Fundamental Valuation

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

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

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

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

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

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

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

Is the conventional wisdom that traders can scalp part of cash dividends by buying stocks just before ex-dividend day and selling just after reliable across exchanges? In their January 2014 paper entitled “Ex-Dividend Day Stock Price Behavior – the NASDAQ Evidence”, Shishir Paudel and Sabatino Silveri investigate whether dividend-paying NASDAQ stocks exhibit ex-dividend day price behaviors similar to those of more closely studied dividend-paying NYSE stocks. They measure ex-dividend day price drops with the price-drop ratio (PDR), the ratio of the change in stock price to the amount of the cash dividend. Using a sample of 49,325 (90,867) cash dividends for NASDAQ (NYSE) stocks during 1983 through 2011 (ignoring dividends less than $0.05), they find that: Keep Reading

Are “quality” country stock markets good places to invest? In his December 2013 paper entitled “Quality Investing and the Cross-Section of Country Returns”, Adam Zaremba investigates whether aggregate financial quality determines country stock market performance. Specifically, he uses two-month lagged 12-month data for listed firms to calculate the following eight quality metrics at the country level in each of 66 countries:

1. Return on Assets (ROA) – ratio of net income to average assets.
2. Return on Equity (ROE) – ratio of net income to average common equity.
3. Profit Margin (PM) – ratio of net income to sales.
4. Operating Margin (OM) – ratio of operating income to sales.
5. Gross Margin (GM) – ratio of gross income (sales minus cost of goods sold) to sales.
6. Assets to Debt (AD)- ratio of total assets to short-term plus and long-term borrowings.
7. EBITDA to Debt (ED) – ratio of EBITDA to short-term plus long-term borrowings.
8. Current Ratio (CR) – ratio of current assets to current liabilities.

He uses MSCI country indexes to measure country market returns. He also calculates for each country the total market capitalization, aggregate book-to-market ratio and 12-month market return momentum. He tests relationships between country-level quality factors and returns by constructing portfolios of the equally weighted top 30% (high-quality), middle 40% (mid-quality) and bottom 30% (low-quality) of country markets based on each quality metric. He also measures for each quality metric the performance of a fully collateralized portfolio that is each month long (short) the equally weighted 30% of country markets with the highest (lowest) quality. To test sensitivity to the currency used, he perform all calculations separately in U.S. dollars, euros and yen. Using monthly accounting and return data as specified during May 2000 through October 2013, he finds that: Keep Reading

Why does the gross profitability stock-screening strategy work? In their December 2013 paper entitled “Factoring Profitability”, Michael Branch, Lisa Goldberg and Ran Leshem explore the drivers of the gross profitability strategy for U.S. stocks. Specifically, they examine the contributions of factors in the conventional Fama-French-Carhart four-factor (FFC4) model of equity returns and the Barra USE4 12-factor model of equity returns to an idealized, industry-neutral gross profitability strategy. They define gross profitability as revenue minus cost of goods sold divided by assets. Idealized means a hedge portfolio that is each month long (short) stocks of firms in the top (bottom) fifth of gross profitability with no rebalancing frictions. Industry-neutral means constraining industry weights in the portfolio to equal those in the market index. Using stock price and accounting data and contemporaneous asset pricing model factor values as available during July 1963 through December 2012, they find that: Keep Reading