Global Equity Momentum (GEM)

Tactical Asset Allocation Medium

About Strategy

Gary Antonacci's classic dual momentum strategy. Combines relative momentum (switching between US and international equities) and absolute momentum as a safety filter to switch to bonds during bear markets.

Performance Metrics (2016�2026)

CAGR (10-Year)12.3%
Max Drawdown-17.8%
Sharpe Ratio0.72
Volatility (StdDev)12.5%
Best Year+31.2%
Worst Year-11.2%
Strategy TypeTactical Asset Allocation
Risk ProfileMedium

Asset Allocation

GEM rotates 100% of the portfolio into one of three assets based on momentum signals: US Equities (tracked via SPY or VOO), International Equities (tracked via VXUS), or Aggregate Bonds (tracked via BND). Only one asset is held at any given time � this is a binary, all-or-nothing allocation model.

Execution Rules

  1. At the end of each month, evaluate the trailing 12-month return of S&P 500 (US) and MSCI ACWI ex-US (International).
  2. Select the index with the higher 12-month return (relative momentum).
  3. Compare the leading asset's performance against the risk-free rate (absolute momentum).
  4. If the return is greater than cash, invest 100% in the winning equity. Otherwise, allocate 100% to Aggregate Bonds.

ETF Proxies Used in Our Backtest

  • Vanguard S&P 500 ETF (VOO) � for US stock exposure
  • Vanguard Total International Stock ETF (VXUS) � for global ex-US equities
  • Vanguard Total Bond Market ETF (BND) � for aggregate bond allocation
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GEM Allocation Calculator


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History & Background of Global Equity Momentum

Global Equity Momentum (GEM) was developed by Gary Antonacci, a financial author and portfolio theorist who published the landmark book "Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk" in 2014. The strategy emerged from decades of academic research into the momentum factor � one of the most well-documented anomalies in financial markets.

The core innovation of GEM lies in combining two distinct types of momentum that had previously been studied in isolation. Relative momentum (also called cross-sectional momentum) compares the performance of different assets against each other to select the winner. Absolute momentum (also called time-series momentum) compares an asset's performance against a risk-free benchmark to determine whether the trend is positive or negative. By fusing both signals, GEM attempts to capture equity upside during bull markets while avoiding the worst drawdowns during bear markets.

Since its publication, GEM has become one of the most widely followed tactical asset allocation strategies among self-directed investors. Its simplicity � requiring only one monthly check and a single trade � makes it accessible to anyone with a brokerage account that offers commission-free ETF trading.

How GEM Works: Step-by-Step Decision Process

Every month, GEM runs a simple two-step decision tree:

Step 1 � Relative Momentum Check: Compare the trailing 12-month total return of US equities (S&P 500) versus international equities (MSCI ACWI ex-US). The asset with the higher return is the "momentum winner." This step determines which equity market to invest in.

Step 2 � Absolute Momentum Filter: Take the momentum winner from Step 1 and compare its 12-month return against the risk-free rate (typically US Treasury Bills). If the winner's return exceeds the risk-free rate, invest 100% in that equity. If not, it signals a potential bear market � move the entire portfolio into aggregate bonds (BND/AGG) as a defensive position.

This dual-filter approach is what gives GEM its edge. The relative momentum screen captures the strongest equity trend globally, while the absolute momentum filter acts as a circuit breaker, pulling money out of equities entirely when momentum turns negative. During the 2008 financial crisis, for example, absolute momentum would have triggered a move to bonds well before the worst of the drawdown.

When to Use GEM: Pros & Cons

Strengths

  • Strong risk-adjusted returns (Sharpe 0.72) over the last decade
  • Built-in bear market protection via absolute momentum filter
  • Extremely simple execution � one trade per month maximum
  • Low cost � requires only 3 ETFs (VOO, VXUS, BND)
  • Backed by extensive academic research (Jegadeesh & Titman, 1993)

Limitations

  • Binary allocation (100% in one asset) creates concentration risk
  • Susceptible to whipsaw signals in choppy, sideways markets
  • 12-month lookback period may react slowly to sudden regime changes
  • Tax-inefficient due to frequent switching (better in tax-advantaged accounts)
  • Requires discipline � psychologically hard to sell at momentum shifts

Ideal for: Self-directed investors who want equity-like returns with reduced drawdowns, are comfortable with a tactical approach, and have access to a tax-advantaged account (IRA, 401k). GEM works best as a core portfolio strategy rather than a satellite holding.

Learn More & Guides

Complete Guide to GEM

Learn the execution details, ETF picks, and detailed historical analysis of Gary Antonacci's system.

What is Momentum Investing?

Understand the behavioral psychology and anomalies that explain why momentum is persistent.

Related Strategies

Dual Momentum (DM)

Simplified version of GEM � rotates only between US equities and bonds, removing international stocks. CAGR: 10.9%

Adaptive Asset Allocation

Dynamic 3-asset momentum strategy. Higher risk, higher return potential. CAGR: 11.5%

Ivy Portfolio (Meb Faber)

5-asset tactical model with SMA trend filter. More diversified than GEM. CAGR: 8.8%

MK
Marcin Kowalski Quantitative Researcher

Marcin Kowalski designs and backtests rules-based quantitative strategies. He holds an MS in Quantitative Finance and leads research for systematic asset allocation at StrategyIndex.io.

Backtest Methodology

Backtests are based on historical monthly Total Return data (dividends reinvested) of proxy index ETFs. We assume zero transaction slippage, annual/monthly rebalancing frequency, and no leverage. All calculations are executed systematically without human discretion.

Data Sources & Integrity

Historical figures are sourced from Yahoo Finance API, Tiingo Cloud API, and FRED Federal Reserve Database.

Last Data Update: June 30, 2026
Educational Purpose Only & Disclaimer

All content and calculation tools on StrategyIndex.io are intended solely for educational, research, and informational purposes. They do not constitute financial advice, tax planning, investment recommendations, or legal counsel. Hypothetical backtesting results have inherent limitations and do not represent actual trading. Past performance is never an indicator or guarantee of future returns. Asset allocation models are subject to market volatility, tracking errors, and strategy breakdown. Consult a certified financial planner before making any investment decisions.