Extended Dividend,Cash Flow,and Residual Income Valuation Models: Accounting for Deviations from Ideal Conditions*

Previous empirical studies derive the standard equity valuation models (i.e., DDM, RIM, and DCF model) while assuming that ideal conditions, such as infinite payoffs and clean surplus accounting, exist. Because these conditions are rarely met, we extend the standard models by following the fundamental principle of financial statement articulation. We then empirically test the extended models by employing two sets of forecasts: (1) the analyst forecasts provided by Value Line, and (2) the forecasts generated by cross‐sectional regression models. The main result is that our extended models yield considerably smaller valuation errors. Moreover, by constructing these models, we obtain identical value estimates across the extended models. By reestablishing empirical equivalence under nonideal conditions, our approach provides a benchmark that enables us to quantify the errors caused by individual deviations from ideal conditions and thus to analyze the robustness of the standard models. Finally, by providing a level playing field for the different valuation models, our findings have implications for other empirical approaches, for example, estimating the implied cost of capital.     

An Analysis of Historical and Future-Oriented Information in Accounting-Based Security Valuation Models*

The Ohlson (1995) and Feltham and Ohlson (1995) valuation model provides a rigorous framework for summarizing the information in expected future earnings and book values. However, the model provides little guidance on selecting an empirical proxy for expected future earnings. We examine whether and under what circumstances historical earnings and analyst earnings forecasts offer comparable explanation of security prices. This issue is of particular interest because analyst forecasts are less readily available than historical data. Under appropriate circumstances, historical data may allow wider use of the Feltham-Ohlson valuation model by researchers and investors. A related issue is the incremental explanatory power of historical earnings and realized future earnings (perfect-foresight forecasts) for security prices beyond analyst forecasts. If historical earnings are incrementally informative, that would suggest that analyst forecasts do not fully reflect price-relevant information in past earnings. If future earnings are incrementally informative, that would suggest that security prices reflect investors' implicit earnings forecasts beyond analyst forecasts. We examine these issues using a historical model (based on past earnings), a perfect-foresight model (based on realized future earnings), and a forecast model (based on Value Line earnings forecasts). All three models provide significant explanatory power for security prices, and each set of earnings data provides incremental explanatory power for prices when used with the other sets of earnings data. We estimate the models separately for firms with moderate and extreme earnings-to-price (E/P) ratios, a proxy for earnings permanence. For moderate-E/P firms, the historical model's explanatory power exceeds that of the perfect foresight model, and is indistinguishable from that of the analyst forecast model. In contrast, for extreme-E/P firms, the perfect-foresight model offers greater explanatory power than the historical model, but lower explanatory power than analyst forecasts. Our results suggest that financial analysts' forecasting efforts are best focused on firms whose earnings contain large temporary components (extreme E/P firms). However, in general, both historical data and analyst forecasts are complementary information sources for security valuation.     

Some Further Evidence on Exchange-Rate Volatility and Exports

The relationship between exchange-rate volatility and aggregate export volumes is examined using a model that includes real export earnings of oil-exporting economies as a determinant of export volumes of a sample of 12 industrial countries. Four fixed-coefficient panel-data estimation techniques, including a generalized method of moments (GMM) and random coefficient (RC) estimation, are employed on panel data covering the estimation period 1977:1–2003:4 using three measures of exchange-rate volatility. Our aim is to provide a theoretically and empirically justifiable specification that can guide researchers. In contrast to recent studies employing panel data, we find little evidence that volatility has a negative and significant impact on trade. We use second-generation RC estimation, which corrects for biases arising from incorrect functional forms, omitted variables, and measurement errors. Our results suggest that the finding of a significant and negative impact of volatility is attributable to specification biases. JEL no. C23, F3, F31     

Nonprice rivalry among health insurers and coverage of new technologies

This paper develops a multiple-period theoretical model of health maintenance organization (HMO) coverage of medical procedures as a function of HMO competition and a market's predisposition toward managed care. Previous empirical results regarding one laser procedure were not predicted by a single-period model. The new model predicts that more favorable predisposition toward managed care is positively associated with coverage of procedures for which coverage is discretionary. The empirical analysis in this paper focuses on 13 additional laser procedures. The new empirical findings are different from the previous findings and are more consistent with the hypotheses generated by the new theoretical model.The data were obtained under a grant from the Office of Technology Assessment (HMO Laser Procedure Coverage) and the University of Michigan Rackham Pre-doctoral Fellowship (InterStudy). The authors would like to thank an anonymous reviewer and participants at a session sponsored by the International Atlantic Economic Society at the 1998 Allied Social Science Association meetings, Chicago, IL, for their helpful comments. Any remaining errors belong to the authors.     

Forecasts for international financial series with VMD algorithms

Recent models with variational mode decomposition (VMD) have been applied to time-series forecasting. In this paper, we build a hybrid model named VMD–autoregressive integrated moving average (ARIMA)–Taylor expansion forecasting (TEF) to increase accuracy and stability for predicting financial time series. We use VMD algorithms to decompose financial series into subseries. An ARIMA model is built to predict each mode’s linear component, and the pragmatic TEF model based on a tracking differentiator is applied to forecast of the nonlinear component. Then the forecasts of all subseries are assembled as a final forecast. Our empirical results of international stock indices demonstrate that the proposed hybrid approach surpasses several existing state-of-the-art hybrid models.     

Horizon‐Dependent Underreaction in Financial Analysts' Earnings Forecasts*

This paper provides empirical evidence that underreaction in financial analysts' earnings forecasts increases with the forecast horizon, and offers a rational economic explanation for this result. The empirical portion of the paper evaluates analysts' responses to earnings‐surprise and other earnings‐related information. Our empirical evidence suggests that analysts' earnings forecasts underreact to both types of information, and the underreaction increases with the forecast horizon. The paper also develops a theoretical model that explains this horizon‐dependent analyst underreaction as a rational response to an asymmetric loss function. The model assumes that, for a given level of inaccuracy, analysts' reputations suffer more (less) when subsequent information causes a revision in investor expectations in the opposite (same) direction as the analyst's prior earnings‐forecast revision. Given this asymmetric loss function, underreaction increases with the risk of subsequent disconfirming information and with the disproportionate cost associated with revision reversal. Assuming that market frictions prevent prices from immediately unraveling these analyst underreac‐tion tactics, investors buying (selling) stock on the basis of analysts' positive (negative) earnings‐forecast revisions also benefit from analyst underreaction. Therefore, the asymmetric cost of forecast inaccuracy could arise from rational investor incentives consistent with a preference for analyst underreaction. Our incentives‐based explanation for underreaction provides an alternative to psychology‐based explanations and suggests avenues for further research.     

Out-of-Sample Forecasts and Nonlinear Model Selection with an Example of the Term Structure of Interest Rates

It is well known that goodness-of-fit measures lead to overfitting. We compare the small-sample properties of linear and several nonlinear models using a Monte Carlo study. A large number of linear series are generated and conventional methods of fitting nonlinear models are applied to each. The best linear and nonlinear models are compared using in-sample and out-of-sample criteria. Out-of-sample forecasts are shown to be superior for selecting the proper specification. The experiment is repeated using a nonlinear model and the in-sample lit and forecasts of the various models are compared. An example is provided using the term structure of interest rates.     

Price and Volume Reactions to Public Information Releases: An Experimental Approach Incorporating Traders' Subjective Beliefs*

This paper examines how market prices, volume, and traders' dividend expectations respond to public information releases in laboratory markets for a long-lived financial asset. The objective is to study deviations from the symmetric information risk-neutral rational expectations (RE) benchmark, which predicts no trade in such settings. The results of a series of double-auction and call markets are reported in which traders manage a portfolio of cash and asset shares over 15 rounds of trading. A public signal regarding the value of the liquidating dividend is released every third round, and traders' subjective expectations of the liquidating dividend are elicited each round as cash-motivated forecasts. We find that, despite the public dividend signal, traders' dividend forecasts are heterogeneous. Forecasts and prices both underreact to the public signals, with prices under-reacting more than forecasts. In general, price changes are not closely associated with public signals, and there is greater excess price volatility in double auctions than in call markets. Forty-three percent of trades are inconsistent with the trader's forecasts, and inconsistent trades occur more frequently in the double-auction markets. On average, approximately 10 percent of the outstanding shares are traded in each round, and trading volume is increasing in the mean absolute forecast revision and decreasing in the contemporaneous dispersion in forecasts. These results suggest that differential processing of the public signal and/or speculative trading for short-term gain may help to explain why symmetric information RE predictions are often not supported in empirical and experimental settings. They also suggest that market reactions to public information releases may be influenced by market microstructure.     

Equity Valuation Employing the Ideal versus Ad Hoc Terminal Value Expressions*

Recently, Penman and Sougiannis (1998) and Francis, Olsson, and Oswald (2000) compared the bias and accuracy of the discounted cash flow model (DCF) and Edwards‐Bell‐Ohlson residual income model (RIM) in explaining the relation between value estimates and observed stock prices. Both studies report that, with non‐price‐based terminal values, RIM outperforms DCF. Our first research objective is to explore the question whether, over a five‐year valuation horizon, DCF and RIM are empirically equivalent when Penman's (1997) theoretically “ideal” terminal value expressions are employed in each model. Using Value Line terminal stock price forecasts at the horizon to proxy for such values, we find empirical support for the prediction of equivalence between these valuation models. Thus, the apparent superiority of RIM does not hold in a level playing field comparison. Our second research objective is to demonstrate that, within each class of the DCF and RIM valuation models, the model that employs Value Line forecasted price in the terminal value expression generates the lowest prediction errors, compared with models that employ non‐price‐based terminal values under arbitrary growth assumptions. The results indicate that, for both DCF and RIM, price‐based valuation models outperform the corresponding non‐price‐based models by a wide margin. These results imply that researchers should exercise care in interpreting findings from models using ad hoc terminal value expressions.     

An Examination of the Statistical Significance and Economic Relevance of Profitability and Earnings Forecasts from Models and Analysts

In this paper, we propose and empirically test a cross‐sectional profitability forecasting model which incorporates two major improvements relative to extant models. First, in terms of model construction, we incorporate mean reversion through the use of a two‐stage partial adjustment model and inclusion of a number of additional relevant determinants of profitability. Second, in terms of model estimation, we employ least absolute deviation (LAD) analysis instead of ordinary least squares because the former approach is able to better accommodate outliers. Results reveal that forecasts from our model are more accurate than three extant models at every forecast horizon considered and more accurate than consensus analyst forecasts at forecast horizons of two through five years. Further analysis reveals that LAD estimation provides the greatest incremental accuracy improvement followed by the inclusion of income subcomponents as predictor variables, and implementation of the two‐stage partial adjustment model. In terms of economic relevance, we find that forecasts from our model are informative about future returns, incremental to forecasts from other models, analysts’ forecasts, and standard risk factors. Overall, our results are important because they document the increased accuracy and economic relevance of a cross‐sectional profitability forecasting model which incorporates improvements to extant models in terms of model construction and estimation.     

Country fund discounts and the mexican crisis of December 1994: Did local residents turn pessimistic before international investors?

It has been suggested that Mexican investors were the “front-runners” in the peso crisis of December 1994, turning pessimistic before international investors. Different expectations about their own economy, perhaps due to asymmetric information, prompted Mexican investors to be the first ones to leave the country. This paper investigates whether data from three Mexican country funds provide evidence that supports the “divergent expectations” hypothesis. We find that, right before the devaluation, Mexican fund Net Asset Values (mainly driven by Mexican investors) dropped first and/or faster than Mexican country fund prices (mainly driven by foreign investors). Moreover, we find that Mexican NAVs tend to Granger-cause the country fund prices. This suggests that causality, in some sense, flows from the Mexico City investor community to the Wall Street investor community.     

Capital controls and international trade finance in a dual exchange rate regime: The Belgian experience post-mortem

Capital Controls and International Trade Finance in a Dual Exchange Rate Regime: The Belgian Experience Post-Mortem. — The purpose of the paper is to model “leads and lags” capital flows on the official segment of a dual exchange market and to examine the effects of various types of capital controls imposed by authorities on the official spot and forward exchange markets. The focus of the analysis is the degree of insulation provided by a “dual exchange market cum capital controls” in face of a speculative crisis. The crucial variables in this respect are the deviation from covered interest parity and the forward risk premium. Results of the theoretical model are confronted with empirical evidence over the 1975–85 period.     

A BVAR MODEL FOR THE SOUTH AFRICAN ECONOMY

The paper develops a Bayesian vector autoregressive (BVAR) model of the South African economy for the period of 1970:1‐2000:4 and forecasts GDP, consumption, investment, short‐term and long term interest rates, and the CPI. We find that a tight prior produces relatively more accurate forecasts than a loose one. The out‐of‐sample‐forecast accuracy resulting from the BVAR model is compared with the same generated from the univariate and unrestricted VAR models. The BVAR model is found to produce the most accurate out of sample forecasts. The same is also capable of correctly predicting the direction of change in the chosen macroeconomic indicators.     

Forecasting French and German long-term rates using a rational expectations model

Forecasting French and German Long-Term Rates Using a Rational Expectations Model. — In this paper, the authors study a forecasting model for long-term rates based on the expectations hypothesis of the term structure. The long-term rate is expressed as an average of expected short-term rates, which are modelled using three models: two univariate models (with stationary and nonstationary rates) and one model in which the short-term rate terminal boundary is specified as a function of agents’ expectations. These approaches are used to forecast French and German long-term rates from 1960 to 1996. The authors find that the model based on agents’ expectations gives the best forecasts, especially for short horizons.     

International monetary arrangements in the Asia-Pacific before and after

This paper assesses the characteristics and policy implications of the international monetary arrangements in the Asia-Pacific pre- and post-July 1997. It first examines the literature on speculative attacks on fixed and managed exchange rate regimes. Since these speculative attacks are more likely to be successful when financial markets are well integrated, it then assesses the degree of financial market integration in the region. Furthermore, as the empirical evidence also suggests a possible role for real exchange rate overvaluation, we examine the evidence regarding misalignment. Using a purchasing power parity (PPP) criterion and a criterion based on a Balassa-Samuelson model, we find mixed evidence of exchange rate overvaluation. Given that our ability to determine the equilibrium real exchange rate is so limited, we caution against a return to a fixed or highly managed exchange rate regime. Finally, we assess how monetary policy and exchange rate policy have interacted over the pre- and post-crisis periods, using a monetary model of exchange rates. JEL classification: F31; F33; F34     

An analysis of RSQE forecasts: 1971–1992

The purpose of this paper is to evaluate the accuracy of ex ante econometric model forecasts of four key macroeconomic variables: real GNP growth, the rate of price inflation measured by the GNP deflator, the civilian unemployment rate, and the Treasury Bill rate. Annual forecasts produced by the Research Seminar in Quantitative Economics (RSQE) based on the Michigan Quarterly Econometric Model of the U.S. Economy are compared with quasi ex ante forecasts from a four-variable vector autoregressive (VAR) model. Statistical tests of the equality of forecast error variances as well as univariate and multivariate forecast encompassing-type tests are conducted. The forecast error variance comparisons indicate that for three of the four variables the RSQE forecasts are more accurate than the VAR forecasts and for one of the variables (real GNP growth) only slightly less accurate. The forecast encompassing-type tests indicate that the RSQE forecasts contain information not contained in the VAR forecasts and, conversely, that VAR forecasts contain information not included in the RSQE forecasts. The scope for improving RSQE forecasts by combining them with VAR forecasts is rather limited, however.     

Economic models of speculative attacks and the drachma crisis of May 1994

Speculative attacks on fixed or ‘fixed but adjustable’ exchange rate regimes seem to have become a standard feature of the landscape of foreign exchange markets. The supposed excesses of seemingly untethered financial markets have been documented for some time, but only recently have the concerted attacks by speculators on exchange-rate regimes begun to occupy the popular imagination.Economic models of this phenomenon, however, have been around for some time, and are useful in characterizing the real-world speculative attacks that have occurred in the last 10–15 years in a number of countries. In this paper, we provide a brief overview of one such model. We also sketch some implications of that model for the speculative attack on the Greek drachma in May 1994.     

Evaluating CPB’s Forecasts

This paper analyzes forecasts, for ten key annually observed economic variables for the Netherlands, created by the Netherlands Bureau for Economic Policy Analysis (CPB) for 1971–2007. These CPB forecasts are all manually modified model forecasts, where the model is a (very) large multi-equation macro model. The CPB forecasts are held against real-time forecasts obtained from simple autoregressive time series models, and for seven of the ten cases, CPB’s forecasts are significantly more accurate. Combining CPB’s forecasts with the real time autoregressive forecasts shows that four of the ten combined forecasts are significantly better than CPB’s forecasts, and seven of the ten are better than the time series forecasts. This suggests that CPB’s manual adjustment efforts could perhaps be directed to modifying simple model forecasts and not the forecasts from the own large macro model.     

Trade policy in Mexico

This paper provides an evaluation of the trade policies applied in Mexico in the last quarter century (1956–1982). It examines the policies in three well-defined periods: (1) 1956–1971, considered to be a period of relative stability following the rapid inflation and devaluations of the first post-war decade, though characterized by increasing overvaluation of the peso; (2) March 1972–December 1976, beginning with the acceleration of government spending under President Echeverria and ending with the devaluations of the peso; (3) December 1976–December 1982, covering the Presidency of José López Portillo. For each period, the author discusses macroeconomic policy, trade policy developments and changes in Mexican exports and imports and their contribution to industrial growth. Having demonstrated the interdependence of macroeconomic and trade policies, the paper concludes with recommendations for policy reform, e.g. for remedying macroeconomic disequilibria, reducing price distortions and reforming trade policy, with a view to moving towards an outward-oriented development strategy in Mexico.     

Occupation-specific human capital and local labour markets

Most skills acquired through on-the-job training may be specificto an occupation and therefore transferable to some but notall firms. This paper explores the relationship between thesize of the local market for an occupation-specific skill andjob-training outcomes. The Stevens (1994) model of trainingpredicts that as market size increases, job turnover increasesand training becomes more general. I test these predictionsusing data on blue-collar workers and variation in market sizeacross US metropolitan areas. The empirical results supportthe theoretical predictions and the impacts are most relevantat low levels of market size.