Fundamental Valuation

Is there a way to suppress the volatility and drawdowns of a mixed value and momentum stock strategy while retaining most of its benefit? In his September 2015 paper entitled “Learning to Play Offense and Defense: Combining Value and Momentum from the Bottom up, and the Top Down”, Mebane Faber examines the feasibility of a strategy that combines market valuation and market trend timing (defense) with a mixed value and momentum stock selection strategy (offense). Specifically:

For offense, he each month: (1) ranks stocks by each of price-to-earnings, price-to-book and earnings before interest and taxes-to-total enterprise value ratios and then re-ranks them by the average of the three separate value rankings; (2) ranks stocks by each of 3-month, 6-month and 12-month past returns and then re-ranks them by the average of the three separate momentum rankings; and, (3) forms an equally weighted portfolio of the top 100 value and top 100 momentum stocks and holds for three months (three overlapping portfolios).

For defense, he each month: (1) hedges half of the portfolio by shorting the S&P 500 Index if the long-term real earnings yield for the S&P 500 (inverse of the Cyclically Adjusted Price-Earnings ratio, CAPE or P/E10 as calculated by Robert Shiller, minus the most recently available actual 12-month U.S. inflation rate) is in the 20% of its lowest inception-to-date monthly values; and, (2) hedges half of the portfolio by shorting the S&P 500 Index if the index is below its 12-month simple moving average. 

The overall portfolio can therefore be 100% long “offense” stocks, 50% hedged or market neutral. He does not account for costs of portfolio reformations or hedging. Using monthly total returns for all NYSE stocks in the top 60% of market capitalizations, monthly levels of the S&P 500 Total Return Index and monthly values of CAPE during 1964 through 2014, he finds that: Keep Reading

Is fundamental valuation of stocks an inherently effective investment approach? In their October 2015 paper entitled “Fundamental Analysis Works”, Sohnke Bartram and Mark Grinblatt test whether fundamental valuation usefully predict stock performance. Each month, they estimate the fair value (market capitalization) of each stock based on linear regression versus the 28 most commonly reported firm accounting variables (14 from the balance sheet and 14 from the income statement), thereby avoiding snooping of specific indicators. They then rank stocks into fifths (quintiles) based on the degree to which the market misprices them (percentage difference between actual market capitalization and estimated fair value). Finally, they measure the profitability of a monthly reformed portfolio that buys (sells) the most undervalued (overvalued) quintile. Using monthly accounting data as available from Forms 10-Q/10-K and prices for a broad sample of non-financial U.S. common stocks during January 1977 through December 2012 (432 months), they find that: Keep Reading

How do those whose jobs involve stock valuation perform this task? In their September 2015 paper entitled “Equity Valuation: A Survey of Professional Practice”, Jerald Pinto, Thomas Robinson and John Stowe report results of a 38-question equity valuation practices survey sent to 13,500 CFA Institute members with equity analysis job responsibilities. They guided respondents through the survey via the following introductory question:

“In evaluating individual equity securities, which of the following approaches to valuation do you use? (Select all that apply)

a) A market multiples approach (e.g., based on price-to-earnings, enterprise value-to-EBITDA, or other multiples)
b) A present discounted value approach (e.g., based on forecasts of future dividends, free cash flows, or economic value added/residual income)―also known as the income approach
c) An asset-based approach (e.g., based on book value, adjusted book value, asset market values, or asset replacement costs)
d) A (real) options approach (using options models to value equity)
e) Other (please specify)”

Using responses from 1,980 completed questionnaires, they find that: Keep Reading

Are expert technicians or fundamentalists better forecasters of short-term and intermediate-term asset returns? In the August 2015 version of their paper entitled “Talking Numbers: Technical versus Fundamental Recommendations”, Doron Avramov, Guy Kaplanski and Haim Levy assess the economic value of dual technical and fundamental recommendations presented simultaneously on “Talking Numbers”, a CNBC and Yahoo joint broadcast… “featuring fundamental and technical recommendations before and during the market open. Dual recommendations are made by highly experienced analysts representing prominent institutions.” Recommendations address both individual stocks and asset classes, including U.S. and foreign broad equity indexes, sector/industry equity indexes, bonds, commodities and exchange rates. Using 1,000 dual recommendations on 262 stocks and 620 dual recommendations on other assets, along with associated price data, during November 2011 through December 2014, they find that: Keep Reading

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

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

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

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

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

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:

1. Is weak overall in the U.S.
2. Has not worked out-of-sample and varies significantly over time.
3. Only works for extremely small stocks.
4. Only works in January.
5. Only works for market capitalization-based measures of size.
6. Is subsumed by illiquidity.
7. 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