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Strategic Allocation

Is there a best way to select and weight asset classes for long-term diversification benefits? These blog entries address this strategic allocation question.

Essential Versus Asset Class Risk Allocation

How can a risk parity allocation strategy, equally weighting portfolio components by expected risk contribution, not really spread risk? In their October 2012 paper entitled “The Risk in Risk Parity: A Factor Based Analysis of Asset Based Risk Parity”, Vineer Bhansali, Josh Davis, Graham Rennison, Jason Hsu and Feifei Li examine the essential return and risk drivers embedded in a risk parity diversification strategy applied to multiple asset classes. They apply principal component analysis to extract independent (essential) risk factors from return streams for nine conventional asset classes: U.S. equities; international developed market equities; emerging market equities; real estate investment trusts (REIT); commodities; global bonds; long-maturity U.S. Treasuries; investment-grade corporate bonds; and, high-yield bonds. They then test four commercially available risk parity strategy implementations for dependence on the top two essential risk factors, interpreted as risks to global economic growth (proxied by S&P 500 Index returns) and global inflation (proxied by 10-year Treasury note returns). Using returns for the risk factor proxies and the four commercial risk parity portfolios from portfolio inceptions (ranging from January 1990 to July 2009) through May 2012, they find that: Keep Reading

Benefits of Investing in Emerging Equity Markets

How can positions in emerging equity markets benefit investment portfolios? In their October 2012 paper entitled “How Large are the Benefits of Emerging Market Equities?”, Mitchell Conover, Gerald Jensen and Robert Johnson examine the returns of emerging equity markets with focus on: (1) performance measures that account for return distribution risk and abnormalities; (2) performance by region; and, (3) effects of global economic/monetary environment on returns and diversification power. Using monthly local-currency and dollar-denominated stock index returns and annual GDP estimates for 20 emerging markets as available, along with monthly returns for MSCI developed market MSCI indexes (including MSCI World and MSCI USA) for comparison, during January 1976 through December 2010, they find that: Keep Reading

Volatility-based Equity Market Allocations

Do allocations aimed at managing volatility beat simple equal weighting as applied to the cheapest third of 32 country stock markets based on 10-year cyclically adjusted price-to-earnings ratio (CAPE, or P/E10). In their October 2012 paper entitled “Global CAPE Model Optimization”, Adam Butler, Michael Philbrick, Rodrigo Gordillo and Mebane Faber compare the following six volatility management strategies to EW for a low-P/E10 equity index portfolio:

  1. Equal Volatility: each selected index contributes equally to the volatility of a fully invested portfolio.
  2. Fixed Volatility Limit: allocates to each selected index up to a daily volatility limit of 1%, with any remaining funds going to cash.
  3. Portfolio Volatility Target: allocates equally to all selected indexes with a portfolio-level annualized volatility target of 10%, going to cash when above target (but not applying leverage when below).
  4. Risk Parity with Portfolio Volatility Target: a combination of strategies 1 and 3; allocates such that all indexes contribute equally to portfolio volatility with a portfolio-level annualized volatility target of 10%, going to cash when above target (but not applying leverage when below).
  5. Minimum Variance: minimum variance via a combination of low volatilities and low correlations per Modern Portfolio Theory, but always fully invested. 
  6. Minimum Variance with Portfolio Volatility Target: minimum variance allocations adjusted at the portfolio level to target 10% annualized portfolio volatility, going to cash when above target (but not applying leverage when below).

For all strategies, they estimate prescribed volatilities based on the last 60 days of returns, with monthly portfolio reformation. Using daily and monthly total returns for the 32 country stock indexes during April 1999 through August 2012, they find that: Keep Reading

How Important Is Strategic Allocation?

What is the most important aspect of long-term investing? In the July 2012 version of his paper entitled “Strategic Asset Allocation and Portfolio Performance”, Lujer Santacruz assesses the importance of strategic asset class allocation compared to other sources of returns for a set of Australian managed funds. He specifies three fund return components as: (1) strategic allocation, derived from asset class benchmark returns weighted according to stated fund targets; (2) timing, derived from the difference between actual and target fund asset class weights; and, (3) security selection, derived from the difference between actual and benchmark asset class returns. Using actual quarterly total returns, target asset class allocations and actual asset class allocations for Vanguard’s four diversified Australian funds (Conservative, Balanced, Growth and High Growth), along with quarterly returns for six relevant benchmark indexes, during January 2003 through June 2012, he finds that: Keep Reading

Assessment of Risk Parity Asset Allocation

How does the risk parity asset allocation strategy (equalizing the volatility contributions of portfolio components) fare in comparison to other commonly used strategies? In their March 2012 research note entitled “The Risk Parity Approach to Asset Allocation – Climbing the Wall of Worries?”, Fabian Dori, Frank Haeusler, Manuel Krieger, Urs Schubiger and David Stefanovits contrast three popular allocation strategies: (1) traditional balanced (40% equities, 50% bonds and 10% commodities); (2) minimum variance (the mean-variance optimized portfolio with the lowest variance); and, (3) risk parity. Their asset universe includes equity index futures (FTSE 100, DAX, S&P 500, TOPIX and ASX SPI 200), 10-year government bond futures (UK, German, U.S., Japanese and Australian) and commodity index futures (GSCI agriculture, energy, industrial and precious metals and softs). For each asset allocation strategy, they model daily rebalancing of assets to specified weights. Using daily futures return data during August 1992 through June 2012, they find that: Keep Reading

Common Factor Exposures of Specialized Stock Indexes

How do specialized stock indexes relate to commonly used equity risk factors? In his February 2012 paper entitled “Evaluating Alternative Beta Strategies”, Xiaowei Kang examines risk exposures (betas), construction methodologies and historical performances of alternative stock indexes such as those based on value, low-volatility and diversification strategies. He considers five risk factors: (1) market, representing excess return of the market capitalization-weighted U.S. stock market; (2) size, representing return from a portfolio that is long small-cap stocks and short large-cap stocks; (3) value, representing return from a portfolio that is long high book-to-market stocks and short low book-to-market stocks; (4) momentum, representing return from a portfolio that is long past winning stocks and short past losing stocks; and, (5) volatility, representing return from a portfolio that is long high-volatility stocks and short low-volatility stocks. Using monthly returns for several specialized indexes and the specified risk factors as available through 2011, he finds that: Keep Reading

Diversification Power of Commodities

Are commodities effective diversifiers for stocks and bonds? In his September 2012 paper entitled “Commodity Investments: The Missing Piece of the Portfolio Puzzle?”, Xiaowei Kang examines the diversification properties of commodity indexes relative to stock and bond indexes. He focuses on the widely used S&P GSCI, composed of 24 commodities with liquid futures markets weighted by world production value. He also considers the S&P GSCI Dynamic Roll, designed to suppress negative roll returns by rolling into longer-dated (nearby) futures contracts when a commodity’s term structure is in contango (backwardation). Using monthly levels of these indexes, MSCI World (to represent stocks) and Barclays Global Aggregate Bond Index (to represent bonds), along with contemporaneous U.S. Treasury bill yields to calculate excess returns, from as early as December 1970 through June 2012, he finds that: Keep Reading

Managed Futures as Portfolio Diversifier

Are managed futures programs good portfolio diversifiers? In his September 2012 paper entitled “Revisiting Kat’s Managed Futures and Hedge Funds: A Match Made in Heaven”, Thomas Rollinger updates prior research exploring the diversification effects of adding managed futures to traditional portfolios of stocks and bonds and to portfolios including stocks, bonds and hedge funds. His proxies for the four asset classes are: (1) for stocks, the S&P 500 Total Return Index; (2) for bonds, the Barclays U.S. Aggregate Bond Index; (3) for hedge funds, the HFRI Fund Weighted Composite Index; and, (4) for managed futures programs, the Barclay Systematic Traders Index (focused on systematic trend-following strategies). He assumes monthly (frictionless) portfolio rebalancing. Using monthly returns for the four asset class indexes during June 2001 through December 2011, he finds that: Keep Reading

Gold as Diversifier Versus Safe Haven

Has increasing use of gold as a portfolio diversifier changed the response of its price to crises? In their August 2012 paper entitled “The Destruction of a Safe Haven Asset?”, Dirk Baur and Kristoffer Glover examine the potential of investor behavior to extinguish the safe haven property of gold. Specifically, they consider how widespread inclusion of gold as a diversifier in investment portfolios affects gold price behavior in times of crisis. Based on theoretical conjecture and price data for gold during major financial market crises, they conclude that: Keep Reading

Tests of Strategic Allocations Based on Risk Metrics

Risk-focused asset allocation strategies derive from evidence that forecasting asset return volatility is easier than forecasting average return. Is there a best risk-focused strategy? In his September 2012 paper entitled “A Small Survey of Quantitative Models that Discard Estimation of Expected Returns for Portfolio Construction”, Stefano Colucci compares asset allocation strategies that rely on forecasted asset risk metrics but not on forecasted average returns. Specifically, he compares future gross annualized return-risk ratios, Ulcer indexes, one-month maximum drawdowns and average monthly portfolio turnovers for the following asset allocation strategies:

  1. Minimum Variance (least volatile, or left-most, efficient portfolio per Modern Portfolio Theory).
  2. Minimum Expected Shortfall with weightings estimated by Monte Carlo simulation.
  3. Equal Risk Contribution (each asset weighted by the inverse of its forecasted maximum expected shortfall).
  4. Maximum Diversification (related to expected shortfall with weightings again estimated by numerical simulation).
  5. Risk Parity (each asset weighted by the inverse of its portfolio volatility contribution).
  6. Equal Weighting (requiring neither average return nor volatility forecasts) as a benchmark.

He reforms portfolios every 20 trading days (approximately monthly) and estimates future risk metrics based on a rolling historical window of 500 trading days (approximately two years). Using daily returns over recent periods for stock and bond indexes and individual stocks segregated into several asset selection universes, he finds that: Keep Reading

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