All Weather Portfolio vs Classic 60/40 Portfolio

A head-to-head comparison analyzing Gary Antonacci's dynamic tactical dual-momentum approach against the passive buy-and-hold benchmark that has defined balanced portfolio construction for decades.

Performance & Risk Metrics (2016-2026)

Metric All Weather Portfolio Classic 60/40 Portfolio
CAGR (10-Year Annualized Return) 7.2% 8.2%
Max Drawdown -11.9% -20.5%
Sharpe Ratio (Risk-Adjusted Return) 0.60 0.48
Volatility (Annualized StdDev) 7.8% 9.8%
Best Calendar Year +16.8% +22.4%
Worst Calendar Year -6.2% -18.0%
Strategy Type Passive Portfolio (Strategic Buy & Hold) Passive Portfolio (Strategic Buy & Hold)
Rebalancing Frequency Annually (fixed target weights) Annually (fixed target weights)

All Weather Philosophy

Designed by Ray Dalio, the All Weather portfolio uses risk parity to balance the four economic seasons: rising/falling growth, and rising/falling inflation. It heavily weights bonds to match the volatility of stocks.

Classic 60/40 Philosophy

The classic 60/40 portfolio is based on Modern Portfolio Theory, allocating a fixed 60% to stocks for growth and 40% to bonds for stability, assuming they are uncorrelated.

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Which Strategy is Right For You?

Choose GEM if: You are comfortable with monthly monitoring, invest via tax-advantaged accounts (like IRAs or 401ks in the US, or tax-wrapped accounts in Europe), and want to maximize long-term growth while protecting capital from major multi-year bear markets.

Choose 60/40 if: You prefer a hands-off, "set and forget" approach, have a taxable investment account where frequent turnover triggers capital gains tax, and can emotionally tolerate drawdowns of 20-30% without panic-selling.

Analyze GEM Strategy Analyze 60/40 Portfolio

Deep Dive

Want to master stable portfolio construction? Read our definitive Risk Parity & All Weather Guide to understand the core rules, historical performance, and exact ETF implementations.

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.