度相关的,则ωt和єt都是慢慢回归均值,但它们之间的区别是迅速均值回归。这种可能性不能被排除在外。然而,如果快速均值回归V/P完全是由于Vωt和єt之间的关系,V/P将没有能力预测未来的回报。 假设єt有时可以被非零,一个更好的V估计产生一个V/P计量,是єt的更清晰的代理等。因此,更好的V估计与更大的预测能力的回报产生V/P比率。具体来说,当价格相对于价值高(低),我们希望更低(更高)的后续回报。在极端情况下当V充分测量V *,所有均值回归到V/P是由于єt。 在后面的测试中,我们使用这些两个标准比较可供选择的V *经验代理。 II。剩余收益估值模型 我们估值模型用来计算一个V *的代理是基于一个贴现剩余收益方法,有时也称为Edwards-Bell-Ohlson (EBO)估值方程。独立派生的这个估值模型会定期出现在1930年代以来会计学,金融学,经济学文献中。用最近进行实证的方法实施模型在几个文章中
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