Analyst Long-Term Growth Forecasts, Accounting Fundamentals and Stock Returns

Analyst Long-Term Growth Forecasts, Accounting Fundamentals and Stock Returns
Author: Gregg S. Fisher
Publisher:
Total Pages: 47
Release: 2017
Genre:
ISBN:

We decompose consensus analyst long-term growth forecasts into a hard growth component that captures accounting information (asset and sales growth, profitability and equity dilution) and an orthogonal soft growth component. The soft component does not forecast future returns, and the hard component does forecast future returns, but in a perverse way. Specifically, stocks with accounting information indicating favorable long-term growth forecasts tend to realize negative future excess returns. This and other evidence we present is consistent with biased long-term growth forecasts generating stock mispricing.

Do Financial Analysts' Long-Term Growth Forecasts Matter? Evidence from Stock Recommendations and Career Outcomes

Do Financial Analysts' Long-Term Growth Forecasts Matter? Evidence from Stock Recommendations and Career Outcomes
Author: Boochun Jung
Publisher:
Total Pages: 49
Release: 2015
Genre:
ISBN:

Prior literature refers to economic incentives to generate investment banking business and trading commissions as explanations for analyst publication of forecasts of firms' long-term earnings growth (LTG). Prior research also documents wildly optimistic LTG forecasts and a negative relation between LTG forecasts and subsequent excess returns. Thus, the literature portrays analysts' LTG forecasts as nonsensical from a valuation perspective. We introduce and investigate a new perspective on the value-relevance of analyst publication of LTG forecasts. We hypothesize that analysts issuing LTG forecasts signal relatively high effort and ability in developing perspective of the subject firms' long-term prospects. Consistent with this hypothesis, we find that the stock market responds more strongly to the stock recommendation revisions of analysts who publish accompanying LTG forecasts. In addition, we hypothesize and find that analysts issuing LTG forecasts are less likely to leave the profession or move to smaller brokerage houses. Consistent with Reg. FD's intention to restrict analyst access to insider information and promote fundamental analysis of the valuation implications of firms' long-term prospects, we find that post-Reg. FD observations drive most of our results. Overall, we identify previously undocumented benefits accruing to analysts who publish LTG forecasts.

Diagnostic Expectations and Stock Returns

Diagnostic Expectations and Stock Returns
Author: Pedro Bordalo
Publisher:
Total Pages: 0
Release: 2017
Genre:
ISBN:

We revisit La Porta's (1996) finding that returns on stocks with the most optimistic analyst long term earnings growth forecasts are substantially lower than those for stocks with the most pessimistic forecasts. We document that this finding still holds, and present several further facts about the joint dynamics of fundamentals, expectations, and returns for these portfolios. We explain these facts using a new model of belief formation based on a portable formalization of the representativeness heuristic. In this model, analysts forecast future fundamentals from the history of earnings growth, but they over-react to news by exaggerating the probability of states that have become objectively more likely. Intuitively, fast earnings growth predicts future Googles but not as many as analysts believe. We test predictions that distinguish this mechanism from both Bayesian learning and adaptive expectations, and find supportive evidence. A calibration of the model offers a satisfactory account of the key patterns in fundamentals, expectations, and returns.

Forecasting Economic Fundamentals and Expected Stock Returns Using Equity Market Order Flows

Forecasting Economic Fundamentals and Expected Stock Returns Using Equity Market Order Flows
Author: Aditya Kaul
Publisher:
Total Pages: 29
Release: 2013
Genre:
ISBN:

This paper examines the information content of two different measures of aggregate equity-market order flow for future macroeconomic fundamentals and expected stock market returns. The first measure, the cross-sectional average of individual stock order flows, predicts future growth rates for industrial production and real GDP, but not for corporate earnings. The second measure, the difference between the average order flow for big stocks and the average order flow for small stocks, has strong forecast power for industrial production and real GDP, as well as corporate earnings, up to four quarters ahead. The significance of the two order flow-based measures is robust to controls for common equity pricing factors. This suggests a role for aggregate order flows in predicting stock returns. We show that a positive shock to the second factor, the order flow differential, forecasts higher returns for ten size sorted portfolios and greater market and size premiums in the subsequent quarter, even after accounting for a host of variables including the common return factors, experts' earnings growth forecasts, default and term spreads, new equity capital, and marketwide liquidity. These findings are consistent with a world where aggregate order flow brings together dispersed information from heterogeneously informed investors.

Estimating the Cost of Capital Implied by Market Prices and Accounting Data

Estimating the Cost of Capital Implied by Market Prices and Accounting Data
Author: Peter Easton
Publisher: Now Publishers Inc
Total Pages: 148
Release: 2009
Genre: Business & Economics
ISBN: 1601981945

Estimating the Cost of Capital Implied by Market Prices and Accounting Data focuses on estimating the expected rate of return implied by market prices, summary accounting numbers, and forecasts of earnings and dividends. Estimates of the expected rate of return, often used as proxies for the cost of capital, are obtained by inverting accounting-based valuation models. The author describes accounting-based valuation models and discusses how these models have been used, and how they may be used, to obtain estimates of the cost of capital. The practical appeal of accounting-based valuation models is that they focus on the two variables that are commonly at the heart of valuations carried out by equity analysts -- forecasts of earnings and forecasts of earnings growth. The question at the core of this monograph is -- How can these forecasts be used to obtain an estimate of the cost of capital? The author examines the empirical validity of the estimates based on these forecasts and explores ways to improve these estimates. In addition, this monograph details a method for isolating the effect of any factor of interest (such as cross-listing, fraud, disclosure quality, taxes, analyst following, accounting standards, etc.) on the cost of capital. If you are interested in understanding the academic literature on accounting-based estimates of expected rate of return this monograph is for you. Estimating the Cost of Capital Implied by Market Prices and Accounting Data provides a foundation for a deeper comprehension of this literature and will give a jump start to those who have an interest in these topics. The key ideas are introduced via examples based on actual forecasts, accounting information, and market prices for listed firms, and the numerical examples are based on sound algebraic relations.

Market Response to Revisions in Analysts' Future Years' Earnings Forecasts

Market Response to Revisions in Analysts' Future Years' Earnings Forecasts
Author: Gregory Alan Sommers
Publisher:
Total Pages: 194
Release: 2002
Genre:
ISBN:

Abstract: Questions have been raised in the business press and prior academic research about future years' earnings forecast credibility, particularly long-term growth. This paper documents the market response to revisions in analysts' earnings forecasts for the next year and long-term growth (collectively "future years' earnings"). First, I show there is information content in future years' earnings forecast revisions as evidenced by changes in return volatility and volume at their release. Second, there is a direct market response to the magnitudes of the revisions in the next years' earnings forecasts and to upward revisions in long-term growth forecasts as evidenced by the coefficient relating the unexpected returns to the unexpected portion of the revisions. Finally, I find that investors use the next year earnings forecasts interpret the expected persistence of current year earnings forecast revisions. This is evidenced by increases (decreases) in the coefficient relating unexpected returns to the current year earnings forecast revisions when the next year earnings forecast revision is in the same (opposite) direction. This study documents market response to future years' earnings forecast revisions and indicates that they affect how investors respond to the revisions in current year earnings forecasts.