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     

The Profitability of Momentum Investing

We test for the presence of momentum profits in the UK over the period 1977 to 1998. The analysis shows that significant momentum profits are present in both a comprehensive sample of UK stocks and an accounting sub-sample. An analysis of sub-period results, seasonal effects, and the persistence of momentum profits confirms the robustness of the results. Controlling for factors known to be associated with differences in average returns, such as size, stock price, book-to-market ratio, and cash earnings-to-price ratio, cannot explain momentum profits. We also confirm that serial correlation in common factors and delayed price reaction to common factor realisations cannot explain momentum profits. We conclude that the momentum effect derives from market underreaction to either industry- or firm-specific information and it is a significant, independent phenomenon in UK stock returns.     

Analyst underreaction and the post-forecast revision drift

The post-forecast revision drift (PFRD), the phenomenon of delayed stock price reactions to analyst forecast revisions, is a well-documented market anomaly. Prior research attributes PFRD to underreaction by investors to analyst forecast revisions. This study investigates the role of the analyst forecast revision process itself in the PFRD anomaly. Using a large sample of US firms, we confirm prior findings of a positive serial correlation (momentum) in individual analysts’ revisions to their earnings forecasts and, based on both indirect and direct tests, document a positive association between this momentum and PFRD. Further analyses reveal that both the forecast revision momentum and PFRD vary in similar ways with respect to the nature of the news driving the revisions and the information environment. Collectively, our findings show that underreaction by individual analysts in the forecast revision process is an important contributor to the PFRD phenomenon.     

Improving the Precision of Analysts' Earnings Forecasts by Adjusting for Predictable Bias

This research demonstrates that publicly-available information can be used to develop estimates of analysts' optimistic bias in earnings forecasts. These bias estimates can be used to produce more accurate forecasts, resulting in significant reductions of both cross-sectional mean forecast error and error variance. When bias estimates are based on past observations of forecast error alone, however, reductions in mean forecast error are smaller, and forecast precision is unimproved. Further tests provide evidence of a significant association between returns and the bias predictable from contemporaneously-available information, suggesting that predictable bias is only partially discounted by market participants. This study has significant implications for researchers and investors. The pricing of predictable bias in analysts' forecasts may add error toinferences which are based on the association between returns and analyst forecast errors, and knowledge of the market's partial discounting of predictable bias may help investors to make more efficient resource allocations.     

The Effect of Multinationality on Security Analyst Underreaction

Previous research presented evidence of bias and positive serial correlation in forecast errors suggesting that analysts do not properly recognize the time–series properties of earnings when setting expectations of future earnings. A reason for the security analyst underreaction is the level of multinationality of the firm's activities. This study shows that analysts underreact to prior information more as the level of multinationality of the firm examined increases.     

On the Determinants of Optimism in Financial Analyst Earnings Forecasts: The Effect of the Market's Ability to Adjust for the Bias

This paper examines whether the documented bias in analyst earnings forecasts is intentional by examining whether it is related to the market's ability to adjust for this bias. For intentional bias to exist it is not enough for analysts to face incentives but rather, analysts should also be willing to respond to these incentives. As the market's ability to adjust for the bias increases, its market effects decrease while analyst reputation costs increase reducing analyst willingness to bias their forecasts. The paper utilizes a firm‐specific design that allows for both the bias component of the forecast error and the market's ability to adjust for the bias to be computed at the firm level. Results suggest that even though forecast error is positive in the latter part of the period under review reflecting overall analyst pessimism, the bias embedded in the forecasts is optimistic throughout the period. More importantly, I find that analyst forecast bias is decreasing in the market's ability to adjust for it. This result provides further evidence that analysts knowingly bias their forecasts and provides support for the existence of reporting bias, in particular. Thus, the evidence provides justification for recent regulatory efforts to increase the objectivity of analyst research reports.     

Earnings Forecasts and the Information Contained in Spinoff Announcements

This study examines spinoff announcements in conjunction with financial analysts’ forecasts of earnings. The analysis shows that spinoff announcement abnormal returns are significantly related to the firm's information environment as proxieci by financial analysts’ earnings prediction errors. The findings also indicate that analysts significantly increase their short-term earnings forecasts in response to spinoffs, but do not significantly revise their long-term earnings forecasts. However, the earnings revisions are not significantly different across prediction error groups, which confirms that spinoff-related abnormal returns cannot be attributed solely to expected performance gains.     

The Implications of Dispersion in Analysts' Earnings Forecasts for Future ROE and Future Returns

Dispersion in analysts' forecasts is empirically evaluated by associating dispersion with a firm's future accounting rate of return-on-equity (ROE) and future returns. Forecast dispersion is significantly and negatively associated with future ROE, consistent with the notion that firm disclosures and analysts' information acquisition efforts increase as firm prospects improve. Forecast dispersion is negatively associated with future returns. This appears due to the implications of dispersion for future ROE, and suggests that the market does not immediately assimilate the information contained in forecast dispersion. Dispersion also conveys information about firm-specific risk not captured by beta and firm size.     

Business Cycle and Management Earnings Forecasts

This study examines the effects of the economic cycle on the properties of management earnings forecasts. Although a large volume of accounting literature examines the determinants of managerial earnings forecasts, the properties of such forecasts, and the response of market participants to earnings forecasts (Cameron 1986; King et al., 1990; Hirst et al., 2008), research on management earnings forecasting incentivized by macro‐economic factors has received scant empirical investigation. We use the National Bureau of Economic Research economic cycle definition to operationalize economic recession, and consider some commonly used management earnings forecast characteristics, including forecast likelihood, forecast frequency, forecast error, forecast pessimism, and forecast precision. We find that the likelihood of providing management earnings forecasts and frequency of forecasts increases during economic recession. We also find that economic recession is positively associated with forecast error, but negatively associated with forecast precision. Our findings suggest macro‐economic factors as an important determinant of management earnings forecasts properties.     

Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies

Various theories have been proposed to explain momentum in stock returns. We test the gradual-information-diffusion model of Hong and Stein (1999) and establish three key results. First, once one moves past the very smallest stocks, the profitability of momentum strategies declines sharply with firm size. Second, holding size fixed, momentum strategies work better among stocks with low analyst coverage. Finally, the effect of analyst coverage is greater for stocks that are past losers than for past winners. These findings are consistent with the hypothesis that firm-specific information, especially negative information, diffuses only gradually across the investing public.     

Analysts Earnings Forecasts and the Roles of Earnings and Book Value in Equity Valuation

This study examines the effect of the degree of association between current earnings and expected future earnings on the relative importance of earnings and book value for explaining equity price. Consensus analysts forecasts of one-year-ahead earnings are used to proxy for expected future earnings and are compared to reported current earnings to measure the degree of the association. We find that the value-relevance of current earnings negatively correlates with the extent to which consensus analysts forecasts deviate from current earnings. We also find that the incremental explanatory power of book value for equity price positively correlates with this measure. These results remain robust after controlling for factors known to be affecting the value-relevance of earnings such as negative earnings and the earnings-to-book ratio. Our results also show that this analysts' forecast-based measure of `earnings persistence' dominates historical earnings variance in explaining cross-sectional variations in the value-relevance of earnings and book value.     

Analyst Following and Equity Offerings Subsequent to Initial Public Offerings

Analyst forecast information is collected for firms following their IPOs and is used in an examination of subsequent seasoned equity offerings (SEOs). Consistent with information asymmetry arguments, the analysis indicates that a larger percentage of firms conducting SEOs within three years of the IPO are covered by financial analysts than those without SEOs, and that analyst coverage is a significant predictor of subsequent SEOs. In addition, the results indicate that long-term earnings growth forecasts are larger for firms with subsequent SEOs, but growth forecasts decline significantly following the SEOs. Further, SEO abnormal returns exhibit a significant negative relationship with earnings growth forecasts. These results are consistent with windows of opportunity arguments since they suggest that SEOs are timed to coincide with the peak of earnings growth expectations, but that market participants compensate by reacting more negatively to offerings by firms with high growth forecasts.     

Management Earnings Forecasts,Earnings Announcements,and Institutional Trading in China

Abstract:

In this study, we investigate the trading behavior of institutional investors in China according to management earnings forecasts (MEFs) and earnings announcements (EAs). MEFs are mandatory under the stringent regulatory framework in China. We find evidence that both MEFs and EAs have an effect on the market. However, MEFs have a bigger effect on the market than do EAs. According to a sample of semiannual observations of firms from 2003 to 2008, we find that changes in the stock ownership of institutions are positively associated with EAs but not significantly associated with MEFs. When we further examine the relations between institutional characteristics and trading strategies, we find that growth funds exploit the arbitrage opportunity of MEFs.     

On the Use of Intra-Industry Information to Improve Earnings Forecasts

We investigate whether earnings forecasts are improved by earlier earnings disclosures by firms in the same industry. We find improvements for time series forecasts, but not for analysts' forecasts. Considering prior earnings announcements reduces correlations between forecast errors and security price reactions to earnings announcements, even when incorporating these announcements improves forecast accuracy. Our explanation for this anomaly, which is supported by additional analysis, is that intra-industry information facilitates predicting transitory, rather than permanent, earnings components. The question of whether information transfers improve earnings forecasts provides the context for the analysis, but the primary contribution is the documentation of intra-industry information transfers in a setting other than capital markets.     

Fundamental Information and Monetary Policy: The Implications for Earnings and Earnings Forecasts

Building on the work of Lev and Thiagarajan (1993) and Abarbanell and Bushee (1997 and 1998) this paper tests whether market-based information including dividend yield (Fama and French, 1998), firm size (Reinganum, 1981), and the ratio of book value to market value (Fama and French, 1992) add explanatory power to accounting data for predicting future earnings. The paper also tests whether earnings changes and the predictability of those changes are conditioned on monetary policy. It is found that the ratio of book value to market value is significantly related to earnings changes. Analyst forecast accuracy differs depending on monetary policy regime, but this difference is not due to differing interpretation of fundamental signals on financial statements appearing under differing monetary policy regimes. It is also found that there is a significant relation between monetary policy, earnings changes, and the level of signals concerning earnings changes.     

A Comparative Analysis of Earnings Forecasts in Europe

This study examines the accuracy and bias of financial analysts' EPS forecasts in nine European countries during 1987 to 1995. There are significant differences between the countries which may be due to the differences in earnings behaviour, accounting practices, and the influence of securities markets. An optimistic bias is endemic in European forecasts, consistent with research from the US. Investors who incorporate earnings forecasts in their stock selection procedures may be able to improve returns by explicitly adjusting their models for observed regularities in earnings forecast errors. However, we have shown that these regularities differ in incidence and magnitude across the countries studied, and further research is needed to effectively model these differences.     

Corporate Innovation Strategy,Analyst Forecasting Activities and the Economic Consequences

We examine the impact of corporate innovation strategy on analyst following and forecasting performance, as well as the associated economic consequences. Using a sample of US firms from 1992?2012, we find that firms pursuing an exploration‐oriented innovation strategy (as opposed to an exploitation‐oriented innovation strategy) are associated with lower analyst coverage, higher forecast error and dispersion. The effect is less pronounced for firms with greater disclosure of innovation activities, and for firms followed by analysts with more firm‐specific experience. We also examine how innovation strategy affects the perceived credibility of analyst forecasts and find that investors appear to be less responsive to forecast revisions issued for exploratory firms. Such firms also incur a higher level of cash holdings, greater internal financing, and lower dividend ratio. The findings of this paper advance our understanding of how a public company's choice of innovation strategy affects its performance in the capital markets as well as the associated economic consequences.     

Consistent Analyst Expectation Error and Earnings Management: Evidence from China

Using data from the Chinese A-share market in 2004–12, we show how cognitive bias of individual analysts led to counterproductive effect in less-developed financial markets. We form an ex ante measure of analysts’ expectation error, a measure suitable for markets with a short history. We find that star analysts tend to be more optimistic than ordinary analysts, and their biased opinions influence other analysts because of analyst herding behavior. Two-stage least square regression results suggest that consistent expectation errors among analysts can lead to earnings management. These insights are valuable to investors and regulators.