Strategic Allocation

Has the academic community made practical progress in specifying asset allocation approaches that mitigate adverse impacts of multi-market crises (systemic risk) on diversified portfolios? Two recent papers address this question in complementary top-down and bottom-up ways. The February 2011 version of “Asset Allocation and Asset Pricing in the Face of Systemic Risk: A Literature Overview and Assessment” by Christoph Meinerding assesses recent research linking systemic risk with asset pricing and asset allocation, with systemic risk essentially characterized by the empirical properties of contagion. The 2011 paper “Fat-Tailed Models for Risk Estimation” by Stoyan Stoyanov, Svetlozar Rachev, Boryana Racheva-Iotova and Frank Fabozzi reviews mathematical approaches for modeling return distributions that match empirical data. Based on the relevant bodies of research, these papers conclude that: Keep Reading

Does combining avoidance of fat tail losses with a traditional portfolio optimization strategy enhance performance? In her January 2011 paper entitled “The Economic Value of Controlling for Large Losses in Portfolio Selection”, Alexandra Dias investigates the effectiveness of combining tail loss risk management with minimum variance efficiency. This approach essentially seeks to add avoidance of Black Swans to the benefit of diversification. The investigation consists of testing four long-only strategies using 224 months of rolling historical returns on all possible combinations of three Dow Jones Industrial Average (DJIA) stocks by choosing each month: (1) the minimum variance portfolio with the smallest variance (benchmark strategy); (2) the minimum variance portfolio with the smallest probability of a large loss; (3) the minimum variance portfolio with the thinnest losses tail; and, (4) the minimum Value at Risk (VaR) portfolio with the smallest VaR. Strategies (2), (3) and (4) are alternatives for managing return distribution tail risk. Using monthly returns for the 24 DJIA stocks for which which prices are available during February 1973 through June 2010 (allowing 2,024 combinations of three stocks), she finds that: Keep Reading

Can investors straightforwardly diversify equity portfolios with volatility futures? In the January 2011 draft of their paper entitled “The Hazards of Volatility Diversification”, Carol Alexander and Dimitris Korovilas explore the potential benefits and costs of combining ‘buy-and-hold’ positions in volatility futures with a long-term equity portfolio. Specifically, they examine diversification of long exposure to the S&P 500 Index via S&P Depository Receipts (SPY) with a rolling long position in VIX futures. They distinguish “diversification” from “hedging” based on permanence of positions. They consider three VIX futures strategies using one-month-to-expiration, three-month-to-expiration or longest-maturity-available series, with rollover either at or five business days before expiration. Using daily trading data for VIX futures, SPY and the 1-month Treasury bills from March 26, 2004 through December 31, 2010 (about 69 months), they find that: Keep Reading

What approach to diversifying equity holdings across industries and global geographies is most sensible? In the October 2010 version of his paper entitled “Assessing Alternative Global Equity Investment Frameworks”, Xi Li compares the feasibility and optimality of eight possible approaches for grouping of stocks by geography and industry/sector. He compares feasibility of diversification grouping approaches based on a requirement that each group has at least 15 stocks, such that groups exhibit reasonably reliable behavior. He compares optimality of  diversification grouping approaches based on ability to explain the variation in returns across groups (effectiveness in grouping similar stocks). Using monthly returns for mostly large and medium capitalization stocks of 23 developed country markets assigned to three regions (Americas, Asia Pacific and Europe), 10 sectors and 24 industries over the period July 1989 through March 2010 fewer, he finds that: Keep Reading

In his 2011 book The Power of Passive Investing: More Wealth with Less Work, author Richard Ferri presents “the detailed studies and undeniable evidence favoring a passive investing approach. …This information clearly shows that trying to beat the market has never been a reliable investment strategy in the past, and there’s no reason to believe it will beat a passive approach in the future. …Attempting to earn above market returns by picking actively managed mutual funds is an inefficient use of time and money. Knowing this fact, and acknowledging it allows you the freedom to go in a different direction–to change religion in a sense. …This book makes the case for passive investing. You’ll have to read other books for details on asset allocation recommendations and fund selection methods.” The book includes 140 citations of formal studies and expert commentaries. Some notable points from the book are: Keep Reading

Are Real Estate Investment Trusts (REIT) as an asset class a good diversifier for the stock market? To check, we focus on monthly correlation of returns as a measure of diversification capacity for Vanguard REIT Index Fund Investor Shares (VGSIX), a mutual fund with a reasonably long track record “designed to track the performance of the MSCI US REIT Index.” We use S&P 500 Depository Receipts (SPY) as a proxy for the broad U.S. stock market. For comparison, we also consider returns for three REIT Exchange-Traded Funds (ETF): iShares Dow Jones US Real Estate (IYR), SPDR Dow Jones REIT (RWR), and Vanguard REIT Index ETF (VNQ). Using monthly dividend-adjusted returns for VGSIX and SPY for the period July 1996 through December 2010 (174 monthly returns), we find that: Keep Reading

Many asset class allocation, asset valuation/selection and asset return anomaly studies ignore or treat lightly the implications of liquidity constraints. What are those implications and how serious are they? In his December 2010 paper entitled “Comatose Markets: What If Liquidity is Not the Norm?”, Aswath Damodaran examines how introducing illiquidity into decision processes affects investors with different time horizons and investment strategies. He focuses on trading friction (brokerage fees, bid-ask spread and price impact) as an illiquidity measurement. Using results from prior research and recent data on liquidity variations within and across asset classes, he finds that: Keep Reading

How effectively and consistently do equities, bonds, oil, gold and the dollar serve as hedges and safe havens for each other? In their September 2010 paper entitled “Hedges and Safe Havens – An Examination of Stocks, Bonds, Oil, Gold and the Dollar”, Cetin Ciner, Constantin Gurdgiev and Brian Lucey investigate pairwise hedging and safe haven relationships among these five major assets/asset classes. The define an asset as a hedge (safe haven) for another if respective returns are uncorrelated or negatively correlated on average over the long term (during relatively short intervals of stress). They define the long term (relatively short intervals) as their entire sample period (rolling four-month subperiods). They define intervals of stress as returns in the lowest fourth of observations. Using daily levels of the S&P 500 Index, an index of 10-year Treasuries, nearest-month gold and oil futures and the Federal Reserve Nominal Trade Weighted Effective Index for the dollar from January 1985 through October 2009 (nearly 25 years), they find that: Keep Reading

Market capitalization is the most frequently used metric for weighting the individual stock components of market indexes. Other approaches range from equal weighting to weighting on firm fundamentals to weighting generated by return-risk optimization. How do such alternative metrics work empirically? In the October 2010 draft of their paper entitled “A Survey of Alternative Equity Index Strategies”, Tzee-man Chow, Jason Hsu, Vitali Kalesnik and Bryce Little examine several popular passive index weighting alternatives to market capitalization. They impose common assumptions to backtest these alternatives on U.S. and global equity data over long periods with either annual or quarterly rebalancing. They also apply the Fama-French three-factor model to investigate sources of outperformance relative to capitalization-weighted benchmarks. Using stock/firm data for the 1,000 largest global firms spanning 1987-2009 and for the largest 1,000 U.S. firms spanning 1964-2009, they find that: Keep Reading

How stable are risk premiums? How should investors respond to instabilities? In his August 2010 paper entitled “A New ‘Risky’ World Order: Unstable Risk Premiums: Implications for Practice”, Aswath Damodaran presents approaches for estimating equity, bond and real asset risk premiums that are imprecise, unstable and linked across markets. He also explores the implications of dynamic, linked premiums for asset allocation, market timing and asset valuation. Using long-run data for all three asset classes, he concludes that: Keep Reading