Fundamental Valuation

In their March 2011 paper entitled “The Shrinking Space for Anomalies”, George Jiang and Andrew Zhang investigate the robustness of ten well-known anomalies by iteratively “shrinking the stock space” in two ways to determine whether and how the anomalies really work. The ten anomaly variables are: size, book-to-market ratio, momentum, two liquidity measures, idiosyncratic volatility, accrual, capital expenditure, sales growth and net share issuance. The first way of “shrinking the stock space” involves: (1) ranking the universe of stocks by each of the ten anomaly variables into deciles; (2) iteratively trimming deciles from side of a variable distribution that a hedge portfolio would sell and the side that a hedge portfolio would buy; and, (3) retesting the strength of the anomaly associated with the variable after each iterative trimming. The second way of “shrinking the stock space” involves: (1) trimming from the sample stocks with the smallest market capitalizations and the most extreme book-to-market ratios until size, book-to-market and momentum no longer have significant four-factor alphas for value-weighting and equal equal-weighting (thereby “perfecting” the sample for the four-factor model); and, (2) retesting the strength of the anomalies associated with the other seven variables using the perfected sample. This approach obviates weaknesses in alpha measurement via the commonly applied but imperfect three-factor (market, size, book-to-market) and four-factor (plus momentum) risk models. Using firm characteristics and trading data for all non-financial NYSE, AMEX, and NASDAQ common stocks over the period July 1962 through December 2007, they find that: Keep Reading

Which firm fundamentals predict associated stocks returns, and which ones do not? In their February 2011 paper entitled “Returns Premia on Company Fundamentals”, Kateryna Shapovalova, Alexander Subbotin and Thierry Chauveau assess the significance, stability and interplay of excess returns for individual stocks as predicted by widely used firm fundamentals. Specifically, they consider: book-to-price ratio; earnings-to-price ratio; sales-to-price ratio; cash flow-to-price ratio; dividend yield; market capitalization; growth in sales per share over the past one, three and five years; growth in earnings per share over the past one, three and five years; forecasted growth of earnings per share next year; forecasted long-term growth in earnings per share; forecasted earnings-to-price ratio; five-year average reinvested fraction of return on equity (internal growth); and, for control purposes, past returns over one, three and 12 months. Their methodology is direct stock-by-stock rather than portfolio-mediated, with the values of fundamentals across stocks normalized to a range of zero to one. They impose a three-month lag for accounting data to ensure public availability. Using monthly/quarterly firm fundamentals and monthly total stock returns for 9,363 NYSE-listed firms during 1979 through 2008, they find that: Keep Reading

Do online forums of arguably well-informed investors pay off for their members? In their February 2011 paper entitled “Talking Your Book: Social Networks and Price Discovery”, Wesley Gray and Andrew Kern study the sharing of valuation beliefs by professional investors via a social network. Specifically, they focus on ValueInvestorsClub.com, “designed to facilitate idea sharing among…250 [screened but anonymous] fundamentals-based managers (primarily hedge fund managers) who post detailed summaries of their investment analyses to the website. Once an idea is posted, it is visible to the other club members. Forty-five days after the idea is initially shared within this small community, the club grants public access to the investment thesis through a ‘guest access’ feature available to anyone with an email address.” Using approximately 2,000 long and 250 short recommendations for publicly traded common stocks shared via ValueInvestorsClub.com during 2000 through 2008, along with associated stock return, firm fundamentals and institutional ownership (SEC Form 13F) data, they find that: Keep Reading

What is the state, from an investor’s perspective, of research on the power of accounting and fundamentals to predict stock returns? In their September 2010 paper entitled “Accounting Anomalies and Fundamental Analysis: A Review of Recent Research Advances”, Scott Richardson, Irem Tuna and Peter Wysocki present an overview of post-2000 research on accounting anomalies and fundamental analysis geared toward forecasting future earnings and stock returns. They include results from matched 2009 surveys of 201 investment practitioners and 63 accounting academics on relevant beliefs about this research. They also present a new analysis of how expected risk and expected transaction costs affect the accrual and post-earnings announcement drift (PEAD) anomalies. Using for this new analysis accounting data (lagged three months) and stock returns for 1,000 relatively liquid U.S. stocks over the period 1979 through 2008, they find that: Keep Reading

Is the number of institutional owners of a stock, arguably a proxy for general investor awareness and demand, an important factor in current and future pricing of the stock? In their February 2011 paper entitled “What Makes Stock Prices Move? Fundamentals vs. Investor Recognition”, Scott Richardson, Richard Sloan and Haifeng You investigate the role of institutional ownership breadth in size-adjusted stock price dynamics. They focus on institutional investors with greater than $100 million in equity holdings, as reported quarterly to the SEC via Form 13F. They measure institutional ownership breadth as the number of institutions holding a particular stock relative to the number of institutions holding any given stock. They measure firm size based on total assets. They impose a three-month lag on data to ensure calculations use only publicly available information. Using stock returns, institutional ownership data and accounting data for a broad sample of U.S. firms over the period 1986 through 2008 (35,526 firm years), they find that: Keep Reading

Can financial statement analysis expose stocks that investors incorrectly view as value or growth (glamor)? In their February 2011 paper entitled “Identifying Expectation Errors in Value/Glamour Strategies: A Fundamental Analysis Approach”, Joseph Piotroski and Eric So investigate stock misvaluation by contrasting firm performance expectations implied by value/growth classification with a simple financial statement metric that differentiates improving versus deteriorating financial performance. This metric (FSCORE, scale 0 to 9), based on nine binary financial statement parameters, measures both the overall financial condition of a firm and the degree to which the firm has improved this condition over the prior year. The authors examine how FSCORE interacts with five widely used relative valuation metrics (book-to-market ratio, cash flow-to-price ratio, earnings-to-price ratio, sales growth and equity share turnover) and with momentum. Using annual financial data and stock returns for a broad sample of firms over the period 1972 through 2008 (117,412 firm-year observations), they find that: Keep Reading

Is it feasible to isolate and exploit the value of entrepreneurial spirit among publicly traded stocks? In his Fall 2009 article entitled “Investing in Troubled Times: Entrepreneurs are Your Safest Bet”, Joel Shulman defines, filters and analyzes the performance of entrepreneurial stocks. Building on prior research, he defines “entrepreneurial” based on the following 15 attributes, several of which do not accommodate mechanical quantitative screening:

1. Organic growth opportunities
2. Above-average ownership stakes among key stakeholders
3. Low selling, general, and administrative expenses
4. Above average return on invested capital
5. Sustainable growth
6. Manageable debt
7. Active strategic alliances/partnerships/licensing deals
8. Aligned executive compensation packages
9. Low executive turnover
10. Transparent governance
11. Long duration of key managers
12. Low or no dividends
13. Family involvement
14. Strong earnings before interest, taxes, depreciation and amortization
15. Other significant stakeholder relationships (such as key board members)

Using  information for 9,000 publicly traded firms worldwide for which sufficient financial, stock return and other data are available over the period January 1997 through August 2009, he finds that: Keep Reading

Is company financial leverage a useful indicator of future stock returns? In their October 2010 paper entitled “Would You Follow MM or a Profitable Trading Strategy?”, Brian Baturevich and Gulnur Muradoglu test company leverage (gearing ratio) as a predictor of stock outperformance, controlling for market capitalization, price-to-earnings ratio, market-to-book value ratio and beta. At the beginning of May each year, they construct ten equally weighted portfolios ranked on gearing ratio as of the end of the preceding December and hold the portfolios for three years. They further sort each of these portfolios into ten sub-portfolios ranked on controlling variables as of the end of the preceding December (creating 100 sub-portfolios). Using stock return and accounting data for 413 non-financial S&P 500 companies over the period May 1985 through April 2004, they find that: Keep Reading

What are the implications for investors of a trend toward strategic and tactical allocation to index proxies (exchange-traded funds and derivatives) rather than individual securities? The July 2010 paper entitled “On the Economic Consequences of Index-Linked Investing” by Jeffrey Wurgler provides an overview of the effects of index-linked investing on stock prices, risk-return trade-offs, investor portfolio allocation decisions and fund manager skill assessments. The September 2010 paper entitled “Index Investment and Financialization of Commodities” by Ke Tang and Wei Xiong investigates the effects of increased investing during the last decade in commodity indexes. The October 2010 paper entitled “The Financialization of Commodity Futures Markets or: How I Learned to Stop Worrying and Love the Index Funds” by Scott Irwin and Dwight Sanders surveys research on the impact of commodity index fund growth on commodity price behavior. Using results of prior research and recent data on indexation investment levels, index returns and component asset returns, these papers find that: Keep Reading

Does high-frequency trading amplify noise and thereby reduce the signal-to-noise ratio in stock returns? In his August 2010 paper entitled “The Effect of High-Frequency Trading on Stock Volatility and Price Discovery”, Frank Zhang examines the effect of high-frequency trading on stock price volatility and on incorporation of fundamental news into price. He defines high-frequency trading as that driven by fully automated trading strategies with very high trading volume and extremely short holding periods ranging from milliseconds to minutes and possibly hours (typically not overnight). He estimates the volume of high-frequency trading as the residual after accounting for institutional and individual investor activities. Using price, trading and institutional holdings data for a broad sample of U.S. stocks from the first quarter of 1985 through the second quarter of 2009, he finds that: Keep Reading