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I seek to liberate investors from the chains of borrowed opinions by teaching metric awareness that leads to the formation of your own opinions. I am a retail investor that gathers, processes and analyzes significantly more data than average. I share that data in my articles. I let the data do... More
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  • From The Ivory Tower - Part Four 0 comments
    Jun 25, 2014 7:34 PM

    This posts continues with my notes started in part one. These are the first notes where I have provided bold font on the key news found in the research.

    Effect of Reputation on the Credibility of Management Forecasts
    Amy P. Hutton, Phillip C. Stocken
    statistika21.files.wordpress.com/2013/03...

    We examine the effect of firm forecasting reputation on investors' reaction to management earnings forecasts. We construct a measure of forecasting reputation that reflects prior forecast accuracy and frequency. We hypothesize and find, first, that investors are more responsive to management forecast news when a firm has built a forecasting reputation. Second, we examine forecasts containing extreme earnings news, a setting where investors are expected to find reputation more salient, and find investors are more responsive to these forecasts when the firm has a reputation. Third, when a firm has a forecasting reputation, investors' reaction at the management forecast date largely preempts their reaction at the earnings announcement date. Consequently, managers of firms with a reputation have their forward-looking information reflected in stock prices more promptly. Fourth, to establish why all firms do not build a forecasting reputation given the benefits of having one, we show that it is costly to build a reputation because investors are less responsive to unexpected earnings news when reported earnings fail to reach the management forecast.

    In PA Williams' (The Relation Between a Prior Earnings Forecast by Management and Analyst Response to a Current Management Forecast. 1996), the primary antecedent to our paper, considers how financial analyst responsiveness to a management earnings forecast varies with the usefulness of a previous management forecast. She finds that analyst responsiveness to good news forecasts, which typically are regarded as less credible, varies with the usefulness of a prior good news forecast, whereas analyst responsiveness to bad news forecasts does not vary with the usefulness of the prior forecast.

    Chen, Francis and Jiang (Investor learning about analyst predictive ability 2005) studied how investors learn about analyst forecasting ability. They model analysts as being disinterested information providers. Consistent with this view, they find that investors update their beliefs about analyst ability in a Bayesian fashion in the sense that they weight analyst quarterly earnings forecasts more heavily than their prior beliefs when analyst forecasts are more accurate and frequent.

    First Call provides a classification of the type of management forecast: point, range, one-sided directional, or confirming statements. Approximately 68 percent of the management forecasts included in our sample are range forecasts, 26.6 percent are point forecasts, and only a little over 5 percent are one-sided directional or confirming forecasts.

    To assess whether the management forecast reveals good, bad, or confirming news, we consider the forecast relative to the prevailing median analyst consensus earnings estimate. If the management forecast is higher than the prevailing median analyst consensus estimate, then we classify the forecast as being good news; if it is lower, then we classify the forecast as being bad news; and if it is equal to the prevailing median analyst consensus estimate, then we classify the news as confirming. Approximately 46 percent of the management forecasts convey bad news, approximately 37 percent convey good news, and approximately 17 percent are confirming.

    We define management forecast errors (MFE) as realized earnings per share less the management forecast of earnings scaled by lagged stock price on the third day after the prior period's earnings announcement. For our sample, the mean management forecast error is significantly negative implying that management forecasts are optimistic on average. This observation contrasts earlier work documenting that management forecasts are unbiased on average (McNichols 1989; Frankel et al. 1995; Kasznik 1999). Moreover, bad news forecasts are significantly more optimistic than good news forecasts, which is inconsistent with the view that bad news should be more credible than good news.

    We show investors react more negatively to missed good news than to missed bad news forecasts.

    Citations with interest titles in the above research:
    BB Ajinkya and MJ Gift. Corporate Managers' Earnings Forecasts and Symmetrical Adjustments of Market Expectations. Journal of Accounting Research, Vol. 22, No. 2 (1984)
    SP Baginski, EJ Conrad and JM Hassell. The Effects of Management Forecast Precision on Equity Pricing and on the Assessment of Earnings Uncertainty. The Accounting Review, Vol. 68, No. 4 (1993).
    Q Chen, J Francis and W Jiang. Investor learning about analyst predictive ability. Journal of Accounting and Economics, Vol. 39 (2005)
    M Coller and TL Yohn. Management Forecasts and Information Asymmetry: An Examination of Bid-Ask Spreads. Journal of Accounting Research, Vol. 35, No. 2 (1997)

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