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Fundamental Valuation

What fundamental measures of business success best indicate the value of individual stocks and the aggregate stock market? How can investors apply these measures to estimate valuations and identify misvaluations? These blog entries address valuation based on accounting fundamentals, including the conventional value premium.

“It’s the P/E, Stupid!”

Is there a relationship between investor risk-aversion, as indicated by the aggregate U.S. stock market price-earnings ratio (P/E), and level of public satisfaction with the performance of the President? In their December 2008 paper entitled “Speculating on Presidential Success: Exploring the Link between the Price-Earnings Ratio and Approval Ratings”, Tomasz Wisniewski, Geoffrey Lightfoot and Simon Lilley examine the relationship between aggregate stock market P/E and the surveyed level of public approval of the current President. Using quarterly P/E for the S&P Composite Stock Price Index derived from Robert Shiller’s long-run dataset and Gallup presidential approval survey data from the beginning of 1950 through the third quarter of 2007 (231 observations), they conclude that: Keep Reading

Kicking the Body of the Fed Model

As with many indicators, the Fed Model is presently so far out of multi-generational bounds that reversion seems hopeless. Is the body still warm, or ready for burial? Using the daily S&P 500 earnings yield (E/P) during 1/2/90-12/4/08, as calculated from the historical S&P 500 index and 12-month trailing Standard & Poor’s earnings data, and contemporaneous daily 10-year Treasury note (T-note) yields, we find that… Keep Reading

Long-term Market Timing Model Flyoff

Do long-term stock market timing models work? If so, which type works best? In their October 2005 paper entitled Timing is Everything: A Comparison and Evaluation of Market Timing Strategies, Chris Brooks, Apostolos Katsaris and Gita Persand investigate the profitability of several timing models over a very long sample of S&P 500 index returns. Specifically, they test the timing power of: (1) the ratio of the long-term Treasury bond yield to the stock dividend yield; (2) the spreads between the stock earnings yield and the yields on either the three-month Treasury bills (T-bills) or the 10-year Treasury notes (T-notes); (3) a model for predicting when bear markets will occur based on the spread between T-note and T-bill yields; and, (4) an approach for predicting market turning points based on speculative bubbles. Timing signals trigger binary switching between stocks and T-bills. Using monthly stock return and model parameter data from January 1871-December 1926 for initial model calibration and January 1927-August 2003 for model testing and recalibration (a total of 1,592 months), they find that: Keep Reading

Darlings of the Dow Strategy

A reader asked:

“Have you tested the Darlings of the Dow strategy developed by Larry Williams? He has modified his original strategy several times, and I wonder whether he made revisions because of new insight or because the original strategy proved not much better than the five cheapest Dogs of the Dow. What I find interesting is his timing of the Darlings with Sy Harding’s MACD timing method and his buying the Dow Jones Utilities for the remainder of the year.”

The original Darlings of the Dow strategy employs fundamentals to select the five most undervalued stocks in the Dow Jones Industrials Average and times entries and exits seasonally (enter in October and exit in April). The revised version chooses other entry and exit dates. To evaluate the strategy, we assume that the trading dates/returns for Darlings of the Dow stocks are as listed by Larry Williams and that returns while out of the Darlings are the adjusted returns for the iShares Dow Jones US Utilities (IDU). As benchmarks, we calculate returns based on adjusted closing values for S&P Depository Receipts (SPY) over the same intervals and average 90-day Treasury bill (T-bill) yields as an alternative to IDU returns. We use a test period of 2002-2007 (10/28/02-9/13/07) that is out-of-sample and post-publication with respect to the original strategy. We find that: Keep Reading

Mispricing Versus Liquidity for Earnings Uncertainty

Does the market efficiently bound the mispricings of stocks within the costs of exploiting the mispricings? In their August 2008 paper entitled “Mispricing and Costly Arbitrage”, Ronnie Sadka and Anna Scherbina explore the difficulty of exploiting short-term mispricings of stocks derived from analyst disagreement about future earnings (with mispricing likely due to very pessimistic analysts withholding their views). Using stock price and earnings forecast data for a broad sample of stocks over the period January 1983 through August 2001, they conclude that: Keep Reading

Perspectives on Earnings Growth Forecasts

How should investors view corporate earnings estimates as determinants of stock valuations? Are analyst and management forecasts of any value? Is high growth inherently unsustainable? Is the source of growth important? In his June 2008 paper entitled “Growth and Value: Past Growth, Predicted Growth and Fundamental Growth”, Aswath Damodaran examines the patterns and broad lessons of research on growth forecasts. Using results from past studies and new analyses of earnings data for 1997-2007, he concludes that: Keep Reading

An International Test of Common Stock Return Indicators

Do any indicators systematically predict stock returns across global equity markets? In his June 2008 paper entitled “Predicting Global Stock Returns”, Erik Hjalmarsson tests the power of four common indicators (dividend-price ratio, earnings-price ratio, short interest rate and term spread) to predict stock returns for markets in 24 developed and 16 emerging economies. Using a very large dataset encompassing 20,000 monthly observations of returns and indicators ranging as far back as 1836, he concludes that: Keep Reading

Is ValueEngine’s Stock Market Mispricing Summary Predictive?

A reader suggested that we evaluate the usefulness of ValueEngine, self-described as “a stock valuation and forecasting service founded by Ivy League finance academics” utilizing “the most advanced quantitative techniques and analysis available.” ValueEngine offers a limited archive (20 weeks) of their free weekly newsletter that includes a “Summary of VE Stock Universe” within a section entitled “ValueEngine’s Market Overview.” This summary states the percentages of stocks undervalued and overvalued and the percentages of stocks undervalued and overvalued by at least 20%. If these summaries are meaningful, the net levels of mispricing they indicate should be to some degree predictive of future stock market behavior. Using the weekly mispricing summaries for 5/11/07-6/20/08 (a total 58 summaries, with none listed for 1/25/08) and contemporaneous weekly S&P 500 index data, we find that: Keep Reading

A Few Notes on The Halo Effect

In his 2007 book, The Halo Effect …and Eight Other Business Delusions That Deceive Managers, Phil Rosenzweig argues for distinguishing carefully between sentiments (halos) derived principally from past bottom-line performance and fundamentals independent from that performance when assessing the excellence of companies and managers. Sentiments are essentially opinions expressed via “managers’ ex post facto recollections, company statements, and articles from the business press.” The distinction between sentimental and fundamental is important for investors/traders, as are his related conclusions about the value of experts and the inherent unpredictability of firm performance. Based on his review of prominent past studies of business excellence, he finds that: Keep Reading

Regulations Suppressing Analysts’ Earnings Optimism?

Have Regulation FD (Fair Disclosure) of 2000 and the Global Analyst Research Settlements of 2002 effectively removed incentives for sell-side analysts to curry favor with their own and covered company management teams by issuing inflated earnings forecasts? In their May 2008 paper entitled “Conflicts of Interest and Analyst Behavior: Evidence from Recent Changes in Regulation”, Armen Hovakimian and Ekkachai Saenyasiri investigate whether these two regulatory actions reduced the average analyst earnings forecast bias found in prior studies. Based on the annual earnings forecasts of sell-side analysts and associated actual annual earnings over the period 1984-2006, they conclude that: Keep Reading

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