Equity Premium

Which equity markets worldwide offer the best reward-to-risk ratios? In their October 2012 paper entitled “Risk-Adjusted Performances of World Equity Indices”, Yigit Atilgan and Ozgur Demirtas investigate whether 52 developed and emerging market equity indexes compensate investors equally based on reward-to-risk ratios. They consider three reward-to-risk ratios: (1) conventional Sharpe ratio based on monthly return and standard deviation of daily returns over the past 100 trading days; (2) Sharpe ratio substituting non-parametric value at risk (VAR) (magnitude of minimum daily return over past 100 trading days) for standard deviation of returns; and, (3) Sharpe ratio substituting parametric VAR (accounting for return distribution skewness and kurtosis) for standard deviation of returns. The latter two variations of the Sharpe ratio emphasize downside risk and return distribution non-normalities. Using daily returns and monthly total returns in local currencies for 28 developed and 24 emerging market value-weighted indexes, and associated risk-free rates, during January 1973 through December 2011 (38 years), they find that: Keep Reading

How should investors view the predictability of stock market returns and volatility? In sections 5 and 6 of the July 2012 version of his draft chapter entitled “Equity Market Level”, Andrew Ang examines the predictability of the equity risk premium and equity market volatility. He also addresses the exploitability of any predictive power found. Using both theoretical arguments and empirical tests based on long-run data through December 2011, he concludes that: Keep Reading

How does consideration of return distribution tails (not just linear correlations) affect assessment of global equity diversification benefits? In their May 2012 paper entitled “Is the Potential for International Diversification Disappearing? A Dynamic Copula Approach”, Peter Christoffersen, Vihang Errunza, Kris Jacobs and Hugues Langlois examine the evolution of equity market diversification benefits based on a methodology that accommodates non-linearity in the relationship between return streams. They focus on differences between developed and emerging markets. Using weekly returns in U.S. dollar for 16 developed markets during January 1973 through mid-June 2009, 13 emerging markets during late January 1989 through July 2008 and 17 emerging markets during July 1995 through mid-June 2009, they find that: Keep Reading

What is the best way to include the least developed (frontier) stock markets for portfolio diversification? In his December 2011 paper entitled “Frontier Markets: Punching Below their Weight? A Risk Parity Perspective on Asset Allocation”, Jorge Chan-Lau compares the diversification effects of frontier markets within a world equity portfolio based on risk parity and market capitalization weighting approaches. Risk parity equalizes risk contributions across equity classes by assigning the same risk budget to each asset based on co-movement between the asset’s returns and the portfolio returns. The asset allocation comparison assumes five major equity classes: U.S., European including the UK, East Asia and Far East, emerging markets and frontier markets. Co-movement of asset and portfolio returns derive from weekly return measurements over five-year rolling historical windows. Using weekly returns in U.S. dollars for each equity class based on corresponding Morgan Stanley Capital Indexes during June 2002 through November 2011, he finds that: Keep Reading

Should investors believe in the superiority of stocks for the long run and bonds for the short run? In his December 2011 paper entitled “Stocks, Bonds, Risk, and the Holding Period: An International Perspective”, Javier Estrada examines how the absolute and relative risks of stocks and bonds evolve as investment horizon grows (time diversification). Considering both annual and cumulative returns and various measures of variability/risk, he focuses on the question of whether stocks become less risky than bonds for long holding periods. Using annual total returns for stocks and bonds in 19 countries during 1900 through 2009, he finds that: Keep Reading

Are the least developed markets also the least efficient, and therefore the best places to look for alpha? Two recent papers address this question for large, sophisticated investors (institutional funds). In the October 2011 version of their paper entitled “Does Active Management Pay? New International Evidence”, Alexander Dyck, Karl Lins and Lukasz Pomorski examine the performance of the passive and active equity segments of large pension plans allocated to U.S., developed Europe, Australasia and Far East (EAFE) and emerging markets. In the November 2011 version of his paper entitled “Is There Any Alpha in Institutional Emerging Market Equity Funds?”, Wenling Lin examines the performance of institutional emerging market fund managers. Using data from the 1990s and 2000s, they find that: Keep Reading

Do relatively high trading frictions in the least developed equity markets offset associated diversification benefits? In the October 2011 version of their paper entitled “Frontier Market Diversification and Transaction Costs”, Ben Marshall, Nhut Nguyen and Nuttawat Visaltanachoti examine this trade-off in 19 frontier stock markets (Argentina, Bahrain, Bulgaria, Croatia, Estonia, Jordan, Kuwait, Lebanon, Lithuania, Oman, Pakistan, Qatar, Romania, Serbia, Slovenia, Sri Lanka, the United Arab Emirates, Ukraine and Vietnam). They first calculate each month a market capitalization-weighted stock index for each country and then combine country indexes to calculate each month both value-weighted and equal-weighted frontier market indexes. They measure trading frictions such as effective spread, quoted spread and price impact based on monthly averages from high-frequency tick data. Using monthly returns and tick-by-tick trading data for frontier market stocks starting as early as June 2002 for six countries and later for others through 2010, along with contemporaneous benchmark index data, they find that: Keep Reading

What is the state of the equity risk premium across global markets? In the October 2011 version of their paper entitled “Equity Premia Around the World”, Elroy Dimson, Paul Marsh, and Mike Staunton update their estimates of equity risk premiums for 19 country markets and a worldwide aggregate relative to both short-term government bills and long-term government bonds over a period of 111 years. They report local currency and dollar-based real returns and the historical equity premium for each country, and they decompose the premium into dividends, dividend growth, multiple expansion and change in real exchange rate. All aggregates are value-weighted. Using stock, bond, bill, inflation and currency returns for the period 1900 through 2010, they find that: Keep Reading

What do leading textbooks have to say about the excess return you got, should expect, should require or should infer from the market for taking the risk of owning stocks? In the July 2011 version of his paper entitled “The Equity Premium in 150 Textbooks”, Pablo Fernandez reviews definitions and values of the equity risk premium offered in 150 finance and valuation textbooks published from 1979 to 2009. Based on this review, he finds that: Keep Reading

Do technical indicators add value to fundamental indicators in assessing broad stock market valuation? In their March 2011 paper entitled “Forecasting the Equity Risk Premium: The Role of Technical Indicators”, Christopher Neely, David Rapach, Jun Tu and Guofu Zhou examine the powers of technical and fundamental indicators to predict stock market returns. They consider 12 variations of three stock market index technical indicators: (1) relative values of two moving averages (1 month versus 3, 6, 9 and 12 months); (2) return momentum (past 3, 6, 9 and 12 months); and, (3) relative values of two on-balance volume moving averages (1 month versus 3, 6, 9 and 12 months). They consider 14 fundamental indicators ranging from stock market valuation ratios to Treasury yields, yield spreads and the default spread. They compare mean squared equity risk premium forecast errors for technical and fundamental indicators to that for the historical average premium. They also compare the average utility gain for a mean-variance investor who allocates monthly between stocks and Treasury bills based on either technical or fundamental market forecasts to that for an investor who uses the historical average premium. Finally, they generate equity risk premium forecasts based on a rolling principal component analysis that encapsulates the predictive powers of the 26 technical and fundamental indicators into three or four variables. Using monthly price and volume data for the dividend-adjusted S&P 500 Index and monthly readings of the 14 U.S. fundamental indicators as available over the period 1927 through 2008 (1926-1959 for in-sample optimization and 1960–2008 for out-of-sample testing), along with NBER business expansion and contraction dates, they find that: Keep Reading