This paper reveals that in addition to fundamental factors, the 52-week high price and recent investor sentiment play an important role in analysts' target price formation. Analysts' forecasts of short-term earnings and long-term earnings growth are shown to be important explanatory variables for target prices; equally, the 52-week high price and recent investor sentiment are also shown to explain target price levels and especially target price biases. Our analysis additionally reveals that analysts place greater weight on these two non-fundamental factors in settings with greater task complexity and to some extent in those with greater resource constraints. Conversely, on balance, the results suggest that this increased reliance does not translate into an increased impact per unit of each non-fundamental factor on forecast bias. Finally, our results show that target prices are useful in predicting future stock returns beyond earnings forecasts and commonly used risk proxies. However, in an internally consistent fashion, the informativeness of target prices for future returns is significantly reduced when greater weight is placed on either the 52-week high or recent investor sentiment in the target price formation process.

SYNOPSIS This study examines quantitative long-term earnings growth (LTG) forecasts issued by publicly traded firms. While the difficulty of verifying management LTG forecasts provides incentives for self-serving disclosures, we find that stakeholder interests and forecast credibility considerations significantly constrain such tendencies. In particular, we find that demand from market participants, information asymmetry, peer LTG forecast provision, product market competition, and industry profitability drive management LTG forecast issuance, while poor performance and high uncertainty over firm growth prospects deter management LTG forecast issuance. Moreover, we provide evidence that management LTG forecasts, on average, provide incremental information about future earnings growth, and that high competition and investor monitoring increase LTG forecast informativeness, consistent with predictions of theoretical cheap talk models. Our findings also indicate that both upward and downward LTG guidance provide incremental information about future earnings growth, and that analysts revise their LTG forecasts in the direction of LTG guidance. Overall, our study contributes to the voluntary disclosure literature by providing evidence that suggests elements of a firm's disclosure environment significantly influence the issuance and informativeness of difficult-to-verify disclosures. JEL Classifications: C23; D81; D82; M41.

ABSTRACTWe examine whether financial analysts understand the valuation implications of unconditional accounting conservatism when forecasting target prices. While accounting conservatism affects reported earnings, conservatism per se does not have an effect on the present value of future cash flows. We examine whether analysts adjust for the effect of conservatism included in their earnings forecasts when using these forecasts to estimate target prices. We find that signed target price errors (actual minus forecast) have a significant positive association with the degree of conservatism in forward earnings, suggesting that target prices are biased due to accounting conservatism. Cross‐sectional analysis suggests that more sophisticated analysts and superior long‐term forecasters adjust for conservatism to a greater extent than other analysts. In additional analyses, we explore the mechanism through which conservatism leads to bias in target prices. We first show that analysts' earnings forecasts are negatively associated with the degree of conservatism; that is, analysts include the effect of unconditional conservatism in their earnings forecasts. Based on alternative earnings‐based valuation models that analysts may use, our evidence suggests that analysts fail to appropriately adjust their valuation multiple for the effect of conservatism included in their earnings forecasts when using these forecasts to derive target prices. As a consequence, we find that, for extreme changes in conservatism, the bias in analysts' target prices due to conservatism leads to a distortion of market prices. The evidence highlights the concern that analysts may not appreciate the valuation implications of conservative accounting which could inhibit price discovery.

Recent corporate governance guidelines have focused on the structure of the board of directors, with little recognition of the importance of director attendance at board and committee meetings. Director attendance is vital as prior studies show that director absences result in weaker monitoring of management and lower firm performance. This study examines whether directors learn from the attendance behavior of their board colleagues, thereby magnifying the scope and potential consequences of good or poor attendance practices. We find that director attendance is significantly positively related to their board colleagues attendance, including colleagues in the same firm and colleagues in other firms where the director holds other directorships. For policymakers, these results indicate that ongoing attention needs to be paid to the attendance practices of directors, with intervention required to ensure poor attendance practices do not become contagious.

This paper reveals both fundamental and non-fundamental factors play an important role in analysts’ target price formation. Analysts’ forecasts of short-term earnings and long-term growth are shown to be important explanatory variables for target prices; equally, the following salient non-fundamental factors are also shown to explain target price levels and especially target price biases: the 52-week high price and recent market sentiment. Here, increases in the 52-week high and market sentiment measures of one standard deviation correspond to increases in positive target price bias of 4.8% and 14.7%, respectively. Initially our analysis is constrained to analysts who provide long-term growth forecasts, however, our findings are robust to the removal of this constraint and the broader set of analysts. Our analysis reveals that analysts place greater weight on these non-fundamental factors in settings with greater task complexity and/or resource constraints, and when they rely on valuation heuristics as opposed to more rigorous valuation methodology, and that this greater weight is associated with increased optimistic bias. Finally, our results show that analysts’ target prices are useful in predicting future stock returns beyond earnings forecasts and commonly used risk proxies. However, in an internally consistent fashion, the informativeness of target prices for future returns is significantly reduced when greater weight is placed on either the 52-week high or recent market sentiment in the target price formation process.

We investigate whether analysts’ long-term growth (LTG) forecasts are a signal of analyst effort to better understand the future prospects of firms, which is reflected in the long-term profitability of their stock recommendations. We develop a one-year-ahead LTG forecast likelihood score and execute a trading strategy that generates average abnormal returns of 2.9% per annum over our sample period (1995–2005). Furthermore, in out-of-sample testing without portfolio rebalancing during the 2006–2011 period, our trading strategy earns abnormal returns of 2.5% per annum. In summary, this study illustrates previously undocumented long-term benefits accruing to investors from the information inherent in analyst LTG forecasts.

We examine the persistence in analysts’ relative earnings forecast accuracy. When analysts are ranked into forecast accuracy quintiles, calculated over all the firms they cover in each year, we find that 52% (45%) of superior (inferior) analysts, i.e. analysts in the lowest (highest) quintile, remain in this quintile in the subsequent period. We show that a variable we develop and denote as forecasting complexity, i.e. the extent to which analysts’ earnings forecasts vary when predicting a firm’s earnings, is important in explaining variation in the persistence of the relative forecast accuracy of analysts. When we control for forecasting complexity, the probability of analyst relative forecast accuracy to persist is reduced by about half. This reduced persistence, however, measures true forecasting ability. When we form portfolios using recommendations of analysts identified as superior in two consecutive periods, controlling for forecasting complexity, we find significant abnormal returns after adjusting for the Fama–French and momentum factors.

We examine whether financial analysts understand the valuation implications of unconditional accounting conservatism when forecasting target prices. While accounting conservatism affects reported earnings, conservatism per se does not have an effect on the present value of future cash flows. We examine whether analysts adjust for the effect of conservatism included in their earnings forecasts when using these forecasts to estimate target prices. We find that signed target price errors (actual minus forecast) have a significant positive association with the degree of conservatism in forward earnings, suggesting that target prices are biased due to accounting conservatism. Cross-sectional analysis suggests that more sophisticated analysts and superior long-term forecasters adjust for conservatism to a greater extent than other analysts. In additional analyses, we explore the mechanism through which conservatism leads to bias in target prices. We first show that analysts’ earnings forecasts are negatively associated with the degree of conservatism, i.e., analysts include the effect of unconditional conservatism in their earnings forecasts. Based on alternative earnings-based valuation models that analysts may use, our evidence suggests that analysts fail to appropriately adjust their valuation multiple for the effect of conservatism included in their earnings forecasts when using these forecasts to derive target prices. As a consequence, we find that, for extreme changes in conservatism, the bias in analysts’ target prices due to conservatism leads to a distortion of market prices. The evidence highlights the concern that analysts may not appreciate the valuation implications of conservative accounting which could inhibit price discovery.

Conservatism in earnings does not have a direct impact on the present value of future cash flows. This paper examines whether financial analysts correctly undo the effect of accounting conservatism incorporated in their own earnings forecasts in arriving at their target price forecasts. Based on prior findings, we consider alternative valuation models/heuristics that may be used by analysts to estimate target prices, e.g. the forward P/E and the PEG ratio. Our evidence suggests that analysts fail to fully undo the effect of accounting conservatism embedded in their forecasts of earnings and earnings growth when deriving their target price forecasts. More sophisticated analysts undo the effect of conservatism to a greater extent than other analysts, although their target price forecasts also exhibit conservatism-induced bias. In contrast, the market on average appears to correctly unravel the conservatism in future earnings when pricing securities. However, for extreme levels of conservatism, our evidence suggests that the under/over-statement of target prices leads to a distortion of market prices.

This paper reveals that in addition to fundamental factors, the 52-week high price and recent investor sentiment play an important role in analysts’ target price formation. Analysts’ forecasts of short-term earnings and long-term earnings growth are shown to be important explanatory variables for target prices; equally, the 52-week high price and recent investor sentiment are also shown to explain target price levels and especially target price biases. Our analysis additionally reveals that analysts place greater weight on these two non-fundamental factors in settings with greater task complexity and to some extent in those with greater resource constraints. Conversely, on balance, the results suggest that this increased reliance does not translate into an increased impact per unit of each non-fundamental factor on forecast bias. Finally, our results show that target prices are useful in predicting future stock returns beyond earnings forecasts and commonly used risk proxies. However, in an internally consistent fashion, the informativeness of target prices for future returns is significantly reduced when greater weight is placed on either the 52-week high or recent investor sentiment in the target price formation process.

We examine how analysts' conflicting incentives to be either accurate or optimistic affect their choice to generate stock recommendations with rigorous valuation models or growth-based heuristics. Consistent with prior research the average analyst recommendation is negatively associated with rigorous valuation models and positively associated with growth-based heuristics, we document that these associations are weakest for the most accurate analysts and strongest for the least accurate analysts. We also find evidence consistent with consistency between recommendations and valuation models underlying the positive future returns from trading on the most accurate analysts' recommendations. Our results are consistent with reputation incentives to be accurate mitigating the use of optimistic growth-based models in generating stock recommendations.

Apparently there are some priceless things in life that money can buy. The year is 2008, the Treasury Department is reporting record-setting federal budget deficits, and almost four years have lapsed since the enactment of the American Jobs Creation Act of 2004 (P.L. 108-357, 118 Stat. 1418 (2004)).1 The Jobs Act granted U.S. multinational corporations (MNCs) a ‘‘one-time’’ tax break to repatriate billions of dollars in unremitted earnings from their foreign subsidiaries almost U.S. tax free. The critics claim that few jobs were created by the tax amnesty legislation, and the repatriated earnings were primarily expended on paying down corporate debt and repurchasing company shares.2 This article takes a closer look behind the scenes at the financial statements of America’s largest firms. These firms had significant amounts of permanently reinvested earnings (PRE) stockpiled away before the Jobs Act, as identified by prior researchers on this topic, Albring et al. (2005) and Sullivan (2006).3 Our

We examine the persistence in analysts’ relative earnings forecast accuracy. When analysts are ranked into forecast accuracy quintiles, calculated over all the firms they cover in each year, we find that 52% (45%) of superior (inferior) analysts, i.e., analysts in the lowest (highest) quintile, remain in this quintile in the subsequent period. We show that a variable we develop and denote as forecasting complexity, i.e., the extent to which analysts’ earnings forecasts vary when predicting a firm’s earnings, is important in explaining variation in the persistence of the relative forecast accuracy of analysts. When we control for forecasting complexity, the probability of analyst relative forecast accuracy to persist is reduced by about half. This reduced persistence, however, measures true forecasting ability. When we form portfolios using recommendations of analysts identified as superior in two consecutive periods, controlling for forecasting complexity, we find significant abnormal returns after adjusting for the Fama-French and Momentum factors.

This article reviews the tax recognition issue associated a firm’s abandonment of, or federal tax disqualification from, using the “last-in, first-out” method of inventory accounting in light of the recent Securities and Exchange Commission movement towards requiring American publicly traded corporations to report under International Financial Reporting Standards. The article pays particular attention to the significant LIFO reserves accumulated in the manufacturing, chemical, automotive and energy sectors, and conducts a tax policy analysis of the ramifications of such a conversion, and suggests possible solutions such as the elimination of the Internal Revenue Code’s conformity requirement and/or extended deferral of gain recognition.

ABSTRACT: Prior research has shown improvements in analysts’ forecast accuracy around various events (e.g., new disclosure regulations or cross-listings), but these studies do not consider a change in the composition and ability of the analysts providing forecasts over time. By studying foreign firms cross-listing on U.S. stock exchanges, we find that analyst composition changes by more than 50 percent during the three-year period around cross-listing. We show that cross-listing is associated with a shift away from analysts who are less accurate forecasters and toward analysts who are more accurate forecasters. This shift in analyst composition accounts for a significant improvement, of 9.5 percent, in analyst forecast accuracy. In addition, we document that changes in both analyst ability and public information disclosure affect analyst forecast accuracy around cross-listing. Our results indicate that researchers should control for changes in analyst composition and ability when measuring the impact of specific events on analyst forecast accuracy.

In this report, the authors discuss the tax and policy issues associated with repatriation under the American Jobs Creation Act of 2004, P.L. 108-357, 118 Stat. 1418 (2004) (Jobs Act), and conduct an extensive survey of the financial statements of the top 81 repatriating multinational corporations. The author's findings suggest that the rate of repatriation by firms was extremely sensitive to the tax burden associated with repatriation, and the rate was further influenced by industry sector, and the amount of permanently reinvested earnings located in low-tax jurisdictions overseas. The authors' data results also evidence that firms repatriated qualifying dividends under section 965 at a U.S. effective tax rate lower than the 5.25 percent initially discussed in literature, and suggest that the amount of permanently reinvested earnings and cash holdings of firms only increased after repatriation.

This study examines managements' decision to issue earnings growth guidance and assesses whether financial analysts' change their long-term earnings growth expectations in response to the guidance. We find that management offers long-term forecasts only when it is strategic to do so, often when short-term news is bad, inducing a significant upward bias in the forecasts. We also find that analysts are influenced by management long-term forecasts; in fact, the findings suggest that they are overly influenced, in that their forecast error increases. This finding sheds new light on the over-optimism hypothesis in analysts' long-term earnings growth forecasts, suggesting the bias could be management induced. Lastly we find that not all analysts are fooled, however, and how they use the information to form price targets varies widely.

Prior research documents a large dispersion in long-term earnings growth forecasts among financial analysts covering the same stock. This suggests that while analysts believe long-term earnings growth is predictable, they face significant uncertainty when estimating it. This thesis examines the effect long-term earnings growth forecast dispersion has on the firm that receives long-term earnings growth forecasts, and investors who follow analysts’ stock recommendations based on valuations that incorporate long-term earnings growth. The first essay examines determinants of voluntary earnings growth guidance by management, and investigates analysts’ reactions to the guidance. The second essay examines trading strategies based on superior analysts’ long-term earnings growth forecasts. The results of the first essay indicate that there is pervasive upward bias in managers’ earnings growth guidance. As a result of this bias, managers are more likely to issue earnings growth forecasts in years of negative short-term earnings surprises and when analysts have low initial long-term earnings growth forecasts. The finding that managements’ earnings growth forecasts primarily convey good news is in contrast to the generally negative nature of management short-term earnings guidance, and suggests that different incentives drive firms’ disclosure of different financial information. Moreover, analysts respond to managements’ earnings growth guidance by increasing their long-term earnings growth forecasts. This finding sheds new light on the over-optimism hypothesis in analysts’ long-term earnings growth forecasts, suggesting the bias could be management induced. However, with regard to analysts’ response, the findings suggest that analysts sacrifice precision in long-term earnings growth forecasts for deliberate upward bias. This bias is not subject to ex post scrutiny and is designed to maintain or increase analysts’ target prices, even though short-term earnings may warrant a lower target price. Results in the second essay show a contemporaneous association between long-term earnings growth forecast accuracy, one-year ahead earnings forecast accuracy, and stock recommendation profitability. Despite these results, a model that predicts the profitability of future stock recommendations based on the analyst’s historical one-yea ahead earnings forecast accuracy and long-term earnings growth forecast accuracy, is not found.

This study examines determinants of voluntary earnings growth guidance by management, and investigates analysts' reactions to the guidance. We find that there is pervasive upward bias in managers' earnings growth guidance, and as a result mangers are more likely to issue earnings growth forecasts in years of negative short-term earnings surprises and when analysts have low initial earnings growth expectations. The finding that managements' earnings growth forecasts primarily convey good news is in contrast to the generally negative nature of management short-term earnings guidance and suggests that different incentives drive firms' disclosure of different financial information. We also find that analysts respond to managements' earnings growth guidance by increasing their earnings growth forecasts. However, we find that analysts trade off precision in their earnings growth forecasts for deliberate upward bias that is not subject to ex post scrutiny, to maintain, or increase, their target prices.