Dividend Forecasts Research Articles

How Important are Earnings Announcements as an Information Source?

In a competitive information market, a single information source can only dominate other sources individually, not collectively. We explore whether earnings announcements constitute such a dominant source using Ball and Shivakumar’s (2008) R2 metric: the proportion of the variation in annual returns explained by the four quarterly earnings announcement returns. We find that the earnings announcement days’ R2 is 11 percent — higher than the corresponding R2 of days with dividend announcements, management forecasts, preannouncements, 10-K and 10-Q filings, and their amendments, and comparable to that of the four days with largest realized absolute return in a year. Additional analysis reveals that earnings announcements convey extreme bad news as often as management forecasts and preannouncements; for any other type of news earnings announcements are much more frequent. We conclude that earnings announcements are an important source of new information in the equity market.

Essay in dividend modelling and forecasting: does nonlinearity help?

This article develops a method of nonlinear modelling for the dividends of the Group of seven (G7) indexes using threshold techniques: Smooth Transition Autoregressive Models (STAR). First, smoothness and nonlinearity are justified by the presence of heterogeneous expectations and companies of different sizes. Then, we show that this methodology is adapted to reproduce persistence in the dividend adjustment dynamics. Finally, we highlight the superiority of STAR models compared to the linear process in modelling dividends and reducing measurement error while forecasting future dividends. STAR forecasting supplanted those of linear model in the short and medium terms.

A knowledge integration model for the prediction of corporate dividends

Dividend is one of essential factors determining the value of a firm. According to the valuation theory in finance, discounted cash flow (DCF) is the most popular and widely used method for the valuation of any asset. Since future dividends play a key role in the pricing of a current firm value by DCF, it is natural that the accurate prediction of future dividends should be most important work in the valuation. Although the dividend forecasting is of importance in the real world for the purpose of investment and financing decision, it is not easy for us to find good theoretical models which can predict future dividends accurately except Marsh and Merton [Marsh, T. A., & Merton, R. C. (1987). Dividend behavior for the aggregate stock market. Journal of Business, 60 (1), 1–40.] model. Thus, if we can develop a better method than Marsh and Merton (1987) in the prediction of future dividends, it can contribute significantly to the improvement of the pricing model of a firm value. Therefore, the most important goal of this study is to develop a better model by applying artificial intelligence techniques than Marsh and Merton (1987). The effectiveness of our approach was verified by the experiments comparing with Marsh and Merton model, Neural Networks, and CART approaches.

Modeling and Forecasting a Firm's Financial Statements with a VAR-VECM Model

This paper details efforts at developing and estimating a Vector Autoregressive (VAR) econometric model representative of the financial statements of a firm. Although the model can be generalized to represent the financial statements of any firm, this work was carried out as a case study, where the chosen company is the largest firm in Brazil: Petrobras S/A. The methodology utilized makes use of correlation analysis, unit root tests, cointegration analysis, VAR modeling, Granger causality tests, in addition to impulse response and variance decomposition methods. Besides the endogenous financial statement variables, an exogenous variable vector was utilized, namely, Brazilian GDP, domestic and foreign interest rates, the international oil price, the exchange rate, and the country risk. The final version of the model is a Vector Error Correction Model (VECM), which takes into account the cointegrating relationships among the endogenous variables. After estimation and validation, the model is used to produce forecasts of the financial statements of the firm under study. Estimates for the exogenous variables and dividend forecasts were also used to estimate the firm's market value. The results are apparently robust and the authors expect they might contribute to the field of financial planning and forecasting.

Private Information and Asset Pricing: Financial Experiments - In Case the Aggregation of Information Does Not Provide the Unique Dividend Forecast

In this paper, we analyzed how market determines prices when private information is present. When there is private information in a market, an investor deduces what private information other investors may have from the market price. Private information in the market can be aggregated through such investor actions. When the aggregation of private information gives the unique forecast for the future dividend (defined as complete private information market), the transaction prices in the market converge to fully revealed rational expectation equilibrium price. If the aggregation of private information in the market cannot eliminate uncertainties, and does not provide the unique forecast (incomplete private information market), an investor may believe in wrong forecast, so the market may systematically provide mispricing. The bubble or the phenomenon such as crashes observed in actual markets may have occurred as a result of such investor actions.

Analysis of IPO Dividend Forecasts for Australian LPTs

While dividend forecasts in the prospectuses of initial public offerings (IPOs) are common, Brown et al. (2000) have found them to be optimistically biased. This study investigates the dividend/distribution forecasts in the prospectuses of Australian LPT IPOs during the period 1994 to 2004 and finds on average that they are not optimistically biased. Because dividends have important cash flow implications for investors, this study also examines factors that might influence the magnitude of the errors between the forecast and the actual distributions. It finds that LPT IPOs that offer stapled securities have overestimated their distribution paying ability.

The accuracy of analysts' dividend forecasts around the world

We examine the link between the accuracy of consensus analysts' dividend forecasts, earnings predictability and dividend policies of firms in 39 countries from 1995 to 2004. For firms that display stronger dividend smoothing, as modeled by Lintner [Lintner, J., 1956. Distribution of incomes of corporations among dividends, retained earnings and taxes. American Economic Review 46, 97–113], there is a lower correlation between dividend and earnings forecast errors, with less of the earnings uncertainty being passed into dividend uncertainty. The link between earnings and dividend forecast errors is weaker in common-law, capital market-based countries and in countries with well-developed financial (debt and equity) markets, where firm managers have greater incentives to smooth dividends and to use dividends for signaling.

Analysts' Dividend Forecasts, Portfolio Selection, and Market Risk Premia

The most relevant practical impediment to an application of the Markowitz portfolio selection approach is the problem of estimating return moments, in particular return expectations. We analyze the consequences of using return estimates implied by analysts' dividend forecasts under the explicit notion of taxes and non-flat term structures of interest rates and achieve quite good performance results. As a by-product, these results cast some doubt upon the adequacy of estimating market risk premia with implied returns, because estimation techniques with good performance results are hardly suited to describe market expectations.

Dividend forecasts and dividend payments of initial public offerings – when zero means zero and no comment most likely also means zero

Managers often try to forecast dividends because as Brown et al. (2002) suggest, dividends have cash flow implications for investors and are important signalling devices. This study analyses the dividend forecasts in the prospectuses of initial public offerings (IPOs) in Australia over the period 1994 to 1999. While many companies forecast dividends, many make no dividend forecast at all and some forecast no (or zero) dividends for the forthcoming year. This paper seeks to determine if no forecast at all should present a different signal to investors than a zero dividend forecast. It is found that those that do not forecast a dividend, by and large, do not pay a dividend. It is also found that those that forecast a zero dividend, true to their forecast, pay no dividend.

Expected returns and expected dividend growth

We investigate a consumption-based present-value relation that is a function of future dividend growth and find that changing forecasts of dividend growth are an important feature of the post-war U.S. stock market, despite the failure of the dividend–price ratio to uncover such variation. In addition, dividend forecasts are found to covary with changing forecasts of excess stock returns over business cycle frequencies. This covariation is important because positively correlated fluctuations in expected dividend growth and expected returns have offsetting effects on the log dividend–price ratio. The market risk premium and expected dividend growth thus vary considerably more than is apparent using the log divided–price ratio alone as a predictive variable.

Promise More, Leave Less: The Importance of Dividend Forecasts in Initial Public Offerings

Following Kim and Ritter (1999) who find that earnings forecasts provide more accurate valuations of IPOs, this paper analyses whether the owners of companies seeking to list will leave less money on the table if positive dividend per share (DPS) yield forecasts are made in the prospectus. Our findings indicate that DPS yield forecasts by directors of Industrial company IPOs have been an important ingredient in the amount of money left on the table. A similar result is found for Limited Liability IPOs and those that do not offer options to subscribers to buy more shares. The offer of an operational dividend reinvestment plan in the prospectus does not appear significant in reducing the amount of money left on the table.

Analysts' Dividend Forecasts and Dividend Signaling

This study complements existing research on the information content of dividends by focusing on the use of dividend expectations. We derive a measure of unexpected dividend changes, called dividend surprises, based on Value Line forecasts. Our results highlight a potentially serious sample misclassification arising from the extensively used naive dividend change method. Classifications of unexpected changes in dividends using dividend surprises result in stock price reactions and earnings changes that are consistent with the implications of dividend signaling models. Also, the approach followed in this paper permits the analysis of a significantly forgotten sample in previous event studies: Firms announcing no dividend changes in which investors (analysts) are expecting a change. We find that no change in dividends often reflects a negative dividend surprise and is indeed associated with negative stock price reaction and negative earnings changes. We provide evidence that the failure to find a relationship between dividend changes and future earning changes may be due to measurement error arising from misclassification of dividend changes. One implication of this study for future research is that empirical tests of dividend signaling models should incorporate dividend forecasts.

Analysts' dividend forecasts

Dividends have direct cash flow implications for firms and investors, and are important for signaling reasons. Consequently, investors, analysts, and managers typically forecast future dividends and report them in various ways. We examine the accuracy of consensus dividend forecasts of Australian sell-side financial analysts published by BARCEP between 1985 and 1998. Although analysts' dividend forecasts are optimistically biased, we find they are less biased and more accurate than their earnings counterparts. Forecast accuracy is positively correlated with proxies for the amount of information available about the firm, and negatively correlated with proxies for the level of uncertainty about its future operating performance. These proxy variables and other variables that control for institutional change, notably occasioned by amendments to the Australian Corporations Law, explain 10–15% of the cross-sectional variation in the accuracy of analysts' dividend forecasts over the period 1991–1998, which is about half the explanatory power of a similar model fitted to BARCEP consensus earnings forecasts.

Analysts' Dividend Forecasts

Analysts' Dividend Forecasts

Expected Returns and Expected Dividend Growth

We develop a consumption-based present value relation that is a function of future dividend growth. Using data on aggregate consumption and measures of the dividend payments from aggregate wealth, we show that changing forecasts of dividend growth make an important contribution to fluctuations in the U.S. stock market, despite the failure of the dividend-price ratio to uncover such variation. In addition, these dividend forecasts are found to covary with changing forecasts of excess stock returns. The variation in expected dividend growth we uncover is positively correlated with variation in expected returns, and the results suggest that a substantial fraction of the variation in expected dividend growth is common to variation in expected excess returns. Movements in expected dividend growth that are entirely common to movements in expected returns have no effect on the log dividend-price ratio. An implication of these findings is that the log dividend-price ratio will have difficulty predicting both dividend growth and excess returns at business cycle frequencies. Such a failure of predictive power is not an indication that risk-premia are constant, however. On the contrary, the results presented here imply that the log dividend-price ratio will have difficulty revealing business cycle variation in both the equity risk-premium and expected dividend growth precisely because expected returns fluctuate at those frequencies, and covary with changing forecasts of dividend growth. The findings imply that both the market risk-premium and expected dividend growth vary considerably more than what can be revealed using the log dividend-price ratio alone as a predictive variable.

The Impact of Forecast Disclosure and Accuracy on Equity Pricing: The IPO Perspective

In a relatively less litigious environment like Australia, it is common to find IPO firms that voluntarily provide forecasts in their prospectus. Using 158 Australian industrial IPOs listed from 1991 to 1997, we examine the impact of the disclosure and accuracy of earnings and dividend forecasts on equity pricing. Our results show that IPO firms' disclosure policy is not related to their initial and long-run valuation. However, the market appears to price managers' ability to forecast: firms with inaccurate earnings and dividend forecasts, especially those that fall short of their forecasts, experience adverse price reactions surrounding the day when the actual figures are released. Our results also show a significant relationship between forecast errors and IPO firms' postlisting performance. Further analysis shows that this relationship is driven mainly by the announcement effect.

The Impact of Forecast Disclosure and Accuracy on Equity Pricing: An IPO Perspective

In a relatively less litigious environment like Australia, it is common to find IPO firms that voluntarily provide forecasts in their prospectus. Using 158 Australian industrial IPOs listed from 1991 to 1997, we examine the impact of the disclosure and accuracy of earnings and dividend forecasts on equity pricing. Our results show that IPO firms' disclosure policy is not related to their initial and long-run valuation. However, the market appears to price managers' ability to forecast: firms with inaccurate earnings and dividend forecasts, especially those that fall short of their forecasts, experience adverse price reactions surrounding the day when the actual figures are released. Our results also show a significant relationship between forecast errors and IPO firms' post-listing performance. Further analysis shows that this relationship is driven mainly by the announcement effect.

Equity Valuation Models and Measuring Goodwill Impairment

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter LinkedIn Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation AAA Financial Accounting Standards Committee; Equity Valuation Models and Measuring Goodwill Impairment. Accounting Horizons 1 June 2001; 15 (2): 161–170. doi: https://doi.org/10.2308/acch.2001.15.2.161 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu nav search search input Search input auto suggest Search

The accuracy of management dividend forecasts in Australia

Dividends have direct cash flow consequences for investors and are important for signalling reasons. Consequently, investors, analysts and managers typically forecast future dividends and report them in various ways. Yet the accuracy of dividend forecasts has been largely neglected in empirical finance. We examine the accuracy of managers' dividend forecasts in Australian IPO prospectuses (a companion paper examines the analysts' dividend forecasts). Managers' dividend forecasts are optimistically biased. Nevertheless, they are substantially more accurate and less biased than their earnings counterparts. Differences in retained ownership and the predictability of earnings help explain why some dividend forecasts are more accurate than others.

Dividend Forecast Biases in Index Option Valuation

Since the early days of option pricing theory,the assumption that the dividends on the underlying stock or index over the life of the contract are known has not been challenged. We examine the sensitivity of index option prices to the assumption of dividend uncertainty. We consider a number of issues related to the forecasting of dividends and build a dividend forecasting model that passes several rigorous tests for unbiasedness. We then generate option prices using contemporary market levels and interest rates. We find that prices generated with the actual dividends are unbiased with respect to those generated using the forecasted dividends. The magnitudes of the forecast errors, however, are sufficiently large to suggest a concern, but the percentage errors are consistently small, typically amounting to less than two percent of the option price. We conclude that the convenient assumption that the stream of future dividendsis known is probably innocuous.