Intangible Assets, Information Complexity, and Analysts' Earnings Forecasts

Abstract:   We examine the relation between analysts' earnings forecasts and firms' intangible assets, including technology‐based intangibles, brand names, and recognized intangibles. We predict that high information complexity of intangible assets increases the difficulty for analysts to assimilate information and increases analysts' forecast error of intangibles‐intensive firms. We find a positive association between analysts' forecast error and the firm's intangible intensity that deviates from the industry norm. We also find that analysts' forecast errors are greater for firms with diverse and innovative technologies. In contrast, analysts' forecast errors are smaller for biotech/pharmaceutical and medical equipment firms that are subject to intangibles‐related regulation.     

The Value Relevance of Management Forecasts and Their Impact on Analysts' Forecasts: Empirical Evidence From Japan

A major financial disclosure feature in Japan is that stock exchanges require firms to provide next year's earnings forecasts. This study investigates the value relevance of Japanese management earnings forecasts and their impact on analysts' earnings forecasts. First, the value relevance of management forecasts is investigated using a valuation framework provided by Ohlson (2001 ), in which firm value is expressed as a function of book value, current earnings and next year's expected earnings. The analysis yields that of the three accounting variables examined, management forecasts have the highest correlation and incremental explanatory power with stock price.
Next, the impact of management forecasts on analysts' forecasts is examined. The results show that more than 90% of changes in analysts' forecasts are explained by management forecasts alone. Further analysis reveals that the heavy dependence of financial analysts on management forecasts in formulating their own forecasts may partially be attributed to the relatively high accuracy of management forecasts. At the same time, financial analysts also somewhat modify management forecasts when certain financial factors indicate that the credibility of management forecasts is in doubt.
Overall, this study presents empirical evidence that Japanese management forecasts provide useful information for the market and have a significant influence on analysts' forecasts.     

Analysts' Forecasts and the Broker Relationship

Analysts' ability to forecast earnings per share has been the subject of considerable debate. A concern highlighted in previous research is the agency problem which may arise when analysts have a close working relationship with the firms for which they are providing forecasts. This paper provides evidence that this relationship does not improve the accuracy of the earnings forecasts, but stimulates optimistic forecasts. In addition, the paper examines whether firm size is a factor in forecast accuracy or bias.     

The Quality of Analysts' Earnings Forecasts During the Asian Crisis: Evidence from Singapore

We bring together three disparate strands of literature to develop a comprehensive empirical framework to examine the efficiency of security analysts' earnings forecasts in Singapore. We focus specifically on how the increased uncertainty and the negative market sentiment during the period of the Asian crisis affected the quality of earnings forecasts. While we find no evidence of inefficiencies in the pre-crisis period, our results suggest that after the onset of the crisis, analysts (1) issued forecasts that were systematically upward biased; (2) did not fully incorporate the (negative) earnings-related news; and (3) predicted earnings changes which proved too extreme.     

An Empirical Analysis of the Bias and Rationality of Profit Forecasts Published in New Issue Prospectuses

Our study sets out to assess the accuracy of profit forecasts made by IPOs in Hong Kong. We use a variety of measures and tests to examine the accuracy, bias, rationality, and superiority of earnings estimates. The results show that forecast accuracy compares favourably with the findings from the developed economies of Australia, Britain, Canada, and New Zealand. Forecasts are shown to be superior to the predictions from time series models. IPOs tend to underforecast in the sense that actual profits exceed the forecasts. The rationality tests show mixed results. Cross-sectional analyses of forecast accuracy have poor explanatory power although the Big Six reporting accountants are associated with smaller forecast errors.     

An Empirical Analysis of the Bias and Rationality of Profit Forecasts Published in New Issue Prospectuses

Our study sets out to assess the accuracy of profit forecasts made by IPOs in Hong Kong. We use a variety of measures and tests to examine the accuracy, bias, rationality, and superiority of earnings estimates. The results show that forecast accuracy compares favourably with the findings from the developed economies of Australia, Britain, Canada, and New Zealand. Forecasts are shown to be superior to the predictions from time series models. IPOs tend to underforecast in the sense that actual profits exceed the forecasts. The rationality tests show mixed results. Cross-sectional analyses of forecast accuracy have poor explanatory power although the Big Six reporting accountants are associated with smaller forecast errors.     

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.     

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.     

A Simultaneous Equations Analysis of Analysts' Forecast Bias, Analyst Following, and Institutional Ownership

In this paper we use a simultaneous equations model to examine the relationship between analysts' forecasts, analyst following, and institutions' investment decisions. Estimates of our three equation model using US data indicate that higher institutional demand leads to greater optimism among analysts and lower analyst following. At the same time, institutional demand increases with increasing optimism in analysts' forecasts but decreases with analyst following. We also investigate firm characteristics as determinants of analysts' and institutions' decisions. Empirical estimates of the effects of these characteristics indicate that agency‐driven behavioral considerations are significant.     

Economic Value Added,Future Accounting Earnings,and Financial Analysts' Earnings Per Share Forecasts

Empirical research to date on the relative effectiveness of Economic Value Added (EVA) and earnings per share (EPS) as measures of firm performance for stock valuation has been mixed. In contrast to prior research, which primarily focuses on the correspondence of these measures with shareholder value and changes therein, we examine their relative effectiveness in predicting future earnings and their role in enhancing the accuracy of analysts' forecasts. Our results indicate that EVA contains information that is incremental to EPS in predicting future earnings. In addition, we find that despite this potential for EVA to add incremental value to analysts' forecasts of future earnings, analysts do not use the information in reported EVA appropriately, but appear rather to overweigh it.     

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.     

Investors' Use of Historical Forecast Bias to Adjust Current Expectations

We explore the extent to which investor response to earnings information differs in the presence of historical bias in earnings forecasts. Overall, the results are consistent with the notion that investors take historical forecast bias into account when interpreting information in earnings announcements and that the market's reaction to forecast errors is larger (less negative) when forecasts are historically more optimistic and suggests that the functional form commonly used in the earnings response literature does not appropriately capture the effect of real unexpected earnings information (i.e., investors' expectation errors as opposed to analysts' forecast errors) on stock returns.     

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.     

Financial Analysts' Earnings Forecast Dispersion and Intraday Stock Price Variability Around Quarterly Earnings Announcements

This study investigates the relationship between the dispersion of analysts' earnings forecasts and stock price variability around quarterly earnings announcements. Consistent with theoretical predictions, the empirical analysis shows that stock price variability at the time of earnings announcements is positively related to the degree of analysts' predisclosure earnings forecast dispersion. Additionally, firms with high levels of forecast dispersion exhibit significant increases in price variability for longer periods prior to and following earnings announcements than do firms with low levels of forecast dispersion. These results suggest that there is information about the earnings announcement that becomes available to at least a subset of investors prior to the earnings release and that market participants take different amounts of time to process the information conveyed by the earnings announcement.     

Analysts' Forecasts Following Forced CEO Changes

This paper examines analysts' earnings forecasts during the period of uncertainty following a change of chief executive officer (CEO). It distinguishes between forced and non‐forced CEO changes, and examines whether analysts utilize their information advantage to reduce the heightened uncertainty of a forced change of CEO. Examining a sample of Australian companies followed by analysts between 1999 and 2009, we find that forecasting accuracy is lower and earnings forecasts are more optimistic for firms experiencing forced CEO turnover compared to firms not undergoing such a change. However, dispersion is not statistically different. The results suggest that forced CEO turnover events provide a challenge to the forecasting environment for analysts. During CEO changes, investors should be aware that forecasts are less accurate and have an optimistic bias.     

The Relevance of Analysts' Earnings Forecasts in Japan

Abstract:   This study examines the role of financial analysts in equity valuation in Japan by comparing the relevance of financial analysts' earnings forecasts, over financial statement information, to investors' decisions. We find that the value‐relevance of a set of accounting variables is very modest, but the incremental contribution of analysts' forecasts is very significant. This is in line with the expectation that the skill and expertise of analysts are more valuable in markets with poor financial disclosure, such as Japan. We also find that the importance of the financial statements increases over time while the importance of the analysts' forecasts does not change. We also provide evidence of the effect of Japanese corporate groupings, keiretsu, on the informativeness of accounting signals and earnings forecasts. The results show that the contribution of accounting variables to valuation is lower for keiretsu firms, which supports the exclusionary hypothesis that companies which are a part of keiretsu, disclose less information than do non‐keiretsu companies. The analysts' forecasts are equally important for investors in both types of firms.     

The Timing of Asset Sales: Evidence of Earnings Management?

This paper presents empirical evidence from a sample of publicly traded Singaporean firms on the question: to what extent do firms manage earnings through the timing of asset sales? Previous studies have focused on accounting motives behind asset sales, ignoring the need to also consider economic motives. Some empirical evidence is provided to support the hypothesis that managers of firms with decreasing net earnings–per–share smooth earnings upwards using asset sales.     

Accruals Management to Achieve Earnings Benchmarks: A Comparison of Pre-managed Profit and Loss Firms

Abstract:  This study examines whether firms with profits before accruals management are more likely than firms with losses before accruals management to meet or exceed earnings benchmarks when pre-managed earnings are below those benchmarks. We extend Brown (2001) by documenting that the differential propensity to achieve earnings benchmarks by profitable and nonprofitable firms results from differential accruals management behavior. We find that firms with profits before accruals management are more likely than firms with losses before accruals management to have pre-managed earnings below both analysts' forecasts and prior period earnings and reported earnings above these benchmarks.     

Tests of Market Reaction and Analysts' Forecast Revisions to the Disclosure of Improved Management Earnings Expectations: A Case of Concurrent Bad News Management Earnings Forecasts

This paper tests whether a negative stock market reaction, associated with a management forecast of near term bad earnings, is lessened by a concurrent management forecast of improved longer term earnings expectations. Stock market reactions depend on the creditability of management forecasts of improved earnings expectations. In this analysis, the authors examined market reactions around the time of management forecasts of bad earnings, with and without longer-term management forecasts of improved earnings expectations. The results show that the stock market reaction is significantly less negative when management forecasts of bad earnings are followed by management forecasts of improved long run earnings expectations than when management forecasts of bad earnings are not accompanied by management forecasts of improved earnings expectations. In addition, this paper examines financial analysts' reactions to management bad earnings forecasts and management forecasts of improved earnings expectations. The findings show that analysts react less negatively to management forecasts of improved earnings expectations than to management forecasts of bad earnings. An analysis of a sub-sample of observations shows that analysts consider management forecasts of improved earnings expectations to imply improved expected future performance, thus conveying that analysts give credence to management forecasts of improved earnings expectations. However, results show that the stock market and analysts are unable to distinguish management forecasts of improved earnings expectations that come true from management forecasts of improved earning expectations that do not come true.     

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.