Properties of Market Expectations of Accounting Earnings by Financial Analysts: UK versus US

This paper compares patterns and properties of financial analysts' forecasts (FAFs) of earnings between the UK and the US. Using 299 UK and 400 US firms from the same data source—Institutional Brokers Estimate System tapes—the accuracy of forecasts is examined and the sources of errors analysed. The results reveal that FAFs errors in the UK are much smaller than those in the US, and that this disparity persists even after controlling for firm size and industry effects. Further, FAFs of US firms demonstrate consistent overestimation of earnings over the sample period 1988–1990, while UK firms show overestimation in only one of three years. A model developed to test the determinants of forecast error reveals that forecasters of UK firms are influenced in a somewhat different fashion from those of US firms. While dispersion, predisclosure information (market capitalisation or number of analysts), and industry are common determinants of forecast error for both countries, the percentage of forecasts revised is a major determinant only for UK firms.     

Assessing the accuracy and dispersion of real estate investment forecasts

Existing empirical evidence has frequently observed that professional forecasters are conservative and display herding behaviour. Whilst a large number of papers have considered equities as well as macroeconomic series, few have considered the accuracy of forecasts in alternative asset classes such as real estate. We consider the accuracy of forecasts for the UK commercial real estate market over the period 1999–2011. The results illustrate that forecasters display a tendency to under-estimate growth rates during strong market conditions and over-estimate when the market is performing poorly. This conservatism not only results in smoothed estimates but also implies that forecasters display herding behaviour. There is also a marked difference in the relative accuracy of capital and total returns versus rental figures. Whilst rental growth forecasts are relatively accurate, considerable inaccuracy is observed with respect to capital value and total returns.     

A social forecast revisited

In 1971, the authors produced a 30-year forecast of leisure in the UK. In 2001 they obtained survey data for comparison with the forecasts. The paper presents the original forecasts and describes the methods used to produce them, assesses their accuracy in the light of the survey data, and concludes with some reflections on the underlying forecasting methodology and on changes in leisure patterns.     

An Analysis of Brokers' and Analysts' Unpublished Forecasts of UK Stock Returns

This paper describes an empirical study of over 4000 specific share return forecasts made by 35 UK stockbrokers and by the internal analysts of a large UK investment institution. A comparison of forecast and realised returns reveals a small but potentially useful degree of forecasting ability. A large part of the information content of the forecasts, however, appears to be discounted in the market place within the first month. Nevertheless, an analysis of some 3000 transactions motivated by, and executed at the time of, the forecasts shows that the apparent predictive ability of the recommendations could be translated into superior performance by the fund's investment managers. Differences in forecasting ability between brokers do not appear to persist over time, but predictive accuracy can be improved by pooling simultaneous forecasts from different sources.     

Forecasting the PSBR Outside Government: The IFS Perspective

Expectations regarding the future state of the public finances are vital for public policy formation. The UK experience has been that forecast of the PSBR have been beset with problems since the mid-1980s. Independent assessments of the accuracy and plausibility of public finance forecasts are an important check on government forecasts and serve to increase public debate over government finance issues. We examine the success of various possible methods available to those outside government. JEL classification: E6, H1, H6.     

THE ASSOCIATION BETWEEN ANALYSTS’ FORECAST REVISIONS AND EARNINGS COMPONENTS: THE EVIDENCE OF FRS 3

This study examines whether the earnings components as required by FRS 3 help UK analysts to predict firms’ earnings changes by investigating the statistical association between analysts’ forecast revisions and firms’ unexpected earnings components. I find that analysts’ forecast revisions made in different time horizons are consistently associated with unexpected earnings components as required by FRS 3. UK analysts are able to incorporate current-year unexpected earnings components into their current and future earnings forecasts even before firms officially release this information. However, empirical results also show that current-year unexpected earnings components are not fully incorporated into analysts’ forecasts of future earnings. Analysts appear to wait for more information releases regarding firms’ future earnings and delay their revisions of future earnings forecasts. This is consistent with the evidence that the cumulative revisions of current earnings forecasts are generally associated with prior-year unexpected earnings components, and the association appears to be stronger as time progresses. Overall, this study provides evidence suggesting that the earnings components as required by FRS 3 help UK analysts to identify firms’ permanent and transitory earnings changes over different forecast horizons. This study also provides strong evidence supporting the informativeness of earnings components for analysts’ forecasts and the information set perspective of FRS 3 that highlights the importance of earnings components in predicting a reporting entity’s future performance.     

Nonlinearity in the stock price–dividend relation

We provide empirical evidence of nonlinearities in the present value (PV) model of stock prices. We test for nonlinearity both in the contemporaneous and in the dynamic stock price–dividend relation for the UK, the US, Japan, and Germany. We employed three nonlinear nonparametric techniques, namely nonlinear cointegration, locally-weighted regression, and nonlinear Granger causality tests. Whilst there is no evidence of linear cointegration and Granger causality for any country, there is significant evidence of nonlinear cointegration and nonlinear Granger causality for all four countries. Furthermore, out-of-sample forecasts obtained from the locally-weighted regression are more accurate than out-of-sample forecasts obtained from the linear model for the UK, the US, and Japan. These results are robust to sub-period analysis. The results are in line with empirical evidence that expected stock returns are time-varying.     

Long-Term Earnings Forecasts in the Electric Utility Industry: Accuracy and Valuation Implications

This paper integrates research on the accuracy of alternative long-term earnings forecasts, the gain in accuracy achievable from combining various forecasts, and the power of different long-term earnings forecasts to explain stock prices. The tests are performed on 82 electric utility firms because of the relative homogeneity of accounting data in that industry and because of the importance of the findings for the determination of the cost of capital in a regulatory proceeding. The results are consistent with earlier research findings that analyst forecasts of long-term earnings growth are more accurate than forecasts from extrapolative models. Combined forecasts applied to out-of-sample data, however, did not result in markedly improved forecasting accuracy. Finally, valuation tests of alternative forecasting techniques offered strong evidence that investors place the greatest weight on forecasts from Value Line.     

Do UK Security Analysts Over-react?

Consensus analysts' earnings per share forecasts have become increasingly accessible in recent years and such measures have been widely adopted by academics as proxies for the market's expectations of earnings. Some US studies have suggested that analysts, in revising earnings forecasts, are prone to over-reaction. This study tests for evidence of over-reaction in revisions of the consensus earnings per share forecasts of UK companies reported by the Institutional Brokers Estimate System. For a series of periods, portfolios of companies attracting high and low revisions of earnings forecasts are constructed. We then compare the subsequent earnings forecast of the companies which attracted high revisions in the portfolio formation period with those of the companies which attracted low revisions in the portfolio formation period. We also compare actual changes in annual earnings with forecast changes in annual earnings. Both analyses suggest that UK analysts are prone to under-reaction, a finding which contrasts with the US studies which have identified over-reaction. There is little evidence that the market, in reacting to earnings forecast revisions, fails to recognise this under-reaction.     

Analyst Earnings Forecasts for Publicly Traded Insurance Companies

Several trends in the insurance and financial services industry, including demutualizationconsolidation, and deregulation, have attracted increasing attention from investors and financial analysts. This paper investigates the accuracy of the earnings forecasts of financial analysts for insurance companies. Our empirical results indicate that analyst forecasts outperform random walk time-series forecasts. Furthermore, we find that both disagreement over earnings forecasts among analysts and the relative forecasting error in the mean forecasts is smaller for life insurers than for property-casualty insurers, whereas the relative errors for forecasts for multiple-line insurers are in between the two. Forecasting error is a negative function of firm size and the number of analysts who are following a company, and is a positive function of the disagreement among analysts.Analyst forecasts have a timing advantage over the random walk model. Our results also suggest that the fair value reporting requirement (SFAS 115), which has been in effect since 1994, has enhanced the accuracy of analyst forecasts. The SFAS 115 has improved the superiority of analyst forecasts over the random walk forecasts for life insurers, but not for property-casualty insurers, and there is a weak improvement for multiple-line insurers. JEL Classification: G15     

How do financial analysts interpret industrial firms' corporate refocusing announcements?

This study investigates how analysts perceive the effect of corporate refocusing announcements on UK industrial firms' future earnings by examining current-year and one-year-ahead earnings forecast revisions, current-year target price revisions and earnings forecast errors in the five years surrounding a refocusing announcement year. The results reveal that analysts adjust their earnings forecasts downward in a refocusing announcement year and the following two years, predicting that operating performance in the post-refocusing period is likely to decline relative to their former earnings forecasts. Secondly, there is no evidence that analysts issue biased earnings forecasts after refocusing announcements or that their forecasts appear less accurate. Thirdly, they adjust their earnings forecasts downward in a refocusing announcement year with downward market movement. However, they do not similarly adjust their earnings forecast upward with upward market movement. The magnitude of downward adjustments exceeds that of upward adjustments. They also adjust current-year target price forecasts downward with downward market movement in the year prior to a refocusing announcement.     

Are analysts’ earnings forecasts more accurate when accompanied by cash flow forecasts?

We examine whether analysts’ earnings forecasts are more accurate when they also issue cash flow forecasts. We find that (i) analysts’ earnings forecasts issued together with cash flow forecasts are more accurate than those not accompanied by cash flow forecasts, and (ii) analysts’ earnings forecasts reflect a better understanding of the implications of current earnings for future earnings when they are accompanied by cash flow forecasts. These results are consistent with analysts adopting a more structured and disciplined approach to forecasting earnings when they also issue cash flow forecasts. Finally, we find that more accurate cash flow forecasts decrease the likelihood of analysts being fired, suggesting that cash flow forecast accuracy is relevant to analysts’ career outcomes.     

The accuracy of earnings forecasts in IPO prospectuses on the Kuala Lumpur Stock Exchange

This paper examines the accuracy of earnings forecasts made by managers of Malaysian initial public offerings (IPOs) during the period 1984–1995. It is a mandatory requirement for Malaysian IPOs to furnish earnings forecasts together with the opinions thereon of the auditors and the lead underwriter in their prospectuses. Their accuracy is measured by forecast errors, absolute forecast errors, squared forecast errors and standardised forecast errors. The results suggest that, on average, managers under-forecast earnings by 33.37%. A comparison with the naive no change model in earnings suggests that 96 out of 122 companies outperform this model. A number of company specific characteristics (size, age, forecast interval, gearing, proportion of shares retained by owners, auditor reputation and industry) are tested. The results reveal that both the age and industry classification of the company are statistically significant, and that management earnings forecasts are particularly inaccurate where firms experience a decline in earnings. Key words: accuracy of prospectus earnings forecasts, initial public offerings, accounting in Malaysia.     

Endogenous entry/exit as an alternative explanation for the disciplining role of independent analysts

Gu and Xue [2008. The superiority and disciplining role of independent analysts. Journal of Accounting and Economics, this issue, doi:10.1016/j.jacceco.2008.02.002] study the disciplining effect of independent analysts on the accuracy and forecast relevance of the forecasts of non-independent analysts. One of the intriguing results is that while independent analysts issue inferior forecasts, their presence appears to reduce the forecast bias, improve the forecast accuracy and increase the forecast relevance of forecasts issued by non-independent analysts. We explore alternative explanations for the Gu–Xue results. Our evidence of endogenous entry and exit of independent analysts provides a more compelling explanation for the reported results.     

Analyst revenue forecast reporting and the quality of revenues and expenses

We decompose earnings quality into revenue and expense quality and examine their associations with analyst propensity to supplement their earnings forecasts with revenue forecasts. Analysts report more revenue forecasts to I/B/E/S when expense quality is low to compensate for the low accuracy of their earnings estimates, which has a positive association with expense quality. Expense quality is unassociated with revenue forecast accuracy, thus revenue forecasts become increasingly useful for valuing firms when expense quality is low. Analysts report fewer revenue forecasts when revenue quality is low because both earnings and revenue forecast accuracy decline as revenue quality deteriorates. To control for endogeneity, we use firm‐fixed effects to control for unobserved time‐invariant heterogeneity across firms, instrumental variables regressions and regression in changes.     

Probability Forecasts of Macroaggregates in the Turkish Economy

We provide probability forecasts of key Turkish macroeconomic variables such as inflation and output growth. The probability forecasts are derived from a core vector error correction model of the Turkish economy and its several variants. We use model and window averaging to address uncertainties arising from estimated models and possible structural breaks. The performances of the different models and their combinations are evaluated using relevant forecast accuracy tests in different pseudo out-of-sample settings. The results indicate that successful directional forecasts can be obtained for output growth and inflation. Averaging over both the models and the estimation windows improves the level of accuracy of the forecasts.     

The Effect of Issuing Biased Earnings Forecasts on Analysts' Access to Management and Survival

This study offers evidence on the earnings forecast bias analysts use to please firm management and the associated benefits they obtain from issuing such biased forecasts in the years prior to Regulation Fair Disclosure. Analysts who issue initial optimistic earnings forecasts followed by pessimistic earnings forecasts before the earnings announcement produce more accurate earnings forecasts and are less likely to be fired by their employers. The effect of such biased earnings forecasts on forecast accuracy and firing is stronger for analysts who follow firms with heavy insider selling and hard‐to‐predict earnings. The above results hold regardless of whether a brokerage firm has investment banking business or not. These results are consistent with the hypothesis that analysts use biased earnings forecasts to curry favor with firm management in order to obtain better access to management's private information.     

Market implied future earnings and analysts’ forecasts

This study provides evidence on market implied future earnings based on the residual income valuation (RIV) framework and compares these earnings with analyst earnings forecasts for accuracy (absolute forecast error) and bias (signed forecast error). Prior research shows that current stock price reflects future earnings and that analyst forecasts are biased. Thus, how price-based imputed forecasts compare with analyst forecasts is interesting. Using different cost of capital estimates, we use the price-earnings relation and impute firms’ future annual earnings from three residual income (RI) models for up to 5 years. Relative to I/B/E/S analyst forecasts, imputed forecasts from the RI models are less or no more biased when cost of capital is low (equal to a risk-free rate or slightly higher). Analysts slightly outperform these RI models in terms of accuracy for immediate future (1 or 2) years in the forecast horizon but the opposite is true for more distant future years when cost of capital is low. A regression analysis shows that, in explaining future earnings changes, analyst forecasts relative to imputed forecasts do not impound a significant amount of earnings information embedded in current price. In additional tests, we impute future long-term earnings growth rates and find that they are more accurate and less biased than I/B/E/S analyst long-term earnings growth forecasts. Together, the results suggest that the RIV framework can be used to impute a firm’s future earnings that are high in accuracy and low in bias, especially for distant future years.     

Determinants of analysts’ revenue forecast accuracy

This study investigates financial analysts’ revenue forecasts and identifies determinants of the forecasts’ accuracy. We find that revenue forecast accuracy is determined by forecast and analyst characteristics similar to those of earnings forecast accuracy—namely, forecast horizon, days elapsed since the last forecast, analysts’ forecasting experience, forecast frequency, forecast portfolio, reputation, earnings forecast issuance, forecast boldness, and analysts’ prior performance in forecasting revenues and earnings. We develop a model that predicts the usefulness of revenue forecasts. Thereby, our study helps to ex ante identify more accurate revenue forecasts. Furthermore, we find that analysts concern themselves with their revenue forecasting performance. Analysts with poor revenue forecasting performance are more likely to stop forecasting revenues than analysts with better performance. Their decision is reasonable because revenue forecast accuracy affects analysts’ career prospects in terms of being promoted or terminated. Our study helps investors and academic researchers to understand determinants of revenue forecasts. This understanding is also beneficial for evaluating earnings forecasts because revenue forecasts reveal whether changes in earnings forecasts are due to anticipated changes in revenues or expenses.     

Rationality and Analysts' Forecast Bias

This paper proposes and tests a quadratic-loss utility function for modeling corporate earnings forecasting, where financial analysts trade off bias to improve management access and forecast accuracy. Optimal forecasts with minimum expected error are optimistically biased and exhibit predictable cross-sectional variation related to analyst and company characteristics. Empirical evidence from individual analyst forecasts is consistent with the model's predictions. These results suggest that positive and predictable bias may be a rational property of optimal earnings forecasts. Prior studies using classical notions of unbiasedness may have prematurely dismissed analysts' forecasts as being irrational or inaccurate.