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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.

Revisiting Performance of Piotroski’s FSCORE

Is Piotroski’s FSCORE really as effective at picking stocks as indicated in the original study, which screens stocks with high book-to-market ratios to isolate those that will eventually provide high returns? In their April 2014 paper entitled “Implementability of Trading Strategies Based on Accounting Information: Piotroski (2000) Revisited”, Sohyung Kim and Cheol Lee re-examine the FSCORE testing methodology. Their broader goal is to investigate the effect of a problematic research approach used in many accounting-based studies. Specifically, they evaluate the difference in investment outcomes between:

  • Accounting studies that typically accumulate returns for individual stocks starting three or four months after their respective fiscal year-ends.
  • Finance studies that synchronize return accumulation with a common annual starting date (regardless of the fiscal year-ends of individual firms) via periodically reformed portfolios with a specified weighting scheme (such as equal weighting).

Accounting study assumptions may confound real-time position weighting due to lack of timely information on how many stocks should be in the portfolio, thereby incorporating look-ahead bias. The study replicates the original Piotroski methodology with equal position weighting, and then makes adjustments to synchronize return calculations by each year reforming a hedge portfolio that is long (short) the equally weighted stocks with high (low) FSCOREs based on a common starting date and most recently available firm fundamentals. Using monthly data for a broad sample of U.S. common stocks with enough information to calculate FSCOREs during 1976 through 2007, they find that:

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Value in Simplicity?

Does compounding rules tend to improve the performance of stock-picking strategies? In the October 2014 draft of their paper entitled “Does Complexity Imply Value, AAII Value Strategies from 1963 to 2013”, Wesley Gray, Jack Vogel and Yang Xu compare 13 stock strategies labeled as “Value” by the American Association for Individual Investors (AAII) to each other and to a simple “low-price” value strategy. The simple strategy each year selects the tenth of stocks with the highest Earnings Before Interest, Taxes, Depreciation and Amortization-to-Total Enterprise Value ratios (EBITDA/TEV), excluding financial firms. To ensure liquidity, they focus on stocks with market capitalizations above the NYSE 40th percentile. To ensure real-time availability of inputs, they lag firm accounting data. To assess performance consistency, they consider three subperiods: July 1963 through December 1980; January 1981 through December 1996; and, January 1997 through December 2013. Because portfolios are equally weighted, they include the S&P 500 equal-weight total return index (S&P 500 EW) as a benchmark. Using stock price and firm accounting data for a broad sample of U.S. common stocks during July 1963 through December 2013, they find that: Keep Reading

Retirement Allocation Strategy Informed by P/E10

Does adjusting an asset allocation retirement glidepath according to a stock market valuation metric such as Shiller’s cyclically adjusted price-earnings ratio (CAPE ratio or P/E10) improve the outcome? In their September 2014 paper entitled “Retirement Risk, Rising Equity Glidepaths, and Valuation-Based Asset Allocation”, Michael Kitces and Wade Pfau investigate the interaction of pre-determined allocation glidepaths and P/E10 valuation based on long-run U.S. historical data. They consider the following strategy alternatives:

  • Fixed equity allocations of either 45% or 60%.
  • Declining (accelerated declining) equity glidepaths that start retirement at 60% stocks and reduce the allocation by 1% (2%) per year.
  • Rising (accelerated rising) equity glidepaths that start retirement at 30% stocks and increase the allocation by 1% (2%) per year.
  • A standalone dynamic valuation-based strategy with baseline 45% equity, raised (lowered) to 60% (30%) at the beginning of any year for which P/E10 is less than (greater than) 67% (133%) of its inception-to-date median. (See the chart below.)
  • Unbounded and bounded combinations of declining or rising glidepaths and the dynamic valuation-based strategy, adding (subtracting) 15% from the equity glidepath at the beginning of any year for which P/E10 indicates undervaluation (overvaluation). Bounded combinations constrain equity allocation to a minimum 30% and a maximum 60%.

They consider both short-term bills (six months to a year) and long-term bonds (10-year) as complements to equities. They use overlapping 30-year intervals to approximate retirement outcomes. They focus on worst-case maximum sustainable real (inflation-adjusted) withdrawal rate over the 30-year retirement interval as the main strategy performance metric. Withdrawals occur at the beginning of each year, with the residual portfolio then rebalanced to target allocations. They assume withdrawals pay the taxes. Using Robert Shiller’s monthly data for U.S. stock market returns, associated P/E10, short-term bill yields (six-month commercial paper/one-year U.S. Treasury notes) and long-term bond yields (10-year U.S. Treasury notes or equivalent) during 1871 through 2013, they find that: Keep Reading

Cash Flow the Best Practical Stock Return Predictor?

Which firm accounting measures best predict future stock returns? In the August 2014 version of their paper entitled “Are Cash Flows Better Stock Return Predictors than Profits?”, Stephen Foerster, John Tsagarelis and Grant Wang investigate the power of enhanced cash flow measures to predict stock returns. They first devise procedures for transforming indirect cash flow and income statements into estimates of cash flow directly available to stockholders (see the table below). They then compare the ability of these measures and of alternative cash flow/profit/income measures to predict stock returns via hedge portfolios that are each month long (short) the tenth of stocks with the best (worst) values of each measure. They scale all measures either by total assets or by market value of equity. They consider both value-weighted and equal-weighted hedge portfolios. They use the real-time S&P 1500 (excluding financial firms) as their stock universe to ensure investability. Using monthly accounting data lagged by four months and monthly stock returns for the specified set of firms during October 1994 through December 2013, they find that: Keep Reading

Preponderance of Evidence Bad for U.S. Stocks?

Is the U.S. stock market in a Federal Reserve-driven bubble that is about to burst? In his August 2014 paper entitled “Fed by the Fed: A New Bubble Grows on Wall St.”, Oliver Dettmann examines how shifts away from quantitative easing by central banks, and the introduction of rising interest rates, may affect current valuation levels of the U.S. stock market. He focuses on a discounted real earnings model, employing a range of optimistic, moderate and pessimistic scenarios. Based on estimates of S&P 500 real earnings growth and an implied earnings discount rate derived from a sample period of January 1974 through June 2014, he finds that: Keep Reading

P/E10s Worldwide in 2014

What is the state of cyclically adjusted price-earnings ratios (CAPE, P/E10 or Shiller PE), stock index level divided by average real earnings over the past ten years, across country equity markets worldwide? In their July 2014 paper entitled “CAPE around the World: Update 2014 – The Relationship between Risk and Return”, Joachim Klement and Oliver Dettmann update expected returns for equity markets around the world in local currencies based on P/E10. They adjust P/E10 for economic conditions for each country via regression of P/E10 versus real GDP growth, real per capita GDP growth, real interest rate and inflation. Using stock index level, P/E10 and economic data for 20 developed and 18 emerging equity markets as available through June 2014, they find that: Keep Reading

High Growth in Operating Costs Bad for Stocks?

Does growth in a firm’s operating costs signal trouble for its stock? In their June 2014 preliminary paper entitled “Cost Growth and Stock Returns”, Dashan Huang, Fuwei Jiang, Jun Tu and Guofu Zhou examine the relationship between growth in operating costs and future stock returns. They measure operating cost growth as the annual percentage change in costs of goods sold plus selling, general and administrative expenses. They speculate that high cost growth warns of deteriorating profitability. Since analysts and investors focus on earnings and cash flows, they may not fully appreciate the import of cost growth. To ensure that cost growth data is available for public signaling, they relate stock return for July through June of year t+1 to accounting data as of the end of firm fiscal year t-1. Using accounting data from 1963 through 2012 and associated stock returns during July 1968 through 2013 for a broad sample of U.S. common stocks, they find that: Keep Reading

Aggregate Asset Growth as a Stock Market Indicator

Research (see “Asset Growth Rate as a Return Indicator” and “Asset Growth a Bad Sign for Stocks Everywhere?”) indicates that stocks of firms with high asset growth rates tend subsequently to underperform the market. Does this finding translate to the overall stock market? In the April 2014 version of his paper entitled “Asset Growth and Stock Market Returns: a Time-Series Analysis”, Quan Wen examines whether the asset growth anomaly observed at the firm level applies in aggregate to the U.S. stock market. He also investigates whether any aggregate effect is predominantly behavioral or risk-based. He estimates aggregate growth rate quarterly as the market capitalization-weighted sum of firm-level percentage changes in book value of total assets. To ensure all asset data is known to investors, he relates asset growth rate to returns two quarters later. Using quarterly U.S. stock market excess returns (relative to the risk-free rate), asset growth rates for listed U.S. firms that employ calendar year accounting, analyst forecasts/revisions, stock returns around earnings announcements, and data required for comparison of asset growth with other U.S. stock market indicators during 1972 through 2011, he finds that: Keep Reading

A Few Notes on Global Value

In the introduction to his 2014 book entitled Global Value: How to Spot Bubbles, Avoid Market Crashes, and Earn Big Returns in the Stock Market, author Mebane Faber, ponders: “Can we or can’t we predict when a bubble is occurring? Below we [try] to find an objective way to identify bubbles, avoid their popping, and invest in their aftermath.” He focuses on the the cyclically adjusted price-to-earnings (CAPE) ratio (or P/E10) as a bubble indicator, including a variety of charts. Based on concepts originally developed and refined by Benjamin Graham, David Dodd, Robert Shiller and many others, he concludes that: Keep Reading

Successfully Exploiting the ex-Dividend Effect?

Can the best traders reliably exploit the ex-dividend effect (the tendency for dividend-paying stocks to fall by less than the dividend amount after paying the dividend)? In their March 2014 paper entitled “Ex-Dividend Profitability and Institutional Trading Skill”, Tyler Henry and Jennifer Koski examine whether highly skilled traders bearing very low transaction costs (some institutions) successfully exploit this effect. They use actual transaction prices and actual transaction costs. They segment their sample period into three regimes: Regime 1 is pre-decimalization and pre-tax reform that equalizes capital gains and dividend tax rates; Regime 2 is post-decimalization and pre-tax reform; and, Regime 3 is post-decimalization and post-tax reform. They specify the ex-dividend trading window as days -5 through +5 relative to ex-dividend day 0. Using a large proprietary set of institutional common stock buy and sell transactions and associated transaction costs, and contemporaneous dividends, returns, bid/ask prices and trading volumes for those stocks, during 1999 through 2007 (24,741 ex-dividend events for 1,351 firms), they find that: Keep Reading

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