The effect of management earnings forecast characteristics on cost of equity capital

This study uses a framework presented in Hirst, Koonce, and Venkataraman (2008) to assess how differences in management earnings forecast characteristics influence a firm's cost of equity capital. I find that less specific forecasts, pessimistic forecasts, and forecasts that predict a loss for the period are associated with higher cost of equity capital levels and more timely forecasts and forecasts with more information content are associated with lower cost of equity capital levels. Analysis interacting control variables and forecast antecedents with forecast characteristics indicates that the effects forecast characteristics have on cost of equity capital are either enhanced or moderated depending on firm beta, firm size, firm book-to-market ratios, analyst following, prior forecast bias, and earnings quality. The results highlight the importance of interacting key variables when interpreting the market effect of management earnings forecasts.     

How do auditors view managers’ voluntary disclosure strategy? The effect of earnings guidance on audit fees

The objective of this study is to examine the relation between attributes of earnings forecasts issued by managers and audit fees. Although there is an extensive literature on managers’ disclosure of earnings forecasts, there is a paucity of research on how auditors incorporate information from these voluntary disclosures. We find that the issuance of an annual or quarterly management earnings forecast in the prior period is positively associated with the current period audit fees. Our results indicate that on average, audit fees are higher by about 7% for firm-years associated with an annual forecast. Among the firms that issue earnings forecasts, we find no association between audit fees and likelihood of updating a previously issued earnings forecast, indicating that auditors do not view such behavior negatively. Further, we find audit fees to be positively associated with the error and the bias (or optimism) in the forecasts for annual forecasts but not for quarterly forecasts. Overall, these results suggest that management’s forecast behavior captures higher business risk for the auditor via greater risk of earnings management or litigation risk.     

Volatility timing: How best to forecast portfolio exposures

This paper investigates how best to forecast optimal portfolio weights in the context of a volatility timing strategy. It measures the economic value of a number of methods for forming optimal portfolios on the basis of realized volatility. These include the traditional econometric approach of forming portfolios from forecasts of the covariance matrix. Both naïve forecasts using simple historical averages, and those generated from econometric models are considered. A novel method, where a time series of optimal portfolio weights are constructed from observed realized volatility and direct forecast is also proposed. A number of naïve forecasts and the approach of directly forecasting portfolio weights show a great deal of merit. Resulting portfolios are of similar economic benefit to a number of competing approaches and are more stable across time. These findings have obvious implications for the manner in which volatility timing is undertaken in a portfolio allocation context.     

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.     

Additional Evidence on Analysts’ Decision to Issue Disaggregated Earnings Forecasts: Strategic Biasing

This study examines why analysts issue disaggregated earnings forecasts to I/B/E/S. Some recent studies suggest that analysts with superior forecasting ability issue disaggregated earnings forecasts to build reputation in the marketplace and stop forecast disaggregation once their reputation has been established. Based on an analysis of I/B/E/S forecast data for U.S. firms from 1998 to 2008, we find that, in a given year, about 20%–34% of analysts disaggregate for some, but not for all the firms that they follow. This evidence of selective disaggregation by analysts suggests that reputation building alone does not fully explain the decision to disaggregate forecasts. We hypothesize that the decision to disaggregate earnings forecasts is at the firm‐level as well and is systematically related to the analysts’ bias in the issued forecasts. Our findings are that (a) analysts’ overall optimistic bias and forecast errors decrease monotonically with the level of forecast disaggregation, and (b) analysts that selectively disaggregate their forecasts for some firms or who do not persistently disaggregate a given firm's forecasts exhibit more positive bias and larger forecast errors. Our findings are consistent with the notion that the analysts who issue biased forecasts, for example, to curry favour with the management, are less likely to provide disaggregated information as part of the forecast.     

Risk-based forecasting and planning and management earnings forecasts

This study examines the association between a firm’s internal information environment and the accuracy of its externally disclosed management earnings forecasts. Internally, firms use forecasts to plan for uncertain futures. The risk management literature argues that integrating risk-related information into forecasts and plans can improve a firm’s ability to forecast financial outcomes. We investigate whether this internal information manifests itself in the accuracy of external earnings guidance. Using detailed survey data and publicly disclosed management earnings forecasts from a sample of publicly traded U.S. companies, we find that more sophisticated risk-based forecasting and planning processes are associated with smaller earnings forecast errors and narrower forecast widths. These associations hold across a variety of different planning horizons (ranging from annual budgeting to long-term strategic planning), providing empirical support for the theoretical link between internal information quality and the quality of external disclosures.     

Evaluating cross-sectional forecasting models for implied cost of capital

The computation of implied cost of capital (ICC) is constrained by the lack of analyst forecasts for half of all firms. Hou et al. (J Account Econ 53:504–526, 2012, HVZ) present a cross-sectional model to generate forecasts in order to compute ICC. However, the forecasts from the HVZ model perform worse than those from a naïve random walk model and the ICCs show anomalous correlations with risk factors. We present two parsimonious alternatives to the HVZ model: the EP model based on persistence in earnings and the RI model based on the residual income model from Feltham and Ohlson (Contemp Account Res 11:689–732, 1996). Both models outperform the HVZ model in terms of forecast bias, accuracy, earnings response coefficients, and correlations of the ICCs with future returns and risk factors. We recommend that future research use the RI model or the EP model to generate earnings forecasts.     

The role of accounting conservatism in management forecast bias

We investigate whether management earnings forecasts fully incorporate information in historical accounting conservatism. We find that management earnings forecasts are more optimistic for firms with greater accounting conservatism in the previous year. We further examine whether this conservatism-related optimistic bias in management earnings forecasts varies with managers’ difficulty predicting earnings accurately, managers’ opportunistic incentives, and the firms’ litigation risk. We find that the negative association between management forecast errors and conservatism increases, to various extent, with the firms’ operating cycles, earnings volatility, and the width of forecast range but does not change with proxies for opportunistic incentives or litigation risk. These results suggest that forecast difficulty is the primary reason for managers’ failure to incorporate conservatism fully in their earnings forecasts.     

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.     

Outside Directors,Litigation Environment,and Management Earnings Forecasts

This study examines whether outside directors factor in litigation costs for the firm while monitoring optimal disclosure policy. It investigates the association of management earnings forecast disclosure and the proportion of outside directors across two regimes with unequal litigation costs, the United States and Canada. I find that the positive association between forecast frequency/ precision and the proportion of outside directors is stronger in Canada. This suggests that outside directors are more likely to encourage disclosure in less litigious Canada. I also find that firm‐level governance mechanisms such as outside directors and country‐level litigation environment act as governance substitutes in determining unbiased forecasts. Specifically, the negative association between forecast bias and the proportion of outside directors is stronger in Canada. I also revisit the effect of legal regime on forecast disclosure in a non‐U.S. context. Recent legislation has increased the likelihood of class‐action lawsuits in Canada. The passage of these laws has decreased the precision in forecasts by Canadian firms.     

Investor sentiment and management earnings forecast bias

This study investigates whether investor sentiment is associated with behavioral bias in managers’ annual earnings forecasts that are generally issued early in the year when uncertainty is relatively high. I provide evidence that management earnings forecast optimism increases with investor sentiment. Furthermore, I find that managers’ annual earnings forecasts are more pessimistic during low‐sentiment periods than during normal‐sentiment periods. Since managers lack incentives to further deflate stock prices during a low‐sentiment period, this evidence indicates that sentiment‐related management earnings forecast bias is likely to be unintentional. In addition, I find that the relationship between management earnings forecast bias and investor sentiment is stronger for firms with higher uncertainty, consistent with investor sentiment having a greater influence on management earnings forecasts when uncertainty is higher.     

Analysts' Rationality and Forecast Bias: Evidence from Sales Forecasts

When optimistic forecasts can improve access to management, rational analysts have incentives to issue optimistically-biased forecasts (Lim, 2001). This paper proposes that the extent of this optimistic forecast bias will depend on the forecast's importance to management. If management attaches less importance to a forecasted measure, analysts should decrease their forecast bias because the expected benefits of issuing optimistic forecasts are less. We examine analysts' earnings and sales forecasts, and predict that analysts' optimistic bias will be greater for earnings than for sales. Results are consistent with our predictions and contribute to the evidence that analysts' forecast bias is rational and intentional.     

Serial Correlation in Management Earnings Forecast Errors

We examine whether management earnings forecast errors exhibit serial correlation and how analysts understand the serial correlation property of management forecast errors (MFEs). MFEs should not exhibit serial correlation if managers efficiently process information in prior forecast errors and truthfully convey their earnings expectations through management forecasts. However, for long‐horizon management forecasts of annual earnings, we find significantly positive serial correlation in MFEs, and sample self‐selection does not seem to drive this phenomenon. Further analyses suggest that managers’ unintentional information processing bias contributes to this positive serial correlation. Analysts anticipate the intertemporal persistence of MFEs but underestimate the persistence level when reacting to management forecasts. Our findings have implications for market participants who rely on management forecasts to form earnings expectations, and also shed light on the efficiency of managerial decision making.     

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 guidance and market uncertainty

We study the effect of disclosure on uncertainty by examining how management earnings forecasts affect stock market volatility. Using implied volatilities from exchange-traded options prices, we find that management earnings forecasts increase short-term volatility. This effect is attributable to forecasts that convey bad news, especially when firms release forecasts sporadically rather than on a routine basis. In the longer run, market uncertainty declines after earnings are announced, regardless of whether there is a preceding earnings forecast. This decline is mitigated when the firm issues a forecast that conveys negative news, implying that these forecasts are associated with increased uncertainty.     

Why Do Managers Explain Their Earnings Forecasts?

Managers often explain their earnings forecasts by linking forecasted performance to their internal actions and the actions of parties external to the firm. These attributions potentially aid investors in the interpretation of management forecasts by confirming known relationships between attributions and profitability or by identifying additional causes that investors should consider when forecasting earnings. We investigate why managers choose to provide attributions with their forecasts and whether the attributions are related to security price reactions to management earnings forecasts. Using a sample of 951 management earnings forecasts issued from 1993 to 1996, we find that attributions are more likely for larger firms, less likely for firms in regulated industries, less likely for forecasts issued over longer horizons, more likely for bad news forecasts, and more likely for forecasts that are maximum type. Furthermore, attributions are associated with greater absolute price reactions to management forecasts, more negative price reactions to management forecasts (forecast news held constant), and a greater price reaction per dollar of unexpected earnings. Our findings hold after control for the aforementioned determinants of attributions and after control for other firm‐ and forecast‐specific variables that are often associated with security prices.     

Optimistic bias in management forecasts by Japanese firms to avoid forecasting losses

Listed firms in Japan are effectively compelled to report management forecasts of sales, ordinary income, and net income along with actual earnings and sales each year. Prior studies report that Japanese managers tend to announce optimistic forecasts of earnings. We show that a large part (61.6%) of the overall optimistic bias in management earnings forecasts in Japan can be explained by loss forecast avoiding behavior of a small fraction (5.25%) of firms. Such behavior is caused in part by the view of the main bank and power group that the management forecast of earnings is the manager's earnings target. Our findings suggest that the Japanese stock market recognizes such loss forecast avoidance and accordingly discounts new information in management forecasts.     

Forecasting the past: the case of US interest rate forecasts

This study evaluates 10-year US government bond yield forecasts and three-month US Treasury bill rate forecasts for the period between October 1989 and December 2004. In total, 136 forecast time series with approximately 13,800 forecast data were scrutinized, making this the most extensive analysis of interest rate forecasts to date. Not one of the forecast time series proved to be unbiased. In the majority of cases, information from the past was not efficiently integrated into the forecasts. The sign accuracy is significantly better than random walk forecasts in only a very few of the forecast time series. The modified Diebold–Mariano test for forecast encompassing reveals that the information content of most of the forecast time series is lower than that of the naïve forecasts, the simple ARIMA models, the implicit forward rates, or average interest rate expectations. The forecasting process is dominated by the present and past market situation.     

A new approach to predicting analyst forecast errors: Do investors overweight analyst forecasts?

I provide evidence that investors overweight analyst forecasts by demonstrating that prices do not fully reflect predictable components of analyst errors, which conflicts with conclusions in prior research. I highlight estimation bias in traditional approaches and develop a new approach that reduces this bias. I estimate characteristic forecasts that map current firm characteristics into forecasts of future earnings. Contrasting characteristic and analyst forecasts predicts analyst forecast errors and revisions. I find abnormal returns to strategies that sort firms by predicted forecast errors, consistent with investors overweighting analyst forecasts and predictable biases in analyst forecasts influencing the information content of prices.     

Do Managers Always Know Better? The Relative Accuracy of Management and Analyst Forecasts

We examine the relative accuracy of management and analyst forecasts of annual EPS. We predict and find that analysts’ information advantage resides at the macroeconomic level. They provide more accurate earnings forecasts than management when a firm's fortunes move in concert with macroeconomic factors such as Gross Domestic Product and energy costs. In contrast, we predict and find that management's information advantage resides at the firm level. Their forecasts are more accurate than analysts’ when management's actions, which affect reported earnings, are difficult to anticipate by outsiders, such as when the firm's inventories are abnormally high or the firm has excess capacity or is experiencing a loss. Although analysts are commonly viewed as industry specialists, we fail to find evidence that analysts have an information advantage over managers at the industry level. The two have comparable abilities to forecast earnings for firms with revenues or earnings that are more synchronous with their industries.