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Fundamental Valuation

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.

Bond Market-Aggregate Earnings Interactions

Do aggregate corporate earnings predict bond market returns? In his January 2012 paper entitled “Aggregate Earnings and Corporate Bond Markets”, Xanthi Gkougkousi investigates the relationship between aggregate earnings and corporate bond market returns. Using quarterly aggregate earnings for a broad sample of U.S. stocks with fiscal years ending in March, June, September and December and total quarterly returns for ten U.S. corporate bond indexes during January 1973 through December 2010 (360,614 firm-quarter observations), he finds that: Keep Reading

Trading Options on Volatility of Fundamentals

Are realized (actual historical) and implied volatilities the whole story for equity option valuation? In their December 2011 paper entitled “Fundamental Analysis and Option Returns”, Theodore Goodman, Monica Neamtiu and Frank Zhang investigate the extent to which the equity options market fails to recognize volatility of firm operations (accounting data) and whether any such failure is exploitable. They focus tests on long, one-month-to-expiration, at-the-money straddles (long both a call and a put), which profit from large moves in underlying stock prices. They estimate future volatility in firm fundamentals via regression based on a combination of short-term sales/earnings growth and long-term sales/earnings growth volatility (standard deviation over the last six years). They isolate a “pure” expected fundamental volatility via regression versus implied volatility and the implied-realized volatility gap. Using data as available to estimate the relationship between fundamental volatility and returns on options for individual U.S. stocks during January 1996 through September 2010 (52,251 firm-quarters involving 3,481 distinct firms), they find that: Keep Reading

40-Year Valuation Ratio Horse Race

Which widely used valuation metric is best for picking individual stocks? In their November 2011 paper entitled “Analyzing Valuation Measures: A Performance Horse-Race over the past 40 Years”, Wesley Gray and Jack Vogel compare the performances of five annually reformed portfolios sorted on different valuation ratios: earnings-to-market capitalization (E/M); earnings before interest, taxes, depreciation and amortization-to-total enterprise value (EBITDA/TEV); free cash flow-to-total enterprise value (FCF/TEV); gross profit-to-total enterprise value (GP/TEV); and, book value-to-market capitalization (B/M). They also compare the performances of ratios calculated with one year of earnings versus averages of annual earnings over the past two to eight years. They include a lag of at least three months between firm reporting interval and return calculation interval. Using stock price and firm fundamentals data for NYSE common stocks with at least eight years of history (excluding financial, utilities and the 10% of stocks with the smallest market capitalizations) during July 1971 through December 2010, they find that: Keep Reading

SumZero Participant Trading Acumen

Do analysts who work for hedge funds make good calls? In their November 2011 paper entitled “Do Buy-side Recommendations Have Investment Value?”, Steven Crawford, Wesley Gray, Bryan Johnson and Richard Price III profile analysts employed by mutual funds, hedge funds and other investment firms and examine whether these experts make good trading recommendations. Using personal data and 2,135 long and short U.S. common stock investment propositions from over 1,100 participants in the SumZero community of buy-side investment professionals (mostly associated with hedge funds) during March 2008 through December 2010, and contemporaneous institutional holdings from SEC Form 13F filings, they find that: Keep Reading

A Few Notes on What Works on Wall Street

James O’Shaughnessy (Chairman and CEO of O’Shaughnessy Asset Management) introduces his 2011 book, What Works on Wall Street (Fourth Edition): the Classic Guide to the Best-Performing Investment Strategies of All Time, by stating: “…investors seem programmed by nature to fail at investing, forever chasing the asset class that has turned in the best performance recently and heavily discounting anything that occurred more than three to five years ago. The whole purpose of What Works on Wall Street is to dissuade investors from that course of action. Only the fullness of time shows which investment strategies are the best long-term performers, and this is doubly true after the last decade’s sorry performance. …We will make the case that equities–particularly those selected using the best long-term strategies–will go on to be the best performing assets over the next 10 and 20 years. …The fourth edition of What Works on Wall Street continues to offer readers access to long-term studies of Wall Street’s most effective investment strategies.” He uses overlapping portfolios formed monthly and rebalanced annually for all tests. Using broad sets of data on U.S. firms/stocks from either 1963 or 1926 through 2009 to extend and expand his prior quantitative analyses, he concludes that: Keep Reading

Dividend Month Premium

Do investors focus on dividends, thereby elevating associated stock prices as ex-dividend date approaches? In the September 2011 draft of their paper entitled “The Dividend Month Premium”, Samuel Hartzmark and David Solomon examine the price behavior of stocks with scheduled quarterly, semiannual and annual dividends during the expected dividend month and around expected ex-dividend dates. Using daily and monthly price and cash dividend data for a broad sample of U.S. stocks during January 1927 through December 2009, along with widely used risk adjustment factors, they find that: Keep Reading

Prediction of Industry-level Returns Based on Oil Price Changes

Do oil price variations reliably affect returns for U.S. industry-level stock portfolios? In the June 2011 draft of their paper entitled “U.S. Industry-Level Returns and Oil Prices”, Qinbin Fan and Mohammad Jahan-Parvar apply several tests to investigate how oil price changes impact stock returns for 49 U.S. industries. They test economic significance by: (1) using a 60-month rolling historical window to model the predictive relationship between spot oil price changes and industry returns; (2) applying this relationship each month to the last observed oil price change to predict future industry returns; and, (3) investing in either industry portfolios or 4-week Treasury bills according to which has the higher expected return. They assume an industry portfolio-Treasury bill switching friction of 0.10%. Using monthly and weekly prices for West Texas Intermediate crude oil spot (January 1979 through January 2009) and nearest contract Cushing, Oklahoma light sweet crude oil futures (February 1986 through January), along with contemporaneous U.S. industry returns, they find that: Keep Reading

Announcement Tone and Short-term Reaction to Earnings News

Does the semantic tone of an earnings announcement, as measured independently of the level of earnings surprise, affect stock price reaction. In his September 2011 paper entitled “Short-term Reactions to News Announcements”, Michal Dzielinski investigates the effect of the tone (positive, neutral or negative) of the words in earnings announcements and other company news on stock prices from two days before to ten days after release. He averages news tone for each stock by day, with news released before (after) the market close counting as current-day (next-day) news. Using daily return data and over six million automatic, real-time Thomson Reuters news sentiment (tone) measurements (including those for over 68,000 earnings announcements) for 4,750 U.S. stocks during 2003 through 2010, he finds that: Keep Reading

CSI: Wall Street

Can investors apply forensic accounting principles (searching for inconsistencies, irregularities and other signs of trouble) to help forecast stock returns? In their July 2011 paper entitled “To Catch a Thief: Can Forensic Accounting Help Predict Stock Returns?”, Messod Beneish, Charles Lee and Craig Nichols investigate the ability of an earnings manipulation model to predict stock returns and detect fraud. The model, which relies exclusively on financial statement data, consists of eight ratios indicative of either financial statement distortions associated with earnings manipulation or a predisposition to engage in earnings manipulation. Specifically, four of the ratios detect unusual buildup in receivables, unusual expense capitalization and dependence of profits on accruals. The other four ratios detect deteriorating gross margins and increasing administration costs, high sales growth and increasing reliance on debt financing. The model calibration period is 1982-1988, and its initial test period is 1989-1992. Using the exact model published in the Financial Analyst Journal in 1999 as applied to accounting data and stock returns for a broad sample of NYSE, AMEX, and NASDAQ over the period 1993 through 2007 (33,848 firm-year observations, excluding financial services firms and small firms), they find that: Keep Reading

Does the Magic Formula Produce Enchanting Returns?

A reader commented and asked: “One of the most read investing books in the U.S. is Joel Greenblatt’s The Little Book that Beats the Market, which reveals the ‘magic formula’. What do you think of it?” In response, rather than review the book, we examine the U.S. Value Direct Composite returns at Formula Investing. These returns summarize the composite performance of portfolios of professionally managed (minimum $100,000) accounts each holding approximately 24 stocks with the highest rank per the magic formula, reformed quarterly by replacing the six worst performers with the highest ranking stocks not in the portfolio. Portfolio weights are apparently about equal, subject to rotation rule constraints. According to Formula Investing:

“The S&P CompuStat database is used for the screening of U.S. listed stocks, with the exception of financials and utilities. The stocks are screened for our best ranked companies based on return on capital and earnings yield.”

“Returns are presented net of investment advisory fees and include the reinvestment of all income. For the period May 1, 2009 – December 31, 2010, the composite includes accounts that received a temporary waiver of the advisory fee. …Net returns may be reduced by additional fees (outside of investment advisory fees) and transaction costs that may be incurred in the management of the account.”

Using monthly U.S. Value Direct Composite returns as presented and contemporaneous monthly returns of the dividend-adjusted Rydex S&P 500 Equal Weight (RSP) and dividend-adjusted iShares Russell 2000 Index (IWM) as benchmarks for May 2009 through June 2011 (27 months), we find that: Keep Reading

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