Academic journal article Quarterly Journal of Finance and Accounting

The Value Line Timeliness Ranking and the Equivalence of Analyst Forecasts and Market Expectations

Academic journal article Quarterly Journal of Finance and Accounting

The Value Line Timeliness Ranking and the Equivalence of Analyst Forecasts and Market Expectations

Article excerpt

Introduction

The Value Line Enigma is so named to describe researchers' inability to reconcile the seemingly superior investment performance of Value Line's Timeliness rank with market efficiency (Copeland and Mayers 1982; Black 1973). A stock's Timeliness is the output of a quantitative model incorporating ex post data on earnings and stock prices in order to project 6-12 months ahead relative stock price performance. The scale ranges from one to five, with stocks ranked 1 (5) having the best (worst) relative prospects. Independent of Timeliness, Value Line's team of fundamental research analysts produces ex ante forecasts of stock prices and 23 financial variables for each of the stocks in its coverage universe. Scholarly research in equity valuation and implied expected returns has incorporated Value Line fundamental forecasts in valuation models on the maintained assumption of equivalence between analyst forecasts and market expectations. I investigate this equivalence in the context of valuation errors across Timeliness rank. I argue that a stock's Timeliness reflects the probable magnitude and direction of divergence between market expectations and analyst forecasts. The evidence suggests that equivalence holds for stocks of average Timeliness and that it does not hold for stocks above or below average Timeliness.

The question is important for research in equity valuation and implied expected returns, because inferences can be confounded when equivalence breaks down. Heinrichs et al. (2013), Devos et al. (2009), Courteau et al. (2001) and others compute stocks' intrinsic values with Value Line analyst forecasts as model inputs, but these valuations are biased predictors of stock price if the forecasts do not correspond to investor expectations. Botosan et al. (2011) evaluate alternative measures of implied expected return in terms of their correlation with firm-specific risk proxies that depend on stock price (e.g., the ratio of book-to-market value), and Brav et al. (2005) test asset pricing theories on the basis of correlations between implied returns and stock price-based risk measures. Because stock price responds quickly to new information and because both implied returns and measures such as book-to-market value depend on stock price, an observed correlation between them can be attributed to divergent expectations during the time in which analysts are working to update their forecasts. This correlation will be observed even when equivalence prevails on average in the cross section, and it calls into question the validity of the inferences reached in these and similar studies.

Value Line (hereafter, VL) publishes quarterly updates of analysts' fundamental forecasts for each of approximately 1,700 companies in its coverage universe; hence, there can be a lag of up to three months from, for example, the date of a quarterly earnings release to the date of its incorporation in updated forecasts. Analyst forecasts are stale when they do not incorporate all relevant information, and it is generally the case that at any time some forecasts are stale. A stock's Timeliness rank factors in recent earnings and stock price news, and stocks that have experienced recent positive (negative) news are more likely to be rated above (below) average. Because Timeliness is updated weekly, a stock's rank often reflects more recent information than do analyst forecasts. Consequently, market expectations most likely differ from analyst forecasts for stocks rated above or below average Timeliness. Further, because the magnitude and direction of divergence are related to Timeliness, valuations based on stale forecasts manifest in a systematic pattern of valuation errors across Timeliness ranks. Among average Timeliness stocks, analyst forecasts reflect recent news, and valuation errors tend to be near zero. Among stocks above (below) average Timeliness, stale forecasts tend not to reflect recent good (bad) news, and the valuations based on these forecasts tend to be biased downward (upward) vis-a-vis actual stock prices. …

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