Equity Premium

Governments are largely insulated from market forces. Companies are not. Investments in stocks therefore carry substantial risk in comparison with holdings of government bonds, notes or bills. The marketplace presumably rewards risk with extra return. How much of a return premium should investors in equities expect? These blog entries examine the equity risk premium as a return benchmark for equity investors.

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Better Four-factor Model of Stock Returns?

Are the widely used Fama-French three-factor model (market, size, book-to-market ratio) and the Carhart four-factor model (adding momentum) the best factor models of stock returns? In their September 2014 paper entitled “Digesting Anomalies: An Investment Approach”, Kewei Hou, Chen Xue and Lu Zhang construct the q-factor model comprised of market , size, investment and profitability factors and test its ability to predict stock returns. They also test its ability to account for 80 stock return anomalies (16 momentum-related, 12 value-related, 14 investment-related, 14 profitability-related, 11 related to intangibles and 13 related to trading frictions). Specifically, the q-factor model describes the excess return (relative to the risk-free rate) of a stock via its dependence on:

  1. The market excess return.
  2. The difference in returns between small and big stocks.
  3. The difference in returns between stocks with low and high investment-to-assets ratios (change in total assets divided by lagged total assets).
  4. The difference in returns between high-return on equity (ROE) stocks and low-ROE stocks.

They estimate the q-factors from a triple 2-by-3-by-3 sort on size, investment-to-assets and ROE. They compare the predictive power of this model with the those of the Fama-French and Carhart models. Using returns, market capitalizations and firm accounting data for a broad sample of U.S. stocks during January 1972 through December 2012, they find that: Keep Reading

Forget CAPM Beta?

Does the Capital Asset Pricing Model (CAPM) make predictions useful to investors? In his October 2014 paper entitled “CAPM: an Absurd Model”, Pablo Fernandez argues that the assumptions and predictions of CAPM have no basis in the real world. A key implication of CAPM for investors is that an asset’s expected return relates positively to its expected beta (regression coefficient relative to the expected market risk premium). Based on a survey of related research, he concludes that: Keep Reading

Earnings per Share Growth in the Long Run

Can the U.S. stock market continue to deliver its historical return? In the preliminary draft of his paper entitled “A Pragmatist’s Guide to Long-run Equity Returns, Market Valuation, and the CAPE”, John Golob poses two questions:

  1. What long-run real return should investors expect from U.S. equities?
  2. Do popular metrics reliably indicate when the U.S. equity market is overvalued?

He notes that the body of relevant research presents no consensus on the answers to these questions, which both relate to long-term growth in corporate earnings per share. Recent forecasts for real stock market returns range from as low as 2% to about 6% (close to the 6.5% average since 1871), reflecting disagreements about how slow GDP growth, low dividends, share buybacks and the profitability of retained earnings affect earnings per share growth. The author introduces Federal Reserve Flow of Funds (U.S. Financial Accounts) and S&P 500 aggregate book value to gauge effects of stock buybacks. He also assesses the logic of using Shiller’s cyclically adjusted price-earnings ratio (CAPE or P/E10) as a stock market valuation metric. Using S&P 500 Index price and dividend data, related earnings data and U.S. financial and economic data as available during 1871 through 2013, he concludes that: Keep Reading

Bench the Market Benchmark?

Is the capitalization-weighted market portfolio a lame benchmark? In his August 2014 paper entitled “It’s Easy to Beat the Market”, Moshe Levy tests the perception that it is hard to beat a capitalization-weighted portfolio and therefore that an index so weighted is a challenging benchmark. Specifically, he compares the gross risk-adjusted performance of a capitalization-weighted buy-and-hold portfolio to those of 1,000 random-weighted (normalized to 100%) buy-and-hold portfolios of the same stocks.To ensure liquidity, he restricts the portfolios to the 500 U.S. stocks with the largest market capitalizations at the beginning of 1998. If a stock is delisted during the sample period due to merger/acquisition or bankruptcy, he sets its weight to zero at that point and renormalizes residual portfolios to 100% [per an email exchange with the author]. He focuses on Sharpe ratio and terminal value of an initial investment as key performance metrics. He ignores trading frictions, arguing that no trading is involved other than initial purchases at portfolio formation and reinvestment of dividends. Using daily total (dividend-reinvested) returns for the specified stocks and the contemporaneous 30-day U.S. Treasury bill yield as the risk-free rate during January 1998 through December 2012, he finds that: Keep Reading

The 2014-2023 Equity Risk Premium

What is the best estimate of the Equity Risk Premium (ERP), the return in excess of the risk-free rate required as compensation for the risk of holding equity? In his August 2014 paper entitled “A History of the Equity Risk Premium and its Estimation”, Basil Copeland summarizes recent ERP estimates and explains how the historical equity return can overstate ERP in terms of unanticipated (anomalous) capital gains. He further describes the behavior of historical and expected ERP during 1872 through 2013 and estimates ERP for 2014 through 2023. He discusses ERP estimation issues such as geometric mean versus arithmetic mean and top-down versus bottom-up forecasts. Using data from Shiller for 1871-1959 and from Damodaran for 1960-2013, he finds that: Keep Reading

Preponderance of Evidence Bad for U.S. Stocks?

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

Composite Stock Market Valuation Model

Is there some better predictor of long-term stock market return than the widely cited cyclically adjusted price-earnings ratio (P/E10 or CAPE)? In the July 2014 version of his paper entitled “Forecasting Equity Returns: An Analysis of Macro vs. Micro Earnings and an Introduction of a Composite Valuation Model”, Stephen Jones compares how well several fundamental and economic factors predict real long-term (10-year) equity market total return, with focus on Market Value/Gross Domestic Product (MV/GDP). He compares the predictive power of MV/GDP to those of P/E10 and Tobin’s q. He then constructs a multi-variable forecasting model that includes MV/GDP, a demographic metric and personal income-related variables. Using U.S. data since 1954 for different input variables, he finds that: Keep Reading

2014 Country Equity Risk Premiums from Academia and Practitioners

What are the current academic and practitioner estimates of annual premiums over the risk-free rate demanded in each country by equity investors? In their June 2014 paper entitled “Market Risk Premium Used in 88 Countries in 2014: A Survey with 8,228 Answers”, Pablo Fernandez, Pablo Linares and Isabel Fernandez Acin summarize the results of a May-June 2014 email survey “about the Market Risk Premium (MRP or Equity Premium) that companies, analysts and professors use to calculate the required return on equity in different countries.” Based on 2,022/1,278/1,803/1,968 specific responses to the question from professors/analysts/financial companies/non-financial companies, respectively, around the world, they find that: Keep Reading

Emerging Stock Markets Research Stream

What are the main investment behaviors of emerging markets and component stocks? In their January 2014 paper entitled “Studies of Equity Returns in Emerging Markets: A Literature Review”, Yigit Atilgan, Ozgur Demirtas and Koray Simsek survey the stream of research on emerging markets equity return predictability and volatility. This survey covers articles in the top four finance journals (Journal of Finance, Journal of Financial Economics, Journal of Financial and Quantitative Analysis and Review of Financial Studies) and the three finance journals that focus on emerging markets (Emerging Markets Finance & Trade, Emerging Markets Review and Journal of International Money and Finance). Based on detailed reviews of 54 articles published in these journals over the past three decades, they conclude that: Keep Reading

Basic Equity Return Statistics

What do the basic statistics of stock market returns tell us about risk and predictability? Basic statistics are the measures of the moments of the return distribution: mean (average), standard deviation, skewness and kurtosis. Are these stock market return statistics (and the risk-reward environment they describe) stable over time? Do they reliably relate to future returns? To make the investigation tractable, we calculate these four statistics month-by-month based on daily returns. Using daily closes of the Dow Jones Industrial Average (DJIA) for January 1930 through April 2014 (1012 months) and the S&P 500 index for January 1950 through April 2014 (772 months), we find that: Keep Reading

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