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.
Models, Trading Calendar and Momentum Strategy Updates November 29, 2013
We have updated the S&P 500 Market Models summary as follows:
- Extended Market Models regressions/rolled projections by one month based on data available through November 2013.
- Updated Market Models backtest charts and the market valuation metrics map based on data available through November 2013.
We have updated the Trading Calendar to incorporate data for November 2013.
We have updated the the monthly asset class momentum winners and associated performance data at Momentum Strategy.
CFO Insights on Earnings Manipulation Red Flags November 12, 2013
What do insiders regard as red flags for corporate earnings manipulation? In their May 2013 paper entitled “Earnings Quality: Evidence from the Field”, Ilia Dichev, John Graham, Campbell Harvey and Shiva Rajgopal report earnings quality insights from Chief Financial Officers (CFO) of publicly owned companies via 169 responses to an anonymous online survey, plus 12 telephone interviews. They invited survey participation via emails in late October 2011 and closed the survey in early December 2011. Firms of responding CFOs are mostly from the manufacturing (38%), banking/finance/insurance (16%) and healthcare/pharmaceuticals (8%) sectors, and about 27% have annual revenues greater than $10 billion. Based on survey results, CFOs believe that: More…
Stock Market Valuation Ratio Trends October 23, 2013
To determine whether the stock market is expensive or cheap, some experts use aggregate valuation ratios, either trailing or forward-looking, such as earnings-price ratio (E/P) and dividend yield. Operating under a belief that such ratios are mean-reverting, most imminently due to movement of stock prices, these experts expect high (low) future stock market returns when these ratios are high (low). Where are the ratios now? Using the S&P 500 Index level as of the close on 10/17/13 and the most recent actual and forecasted earnings and dividend data from Standard & Poor’s, we find that: More…
Implications of Worldwide P/E10s October 17, 2013
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 his October 2013 paper entitled “What the Shiller PE Says About Global Equity Markets: Update 2013″, Joachim Klement updates expected returns for equity markets around the world based on an P/E10 (see “Predictive Power of P/E10 Worldwide”). He adjusts 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 September 2013, he finds that: More…
Stock Screening Power of Long-term Average Valuation Ratios October 8, 2013
Which long-term smoothed (10-year average) stock valuation metric works best to screen stocks? In the end-of-September 2013 version of their paper entitled “On the Performance of Cyclically Adjusted Valuation Measures”, Wesley Gray and Jack Vogel compare the abilities of five valuation ratios expressed as yields to predict U.S. stock returns, as follows:
- 10-year average real earnings to market capitalization (CA-EM)
- 10-year average real book values to market capitalization (CA-BM)
- 10-year average real earnings before interest, taxes, depreciation and amortization to total enterprise value (CA-EBITDA/TEV)
- 10-year average real free cash flow to total enterprise value (CA-FCF/TEV)
- 10-year average real free gross profits to total enterprise value (CA-GP/TEV)
They adjust for inflation using the monthly U.S. Consumer Price Index (CPI). Each year on June 30 (with accounting data lagged to ensure availability), they sort stocks into tenths (deciles) based on each ratio. They then calculate monthly decile returns over the next 12 months based on equal initial weights, with either annual (next June 30) or monthly decile reformation. For monthly reformation, they recalculate market capitalizations (but not valuation ratios) each month. They also test a stock return momentum overlay, each month splitting each valuation ratio top decile into high-momentum and low-momentum halves, with momentum defined as cumulative return from 12 months ago to one month ago. They do not account for trading frictions or taxes. Using stock prices and accounting data for U.S. firms with at least 10 years of the required accounting data and market capitalizations above the 40th percentile for NYSE-listed stocks, and contemporaneous CPI data, during 1962 through 2012, they find that: More…
Reward for the Risk of Value Worldwide? October 7, 2013
Do book value-to-price ratio (B/P) and earnings-to-price ratio (E/P) indicate reward-for-risk opportunities at the country level worldwide? In their September 2013 paper entitled “Risky Value”, Atif Ellahie, Michael Katz and Scott Richardson investigate relationships among these valuation ratios, earnings growth and future returns at the country level for 30 countries over the past two decades. They construct monthly country-level valuation and earnings growth outlooks from capitalization-weighted firm fundamentals and earnings forecasts. They then relate these measures to country capitalization-weighted stock market future excess returns (relative to local risk-free rates), with the return measurement interval commencing four month after fundamentals are available. They replace negative country-level E/P values with zero. Using monthly firm-level fundamentals and stock data, as well as macroeconomic forecasts, for 30 countries during March 1993 through June 2011 (6,600 country-month observations), they find that: More…
Stock Quality and Future Returns August 30, 2013
Are high-quality stocks worth the price? In their August 2013 paper entitled “Quality Minus Junk”, Clifford Asness, Andrea Frazzini and Lasse Pedersen investigate whether high-quality stocks outperform low-quality stocks. They define high-quality stocks as those that are profitable, growing, safe and well-managed. Specifically, they compute a single quality score for each stock by averaging scores for four components calculated as follows:
- Profitability – average of rankings for (high) gross profits/assets, return on equity, return on assets, cash flow/assets, gross margin and fraction of earnings that is cash.
- Growth – average of rankings for (high) prior five-year growth rates for each of the six profitability measures.
- Safety – average of rankings for (low) market beta, idiosyncratic volatility, leverage, bankruptcy risk and volatility of return on equity.
- Payout – average of rankings for (low) net equity issuance and net debt issuance, and (high) total net payout/profits.
They consider two modes of analysis: quality-sorted portfolios and quality-minus-junk (QMJ) long-short factor portfolios. For both modes, the global portfolios is a value-weighted composite of country portfolios. Quality-sorted portfolios are by deciles (tenths), value-weighted and reformed/rebalanced as the end of each calendar month. The monthly QMJ factor portfolio return is the average return on two value-weighted top 30% of quality portfolios (big stocks and small stocks separately) minus the average return on two value-weighted bottom 30% of quality portfolios (big stocks and small stocks separately), reformed/rebalanced monthly by sorting first on size and then on quality. Using characteristics and returns for a broad sample of U.S. stocks during 1951 through 2012 and samples of stocks from 24 developed markets (including the U.S.) as available during 1986 through 2012, and contemporaneous U.S. Treasury bill yields as the risk-free rate, they find that: More…
Fed Model or P/E Model for Predicting Stock Market Corrections? August 20, 2013
Can investors rely on overvaluation signals from the market price-earnings ratio (P/E) and the Fed Model to predict major stock market corrections? Which model works better? In their July 2013 paper entitled “Does the Bond-Stock Earning Yield Differential Model Predict Equity Market Corrections Better Than High P/E Models?”, Sebastien Lleo and William Ziemba test the power of eight bond-stock earnings yield differential model (BSEYD) variants and eight market P/E model variants to predict stock market corrections. They specify the bond yield for the BSEYD model as that of the 10-year U.S. Treasury note (T-note). They define a stock market correction as a decline of 10% or more within one year. They specify the 16 model variants based on: (1) either BSEYD, the natural logarithm of BSEYD, P/E or the natural logarithm of P/E; (2) either current year or rolling 10-year average stock market earnings; and, (3) either of two ways of calculating the threshold for extreme overvaluation. Both methods of setting the extreme overvaluation threshold for the 16 indicators are out-of-sample based on indicator average and standard deviation over a rolling one-year historical window. They measure success of model variants based on both the proportion of signals followed by corrections within two years and, conversely, the proportion of crashes preceded by signals within the past two years. Using daily S&P 500 Index levels, S&P 500 earnings data and daily T-note yields during 1962 through 2012, they find that: More…
Out-of-Sample Test of What Works on Wall Street (O’Shaughnessy’s Cornerstone Strategies) August 6, 2013
How well does stock screening research translate into performance? In the mid-1990s, James O’Shaughnessy identified “cornerstone value” and “cornerstone growth” as best-of-breed equity investment strategies. The former emphasizes dividends among large-capitalization stocks, and the latter momentum/earnings growth for a broader universe. Based on Standard and Poor’s Compustat data, he found that the value (growth) strategy returned 15% (18%) per year during 1952-1994, compared to 8.3% for the S&P 500 Index. He implemented these two strategies in late 1996 via mutual funds and publicized them in early editions of his book What Works on Wall Street: A Guide to the Best-Performing Investment Strategies of All Time. He subsequently sold the mutual funds (which apply slightly different portfolio formation rules from those specified in the original research) to Hennessy Funds in 2000, where they survive as the Hennessy Cornerstone Value Fund (HFCVX) and the Hennessy Cornerstone Growth Fund (HFCGX). Do these funds outperform simpler exchange-traded funds (ETF) that track their respective benchmarks funds: iShares Russell 1000 Value Index (IWD) for HFCVX and iShares Russell 2000 Index (IWM) for HFCGX? Using monthly total returns for HFCVX, HFCGX, IWD and IWM during May 2000 (inception of the ETFs) through July 2013, we find that: More…
Unified Carry Trade Theory August 2, 2013
Does the carry trade concept provide a useful framework for valuation of securities within and across all asset classes? In their July 2013 paper entitled “Carry”, Ralph Koijen, Tobias Moskowitz, Lasse Pedersen and Evert Vrugt investigate expected return across asset classes via decomposition into “carry” (expected return assuming price does not change) and expected price appreciation. They measure carry for: global equities; global 10-year bonds; global bond yield spread (10-year minus 2-year); currencies; commodities; U.S. Treasuries; credit; equity index call options; and equity index put options. Their measurements of carry vary by asset class (based on: futures prices for equity indexes, currencies and commodities, modeled futures prices for global bonds, U.S. Treasuries and credit; and, option prices for options). They further decompose carry returns into passive and dynamic components. The passive component is the return to a hedge (carry trade) portfolio designed to capture differences in average carry returns across securities, and the dynamic component indicates how well carry predicts future price appreciation. Finally, they determine the conditions under which carry strategies perform poorly across all asset classes. Using monthly price/yield data for multiple assets within each class as available during January 1972 through September 2012, they find that: More…