Fundamental Valuation

Do investors efficiently process the information in extreme quarterly earnings? In their November 2009 paper entitled “Post Loss/Profit Announcement Drift”, Karthik Balakrishnan, Eli Bartov and Lucile Faurel examine whether investors fully price the implications of current quarterly losses/profits for future losses/profits. They consider three alternative definitions for profit/loss, all scaled by beginning-of-quarter total assets: (1) earnings before extraordinary items and discontinued operations; (2) earnings before extraordinary items, discontinued operations and special items; and, (3) net income. Using stock return, financial and risk adjustment data for a broad sample of 15,143 distinct firms (458,693 firm-quarters) over the period 1976-2005 (120 quarters), they conclude that: Keep Reading

Is the value premium readily accessible for individual investors? Which value strategy works best? In his May 2009 article entitled “Can Individual Investors Capture The Value Premium?”, Patrick Larkin uses a ranking methodology to compare the performances of Joel Greenblatt’s magic formula and seven other one and two-factor growth at a reasonable price (GARP) and value strategies. The portfolios for the eight strategies derive from rankings on: (1) the magic formula, a combination of return on capital (ROC) and the ratio of earnings before interest and taxes to Enterprise Value ((EBIT/EV); (2) a combination of return on assets (ROA) and earnings yield (E/P); (3) a combination of return on equity (ROE) and E/P; (4) EBIT/EV alone; (5) E/P alone; (6) a combination of book-to-market ratio (B/M) and market capitalization (Size); (7) B/M alone; and, (8) Size alone. Each month, the author forms equally weighted portfolios of the 30 highest-ranking stocks for each of these eight strategies. Using monthly stock return and GARP-value metric data for a broad sample of firms with market capitalizations over $50 million during December 1998-2006 (97 months), he finds that: Keep Reading

A reader asked: “Does buying Exchange-Traded Funds (ETF) currently trading below Net Asset Value (NAV) provide a real advantage in the long run? In other words, are they ‘bound’ to reach NAV at some point? Does buying a fund which is trading at a discount to NAV and shorting a fund within the same sector that is trading at a premium to NAV make sense?” Keep Reading

A reader asked: “I was wondering if you can weigh in on Tobin’s q as a predictor of stock returns.” Keep Reading

What fundamental and technical factors are optimum for stock selection, and how well do they work? In the October 2008 draft of their paper entitled “Case Closed”, flagged by a reader, Robert Haugen and Nardin Baker present a model of future stock returns based on multiple regressions of 12 factors they find most significant in predicting monthly returns. Using monthly data for a sample of U.S. stocks over the 45-year period 1963-2007, they conclude that: Keep Reading

Do earnings surprises work differently for value and growth stocks? If so, can investors exploit the difference? In the September 2009 draft of their paper entitled “When Two Anomalies meet: Post-Earnings Announcement Drift and Value-Glamour Anomaly”, Zhipeng Yan and Yan Zhao investigate the combined effects of the value premium and the post-earnings announcement drift anomaly. They first sort stocks into quintiles according to some measure of value (book-to-market ratio, earnings-to-price ratio, cash-flow-to-price ratio or three-year average sales growth) and then allocate firms within these quintiles to six categories according to sign of the most recent quarterly earnings surprise (+/-/0) and the direction of the most recent earnings announcement abnormal return (+/-). Using stock price, earnings estimate and accounting data for a broad sample of firms over the period June 1984 through December 2008, they find that: Keep Reading

In the 2009 second edition of his book, The Dark Side of Valuation: Valuing Young, Distressed, and Complex Businesses, Professor of Finance Aswath Damodaran, investigates and offers remedies for “dark practices and flawed methods in valuation.” He emphasizes “the importance of first principles in valuation and how they should guide us when we’re faced with estimation questions and issues.” As summarized in the closing chapter, the key enlightening propositions of the book are: Keep Reading

A reader asked: “Have you ever investigated: (1) the work of R. G. Sloan on the predictive power of accruals (both negative and positive); and, (2) the web site www.valuedog.com? It’s not kept up-to-date anymore, but the ‘earnings torpedo’ and ‘value screen’ parts of the web site are still maintained on a monthly basis, complete with charts. It claims to be ‘based on work at the University of Michigan Business School.’ They used to publish a monthly list of companies with positive or negative accrual attributes, but don’t anymore. I can’t find anyone else that does.” Keep Reading

The Value Line Select ETF (VLSE) Index “is an equal-dollar weighted index comprised of between 30 and 100 U.S. traded ETFs ranked #1 by Value Line Publishing, Inc… The Value Line ETF Ranking System seeks to select the ‘best-for-investment’ ETFs among all U.S. traded ETFs…approximately 10% of all traded ETFs but no more than 100 ETFs. The Value Line Select ETF Index is rebalanced and reconstituted once per quarter… Upon Value Line Select ETF Index’s introduction in 2008, the index values were computed on a daily basis dating back to 2003 to provide a historical frame of reference.” Does this approach to ETF investing beat the market? Using self-reported daily performance data for the VLSE Index over the period 10/21/02 through 8/14/09 (almost seven years), and contemporaneous daily returns for S&P Depository Receipts (SPY) for benchmarking , we find that: Keep Reading

Do aggregate earnings (for example, for the S&P 500) predict stock market behavior? In their 2008 paper entitled “Aggregate Earnings, Firm-Level Earnings and Expected Stock Returns”, Turan Bali, Ozgur Demirtas and Hassan Tehranian analyze the predictability of stock returns using market, industry and firm-level earnings. Using monthly stock return data and quarterly fundamentals data for a broad range of U.S. stocks focused mostly on the period from mid-1972 through 2002, they conclude that: Keep Reading