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.
August 3, 2015 - Calendar Effects, Fundamental Valuation, Momentum Investing
We have updated the the monthly asset class ETF value strategy weights and associated performance data at Value Strategy.
July 31, 2015 - Calendar Effects, Fundamental Valuation, Momentum Investing
We have updated the the monthly asset class ETF momentum winners and associated performance data at Momentum Strategy.
We have updated the Trading Calendar to incorporate data for July 2015.
July 23, 2015 - Fundamental Valuation
What are current implications 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 July 2015 paper entitled “CAPE around the World: Update 2015 – Return Differences and Exchange Rate Movements”, Joachim Klement analyzes expected returns in local currencies for equity markets around the world based on an adjusted P/E10. His adjustment accounts for economic conditions in each country via regression of local P/E10 versus real GDP growth, real per capita GDP growth, real interest rate and inflation. He also examines interactions among exchange rate movements, adjusted P/E10s and expected returns. Using stock index level, P/E10, economic data and exchange rate versus the U.S. dollar for 20 developed and 18 emerging equity markets as available through June 2015, he finds that: Keep Reading
July 8, 2015 - Fundamental Valuation, Technical Trading
Stock return anomaly studies based on firm accounting variables generally employ annually reformed portfolios that are long (short) the tenth of stocks expected to perform well (poorly). Does adding monthly portfolio updates based on technical stock price trend measurements boost anomaly portfolio performance? In the June 2015 version of their paper entitled “Anomalies Enhanced: The Use of Higher Frequency Information”, Yufeng Han, Dayong Huang and Guofu Zhou test eight equal-weighted long-short portfolios that combine annual screening based on a predictive accounting variable with monthly screening based on a simple moving average (SMA)-based stock price trend rule. The eight accounting variables (screened in June based on prior December data) are: (1) book-to-market ratio; (2) gross profitability; (3) operating profitability; (4) asset growth; (5) investment growth; (6) net stock issuance; (7) accruals; and, (8) net operating assets. The price trend screen excludes from the long (short) side of the portfolio any stock for which 50-day SMA is less than (greater than) 200-day SMA at the end of the prior month. Using accounting and daily price data for a broad sample of U.S. stocks during July 1965 through December 2013, they find that: Keep Reading
May 22, 2015 - Fundamental Valuation
Are there gradual steps toward a fundamental stock index that work just as well? In their April 2015 draft paper entitled “Decomposing Fundamental Indexation”, Gregg Fisher, Ronnie Shah and Sheridan Titman compare fundamental indexing strategies to strategies that tilt a market index toward high fundamental-to-price stocks. Fundamental indexing strategies weight stocks by firm fundamentals instead of market capitalizations, ignoring any information in stock prices. The tilt strategies adjust market weights with multipliers linearly scaled to fundamental-to-price ratios across a universe of stocks. Reflecting extreme fundamentals ratios for smaller stocks, the range of multipliers for stocks in the upper (lower) half of market capitalizations is 0 to 2 (0 to 4). After applying multipliers, tilt the strategies normalize weights so that they sum to 100%. Rebalancing for all portfolios is annual on the last day in April, incorporating a minimum four-month lag between the end of the financial reporting period and portfolio formation. Using data for a broad sample of U.S. common stocks during May 1975 through December 2014, they find that: Keep Reading
May 1, 2015 - Fundamental Valuation, Strategic Allocation
Do simple stock market valuation ratios work for tactical allocation? In his April 2015 paper entitled “Multiples, Forecasting, and Asset Allocation”, Javier Estrada investigates whether investors can outperform a 60-40 stocks-bonds benchmark portfolio via tactical strategies based on one of three simple stock market valuation ratios: (1) dividend-price ratio (D/P); (2) price-earnings ratio (P/E); or, (3) cyclically adjusted price-earnings ratio (CAPE, or P/E10). The valuation‐based strategies take aggressive (conservative) stances when stocks are cheap (expensive) via combinations of the following rules:
- Designate stocks as cheap (expensive) when a valuation ratio is below (above) its inception-to-date mean by one standard deviation (1SD) or two standard deviations (2SD).
- Use 60-40 stocks-bonds allocations when stocks are not cheap or expensive. When stocks are cheap (expensive), shift toward stocks (bonds) by 20% to 80-20 (40-60) or by 30% to 90-10 (30-70).
- Rebalance either annually or monthly.
For the benchmark portfolio and the valuation-based portfolios when in 60-40 stance, rebalancing occurs only when the stock allocation drifts below 55% or above 65%. To accrue at least 20 years of data for initial valuations, strategy performance measurements span 1920 through 2014 (95 years). Calculations lag dividends and earnings by three months to ensure real-time availability. Testing ignores trading frictions and tax implications. Using monthly S&P 500 Index total returns and the yield on 90-day U.S. Treasury bills (T-bills) during September 1899 through December 2014, he finds that: Keep Reading
April 17, 2015 - Fundamental Valuation
Is the part of profitability based on cash flow more informative than the part based on accruals? In their March 2015 paper entitled “Accruals, Cash Flows, and Operating Profitability in the Cross Section of Stock Returns”, Ray Ball, Joseph Gerakos, Juhani Linnainmaa and Valeri Nikolaev investigate the power of the cash flow part of profitability to predict stock returns. They compare its predictive power to those of overall operating profitability and of the accruals part of profitability. Using monthly returns and annual firm accounting data (lagged six months) for a broad sample of U.S. common stocks during July 1963 through December 2013, they find that: Keep Reading
February 23, 2015 - Economic Indicators, Fundamental Valuation, Sentiment Indicators
The Mojena Market Timing strategy (Mojena), developed and maintained by professor Richard Mojena, is a method for timing the broad U.S. stock market based on a combination of 11 monetary, fundamental, technical and sentiment indicators to predict changes in intermediate-term and long-term market trends. He adjusts the model annually to incorporate new data year by year. Professor Mojena offers a hypothetical backtest of the timing model since 1970 and a live investing test since 1990 based on the S&P 500 Index (with dividends). To test the robustness of the strategy’s performance, we consider a sample period commencing with availability of SPDR S&P 500 (SPY) as a conveniently investable proxy for the S&P 500 Index. As benchmarks, we consider both buying and holding SPY (Buy-and-Hold) and trading SPY with crash protection based on the 10-month simple moving average of the S&P 500 Index (SMA10). Using the trade dates from the Mojena Market Timing live test, daily dividend-adjusted closes for SPY and daily yields for 13-week Treasury bills (T-bills) over the period 1/29/93 through January 2015 (22 years), we find that: Keep Reading
February 17, 2015 - Fundamental Valuation, Size Effect
Given the conflicting evidence about the import of the size effect, is there a way investors can extract a reliable premium from small stocks? In their January 2015 draft paper entitled “Size Matters, If You Control Your Junk”, Clifford Asness, Andrea Frazzini, Ronen Israel, Tobas Moskowitz and Lasse Pedersen examine whether controlling for firm quality mitigates the following seven unfavorable empirical findings that the size effect:
- Is weak overall in the U.S.
- Has not worked out-of-sample and varies significantly over time.
- Only works for extremely small stocks.
- Only works in January.
- Only works for market capitalization-based measures of size.
- Is subsumed by illiquidity.
- Is weak internationally.
They control for quality using a Quality-Minus-Junk (QMJ) factor based on profitability, profit growth, safety and payout. They use a portfolio test approach, ranking stocks into value-weighted tenths (deciles) each month to examine differences among stocks sorted by factor. Focusing on returns and factor metrics for a broad sample of U.S. common stocks during July 1957 (when quality metrics become available) through December 2012 and for 23 other developed country stock markets during January 1983 through December 2012, they find that: Keep Reading
January 29, 2015 - Fundamental Valuation
Can investors usefully apply stock quality metrics to entire country stock markets? In his December 2014 paper entitled “Country Selection Strategies Based on Quality”, Adam Zaremba investigates whether quality metrics effectively predict country stock market index performance. He also examines whether (1) quality-size and quality-value double sorts enhance country-level value and size strategies; and, (2) high-quality markets offer a hedge during times of market distress. He considers six quality metrics: accruals, cash (cash divided by total assets), profitability (return on assets), leverage (total assets divided by common equity), payout (dividends as a fraction of income) and turnover (dollar volume of trading divided by market capitalization). Firm metric aggregation weightings are those used in constructing respective country indexes. After lagging the time series by three months to avoid a look-ahead bias, he forms capitalization-weighted portfolios of country markets by ranking them into fifths (quintiles) based on quality metric sorts. He identifies times of market distress based on: the spread between U.S. LIBOR and U.S. Treasury bill yields; VIX; the spread between U.S. corporate BBB bond and 10-year U.S. Treasury note yields; and, the spread between U.S. Treasury 10-year and 2-year note yields. Using stock market index returns and accounting data in U.S. dollars across 77 country stock markets during February 1999 through September 2014 as available, and contemporaneous market distress indicator values, he finds that: Keep Reading