Strategic Allocation

Alternative assets (private equity, private market real estate, hedge funds and other assets apart from stocks and bonds) constitute approximately 30% of U.S. public pension fund portfolios and 60% of large U.S. endowment portfolios. Are they beneficial? In his August 2023 paper entitled “Have Alternative Investments Helped or Hurt?”, Richard Ennis examines impacts of alternative assets on 59 pension fund portfolios, individually and in equal-weighted composite. His key performance metric is alpha relative to static allocations to a mix of stock and bond indexes selected to match the style of each pension fund (or composite of funds) by statistical returns fitting. The stock and bond index choices are Russell 3000 stock index, MSCI ACWI ex-US stock index (hedged and unhedged) and Bloomberg US Aggregate bond index. He thereby creates a unique benchmark for each fund with which to measure its alpha. Using returns and allocations for 59 large U.S. public pension funds with a common June 30 year-end and returns for the benchmarking stock and bond indexes during 2009 through 2021, he finds that: Keep Reading

Are the “Simple Asset Class ETF Value Strategy” (SACEVS) and the “Simple Asset Class ETF Momentum Strategy” (SACEMS) mutually diversifying. To check, based on feedback from subscribers about combinations of interest, we look at three equal-weighted (50-50) combinations of the two strategies, rebalanced monthly:

1. 50-50 Best Value – EW Top 2: SACEVS Best Value paired with SACEMS Equally Weighted (EW) Top 2 (aggressive value and somewhat aggressive momentum).
2. 50-50 Best Value – EW Top 3: SACEVS Best Value paired with SACEMS EW Top 3 (aggressive value and diversified momentum).
3. 50-50 Weighted – EW Top 3: SACEVS Weighted paired with SACEMS EW Top 3 (diversified value and diversified momentum).

We consider as a benchmark a simple technical strategy (SPY:SMA10) that holds SPDR S&P 500 ETF Trust (SPY) when the S&P 500 Index is above its 10-month simple moving average and 3-month U.S. Treasury bills (Cash, or T-bills) when below. We also test sensitivity of results to deviating from equal SACEVS-SACEMS weights. Using monthly gross returns for SACEVS, SACEMS, SPY and T-bills during July 2006 through July 2023, we find that: Keep Reading

A subscriber requested comparison of four variations of an “Ivy 5” asset class allocation strategy, as follows:

1. Ivy 5 EW: Assign equal weight (EW), meaning 20%, to each of the five positions and rebalance annually.
2. Ivy 5 EW + SMA10: Same as Ivy 5 EW, but take to cash any position for which the asset is below its 10-month simple moving average (SMA10).
3. Ivy 5 Volatility Cap: Allocate to each position a percentage up to 20% such that the position has an expected annualized volatility of no more than 10% based on daily volatility over the past month, recalculated monthly. If under 20%, allocate the balance of the position to cash.
4. Ivy 5 Volatility Cap + SMA10: Same as Ivy 5 Volatility Cap, but take completely to cash any position for which the asset is below its SMA10.

To perform the tests, we employ the following five asset class proxies:

iShares 7-10 Year Treasury Bond ETF (IEF)
SPDR S&P 500 ETF Trust (SPY)
Vanguard Real Estate Index Fund (VNQ)
iShares MSCI EAFE ETF (EFA)
Invesco DB Commodity Index Tracking Fund (DBC)

We consider monthly performance statistics, annual performance statistics, and full-sample compound annual growth rate (CAGR) and maximum drawdown (MaxDD). Annual Sharpe ratio uses average monthly yield on 3-month U.S. Treasury bills (T-bills) as the risk-free rate. The DBC series in combination with the SMA10 rule are limiting with respect to sample start date and the first return calculations. Using daily and monthly dividend-adjusted closing prices for the five asset class proxies and T-bill yield as return on cash during February 2006 through July 2023, we find that:

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What conditions affect the correlation between stock and bond returns, a critical input to asset allocation decisions? In their July 2023 paper entitled “Empirical Evidence on the Stock-Bond Correlation”, Roderick Molenaar, Edouard Senechal, Laurens Swinkels and Zhenping Wang relate changes in this correlation to economic variables and analyze the implications of such changes for stock-bond portfolios. They employ rolling 36-month Spearman rank correlations for stock market and 10-year government bond returns to detect correlation changes. While considering longer periods, they focus on post-1952 monthly and post-1978 daily U.S. data (after Federal Reserve independence) as most representative of the future. Using stock and bond returns and economic data starting 1875 for the U.S., 1801 for the UK, 1871 in France and 1987 for Canada, Germany, Italy and Japan, all through 2021, they find that:

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Subscribers asked why the Simple Asset Class ETF Value Strategy (SACEVS) signaled an apparently dramatic change in allocations at the end of June. SACEVS seeks a monthly tactical edge from timing three risk premiums associated with U.S. Treasury notes, corporate bonds and stocks:

1. Term – monthly difference between the 10-year Constant Maturity U.S. Treasury note (T-note) yield and the 3-month Constant Maturity U.S. Treasury bill (T-bill) yield.
2. Credit – monthly difference between the  Moody’s Seasoned Baa Corporate Bonds yield and the T-note yield.
3. Equity – monthly difference between S&P 500 operating earnings yield and the T-note yield.

At the end of each month, the Best Value version of SACEVS picks the most undervalued premium (if any). The Weighted version of SACEVS weights all undervalued premiums (if any) according to degree of undervaluation. Using monthly SACEVS inputs during March 1989 through June 2023, we find that: Keep Reading

A subscriber asked about the performance of a strategy that each month rebalances to 60% international equities and 40% international corporate bonds (both non-U.S.), and how this performance compares to that of a portfolio that each month allocates 50% to Simple Asset Class ETF Value Strategy (SACEVS) Best Value and 50% to Simple Asset Class ETF Momentum Strategy (SACEMS) equal-weighted (EW) Top 2. To investigate, we use:

• iShares MSCI ACWI ex U.S. ETF (ACWX) to represent international equities.
• SPDR Bloomberg International Corporate Bond ETF (IBND) to represent international corporate bonds.

We begin the test at the end of May 2010, limited by IBND inception. We ignore monthly rebalancing frictions for both strategies. Using monthly dividend-adjusted prices for ACWX and IBND starting May 2010 and monthly gross returns for SACEVS Best Value-SACEMS EW Top 2 50-50 starting June 2010, all through May 2023, we find that: Keep Reading

In response to “Tech Premium Boost for Simplest Asset Class Momentum Strategy?”, a subscriber asked about testing the combination of Vanguard Growth Index Fund (VUG) and Vanguard Total Bond Market Index Fund (BND) in the “Simplest Asset Class ETF Momentum Strategy?”, which each month holds SPDR S&P 500 (SPY) or iShares Barclays 20+ Year Treasury Bond (TLT) depending on which has the higher total return over the last three months. To investigate, we run a horse race between the strategy executed with SPY and TLT (SPY-TLT), the strategy executed with Invesco QQQ Trust (QQQ) and TLT (QQQ-TLT) and the requested alternative (VUG-BND). We focus on compound annual growth rates (CAGR) and maximum drawdowns (MaxDD) as performance metrics and assess robustness across lookback intervals of one to 12 months. Using monthly dividend-adjusted prices for SPY, QQQ, VUG, TLT and BND during April 2007 (limited by BND) through May 2023, we find that:

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A subscriber requested evaluation of a streamlined version of the Simple Asset Class ETF Momentum Strategy (SACEMS) that considers only three exchange-traded funds (ETF):

• SPDR S&P 500 (SPY)
• iShares Barclays 20+ Year Treasury Bond (TLT)
• iShares iBoxx $ Investment Grade Corporate Bond (LQD)

To evaluate, we test a strategy that each month picks the one of these ETFs with the highest total return over a set momentum ranking (lookback) interval. We call the strategy Very Simple SACEMS (VSACEMS) Top 1. We consider lookback intervals of one to 12 months. We then select one of these lookback intervals and generate performance statistics similar to those for SACEMS. We consider three benchmarks:

1. SPY – buy and hold SPY.
2. SPY:SMA10 Cash – Hold SPY (3-month U.S. Treasury bills) when SPY is above (below) its 10-month simple moving average (SMA10) at the end of the prior month.
3. SPY:SMA10 TLT – Hold SPY (TLT) when SPY is above (below) its SMA10 at the end of the prior month.

Using monthly dividend-adjusted prices for the above three assets during July 2002 (limited by TLT and LQD) through May 2023, we find that: Keep Reading

Which alternative risk premiums (ARP) protect against stock and bond market crashes via return correlations/betas that remain low during such events? In their May 2023 paper entitled “Does Alternative Risk Premia Diversify? New Evidence for the Post-Pandemic Era”, Antti Suhonen and Kari Vatanen employ recent data to re-examine ARP risk and diversification properties, focusing on drawdown intervals for stocks and bonds. They categorize ARP strategies as offensive (risk-on) or defensive (risk-off) based on respective equity market interactions. For robustness, they consider several drawdown metrics. Using weekly data for 27 “pure” factors spanning five asset classes (commodity, credit, equity, fixed income and currency exchange) and 10 ARP strategies (backwardation, carry, congestion, low volatility, momentum, quality, size, trend, value and volatility) from PremiaLab during January 2007 through mid-October 2022, they find that:

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In his 2023 book, The Uncertainty Solution: How to Invest with Confidence in the Face of the Unknown, author John Jennings seeks “to provide individual investors with mental models that will help them make better investment decisions, practice better investment behavior, and be better consumers of investment advice… This book is not about how to invest but rather how to think about investing. It is the culmination of my thirteen-year quest for investment wisdom… The mental models in this book describe the investment world as full of uncertainty, wild randomness, unpredictability, and pitfalls. There’s no easy path. But mental models that embrace reality—that take the world as it is, not how we think it is or want it to be—will make you a better investor and a better consumer of investment advice.” Based on his many years of wealth management experience, especially during the 2007-2008 Financial Crisis, he concludes that:

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