Strategic Allocation

Subscribers asked whether substituting Invesco QQQ Trust (QQQ) for SPDR S&P 500 (SPY) in the Simple Asset Class ETF Value Strategy (SACEVS) and the Simple Asset Class ETF Momentum Strategy (SACEMS) improves outcomes. To investigate, we substitute monthly QQQ dividend-adjusted returns for SPY dividend-adjusted returns in the two model strategies. We then compare the modified performance with the original baseline performance, including: gross compound annual growth rates (CAGR) at various horizons, average gross annual returns, standard deviations of gross annual returns, gross annual Sharpe ratios and maximum drawdowns (MaxDD) based on monthly measurements. In Sharpe ratio calculations, we employ the average monthly yield on 3-month U.S. Treasury bills during a year as the risk-free rate for that year. Using the specified methodology and data to generate SACEVS monthly returns starting August 2002 and SACEMS monthly returns starting July 2006, all through March 2025, we find that:

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Can large language models (LLM) help improve portfolio performance metrics, portfolio optimization and strategy feature discovery? In his three January-February 2025 papers entitled “AlphaSharpe: LLM-Driven Discovery of Robust Risk-Adjusted Metrics”, “AlphaPortfolio: Discovery of Portfolio Optimization and Allocation Methods Using LLMs” and “AlphaQuant: LLM-Driven Automated Robust Feature Engineering for Quantitative Finance”, Kamer Yuksel explores use of specially trained LLMs to discover new:

• Enhanced portfolio risk-return metrics that outperform traditional approaches such as Sharpe ratio.
• Better portfolio optimization methods.
• Robust investment strategy features.

The development processes are iterative for continuous improvement. He assesses usefulness of discoveries with 15 years of historical data for 3,246 US stocks and ETFs, of which he uses the last few years for out-of-sample equal-weighted portfolio testing. Using these methods and this dataset, he finds that:

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We have updated monthly allocations and performance data for the Simple Asset Class ETF Momentum Strategy (SACEMS) and the Simple Asset Class ETF Value Strategy (SACEVS). We have also updated performance data for the Combined Value-Momentum Strategy.

We have updated the Trading Calendar to incorporate data for March 2025.

The home page, Simple Asset Class ETF Momentum Strategy (SACEMS) and Simple Asset Class ETF Value Strategy (SACEVS) now show preliminary positions for April 2025. SACEMS rankings probably will not change by the close. SACEVS allocations are unlikely to change by the close.

The “Simple Asset Class ETF Value Strategy” (SACEVS) seeks diversification across a small set of asset class exchanged-traded funds (ETF), plus a monthly tactical edge from potential undervaluation of three risk premiums:

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.

Premium valuations are relative to historical averages. How might this strategy react to changes in the Effective Federal Funds Rate (EFFR)? Using end-of-month values of the three risk premiums, EFFR, total 12-month U.S. inflation and core 12-month U.S. inflation during March 1989 (limited by availability of operating earnings data) through February 2025, we find that: Keep Reading

Can investors use leveraged exchange-traded funds (ETF) to construct attractive versions of simple 60%/40% (60/40) and 40%/60% (40/60) stocks-bonds portfolios? In their March 2020 presentation package entitled “Robust Leveraged ETF Portfolios Extending Classic 40/60 Portfolios and Portfolio Insurance”, flagged by a subscriber, Mikhail Smirnov and Alexander Smirnov consider several variations of classic stocks/bonds portfolios implemented with leveraged ETFs. They ultimately focus on a monthly rebalanced partially 3X-leveraged portfolio consisting of:

• 40% ProShares UltraPro QQQ (TQQQ)
• 20% Direxion Daily 20+ Year Treasury Bull 3X Shares (TMF)
• 40% iShares 20+ Year Treasury Bond ETF (TLT)

To validate findings, we consider this portfolio and several 60/40 and 40/60 stocks/bonds portfolios. We look at net monthly performance statistics, along with compound annual growth rate (CAGR), maximum drawdown (MaxDD) based on monthly data and annual Sharpe ratio. To estimate monthly rebalancing frictions, we use 0.5% of amount traded each month. We use average monthly 3-month U.S. Treasury bill yield during a year as the risk-free rate in Sharpe ratio calculations for that year. Using monthly adjusted prices for TQQQ, TMF, TLT and for SPDR S&P 500 ETF Trust (SPY) and Invesco QQQ Trust (QQQ) to construct benchmarks during February 2010 (limited by TQQQ inception) through February 2025, we find that: Keep Reading

A subscriber suggested adding U.S. large-capitalization growth and value funds to the asset class proxy universe in the Simple Asset Class ETF Momentum Strategy (SACEMS) to capture associated growth and value streakiness. To investigate, we select Vanguard Growth Index Fund ETF Shares (VUG) and Vanguard Value Index Fund ETF Shares (VTV) as growth and value proxies. We compare performance statistics for SACEMS Top 1, equal-weighted (EW) Top 2 and EW Top 3 portfolios for:

1. SPY – Baseline SACEMS with SPDR S&P 500 ETF Trust (SPY) as a proxy for U.S. large-capitalization stocks.
2. SPY/VUG/VTV – SACEMS with VUG and VTV added.
3. VUG/VTV – SACEMS with VUG and VTV but without SPY to limit the overall tilt toward U.S. large-capitalization stocks.
4. VUG – SACEMS with VUG substituted for SPY to assess the benefit of growth alone versus value-growth switching.
5. QQQ – SACEMS with Invesco QQQ Trust (QQQ) substituted for SPY to compare VUG versus QQQ as large-capitalization growth stock proxies.

We focus on gross compound annual growth rate (CAGR), maximum drawdown (MaxDD) based on monthly measurements and annual Sharpe ratio (with excess annual return calculated using average monthly yield on 3-month U.S. Treasury bills during a year as the risk-free rate for that year) as key performance statistics. Using monthly dividend-adjusted returns for baseline SACEMS assets, VUG, VTV and QQQ during February 2006 through February 2025, we find that:

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Has concentration of world equity market capitalization in a few technology megacaps disrupted factor investing? In his short February 2025 paper entitled “Implications of Increased Index Concentration for Active Investors”, David Blitz examines implications of the rise of megacap technology stocks for factor portfolio management. He first considers strategies that focus on capturing a single premium from among quality, momentum or low-volatility factors without tracking error control relative to a world index. He then looks at multi-factor strategies with tracking control. Using megacap/world market capitalizations and MSCI World Quality, Momentum, Minimum Volatility and overall market index returns during 2018 through 2024, he finds that: Keep Reading

What is the best type of account to use for a Treasury Inflation Protected Securities (TIPS) ladder, constructed with incremental maturities to generate a constant risk-free stream of real future withdrawals via compounded inflation adjustments? In his February 2025 paper entitled “Best Asset Location for a TIPS Ladder”, Edward McQuarrie models TIPS behaviors and tax rules to determine whether investors should hold TIPS ladders in: a taxable brokerage account; a tax-deferred account such as a 401(k) or traditional IRA; or, a tax-free account such as a Roth IRA. Potential tax treatments of TIPS ladder account withdrawals include:

1. Maturing principal (initial capital), which is not taxed.
2. Ordinary income (coupon).
3. Tax-favored income, such as qualified dividends or long-term capital gains, with a rate as low as half that for ordinary income.

Only taxable brokerage accounts encounter all three treatments. All withdrawals from tax-deferred accounts are treated as ordinary income. Roth withdrawals are always tax-free. His baseline case is a 20-year TIPS ladder with $1 million initial funding, assuming a 2% real coupon at purchase with all maturities and coupon payments occurring at year-end. He initially assumes a 3% annual inflation rate but considers rates varying from 1% to 9%. He focuses on a 24% income tax rate. He discusses Original Issue Discount (OID), unrealized inflation adjustments, which is crucial to differences in tax rates across account types. Based on this modeling, he concludes that:

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“SACEVS and SACEMS Strategy Momentum?” finds support for belief that a strategy exploiting the relative performance of Simple Asset Class ETF Value Strategy (SACEVS) Best Value and Simple Asset Class ETF Momentum Strategy (SACEMS) Equal-Weighted (EW) Top 2 boosts performance, with focus on a 60%-40% tilt toward the strategy with the stronger past returns. It also considers a full tilt (100%-0%) toward the stronger strategy for one lookback interval. Here, we examine sensitivity of the performance of the full tilt alternative (SACEVS-SACEMS Momentum) across lookback intervals ranging from one to 12 months. This alternative holds either SACEVS Best Value or SACEMS EW Top 2 according to which has the higher past return. We focus on gross compound annual growth rate (CAGR) and gross maximum drawdown (MaxDD) as essential performance metrics. As a benchmark, we use the monthly rebalanced SACEVS Best Value-SACEMS EW Top 2 50%-50% baseline (SACEVS-SACEMS 50-50 Baseline). Using monthly returns for SACEVS Best Value and SACEMS EW Top 2 during July 2006 through January 2025, we find that:

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