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While the Growth-Value Style Selection strategy achieved an impressive 33.9% annual return that outpaced the S&P 500, it subjected investors to a severe -34.0% peak-to-trough drawdown. This high-octane performance relies on rotating between triple-leveraged equity instruments, placing the strategy squarely in the Aggressive risk tier. Evaluating this trade-off requires weighing the substantial upside against the practical difficulty of enduring crushing losses during sharp market reversals.
📈 Yearly return (CAGR): 33.9%
📉 Worst drop (max drawdown): -34.0%
⚡ Sharpe Ratio: 1.07
💰 Total Return: 1727.8%
🆚 S&P 500 (SPY) over the same period: 324.5% — this strategy outperformed by 1403.3 points
🎯 Universe: TQQQ, UPRO, SPXL, TLT, GLD, SHY
- This strategy passed every calculation-integrity check (data, costs, look-ahead, leverage accounting), but these robustness checks did not pass and are disclosed instead: out-of-sample period; deflated Sharpe ratio (luck across many tested candidates).
- Deflated Sharpe ratio: 0.61 (confidence level 0.95). This strategy was selected from many backtested candidates. Its deflated Sharpe ratio is below the 0.95 confidence level, so the backtest result may be luck and cannot be ruled out as such.
- Out-of-sample period 2022-12-30 to 2026-10-05: 29.7% a year with a -28.2% worst drop (return/drawdown 1.053) vs S&P 500 (SPY) 22.2% / -18.8% (1.181) — it lagged the benchmark on a risk-adjusted basis.
- Bear-market losses: 2018Q4 -21.6% (S&P 500 (SPY) -19.2%); 2020 Feb-Mar -19.8% (S&P 500 (SPY) -33.7%); 2022 -22.5% (S&P 500 (SPY) -24.5%).
- Leverage: holds leveraged ETFs (SPXL 3x, TQQQ 3x, UPRO 3x).
- Maximum drawdown in the full backtest: -34.0%.
- Not forward-verified: this is a historical backtest, and the strategy's paper-trading record is still in progress.
| Metric | Growth-Value Style Selection | S&P 500 (SPY) |
|---|---|---|
| Total return | 1727.8% | 324.5% |
| Worst drop (max drawdown) | -34.0% | -33.7% |
| Period measured | 2016-10-24 – 2026-10-06 | |
Both columns come from the same backtest run over the identical period. A higher return with a deeper drawdown is not automatically better.
| 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | 2026 |
|---|---|---|---|---|---|---|---|---|---|---|
| +13.3% | +64.8% | -7.5% | +36.1% | +109.5% | +74.2% | -21.4% | +53.1% | +22.8% | +42.9% | +0.8% |
How the Core Rotation Rule Works
Building on style investing research by Nicholas Barberis and Andrei Shleifer (2003), this systematic model rebalances monthly across growth and value styles using triple-leveraged equities including TQQQ, UPRO, and SPXL. At the final trading session of each month, the strategy evaluates trailing momentum and allocates entirely to the leading style, provided the performance gap clears a strict dominance threshold to prevent whipsaws. If the S&P 500 benchmark drops below its 200-day simple moving average, the system triggers an emergency exit, rotating capital out of equities and into defensive safe havens such as long-term Treasuries (TLT) and gold (GLD). This dual-layer structure automates trend following while enforcing a systematic broad-market circuit breaker that eliminates emotional decision-making.
Why It Can Beat or Lose to the Benchmark
Over the full backtest period, the strategy beat the S&P 500 benchmark by 1,403.3 percentage points, generating a 1,727.8% total return compared to 324.5% for SPY. However, higher total returns coupled with a deeper drawdown (-34.0% versus -33.7%) do not automatically make this strategy superior, as amplified leverage creates severe structural vulnerabilities. While the rule captures massive upside during persistent style trends, it suffers heavy decay and lags during choppy sideways markets where frequent switching erodes capital. This weakness was evident during the 2022 to 2026 out-of-sample period, where its return-to-drawdown ratio of 1.053 trailed the benchmark’s 1.181, confirming that it lagged the broader market on a risk-adjusted basis.
Where It Hurts: Drawdowns and Robustness Failures
Assigned to the Aggressive tier, this strategy inflicts severe losses during rapid market turns before the monthly rebalance or 200-day trend filter can shift to safety. The portfolio endured sharp bear-market hits, losing -21.6% in the fourth quarter of 2018 and -22.5% during 2022, even though its trend filter mitigated the initial February–March 2020 crash to -19.8% against the index’s -33.7% plunge. Crucially, the strategy failed vital robustness checks, recording a deflated Sharpe ratio of 0.61 against a 0.95 confidence threshold, meaning its stellar backtest cannot be ruled out as sheer selection luck across multiple candidate tests. Combined with its out-of-sample risk-adjusted underperformance, these statistical red flags highlight that historical paper gains may not translate into resilient future execution.
Who This Strategy Fits
This approach fits only disciplined, high-risk tolerance investors who operate within an Aggressive tier mandate and can endure drawdowns exceeding 30% without abandoning their rules. Because holding 3x leveraged instruments introduces compounding drag and extreme volatility, this strategy should only be deployed as a speculative satellite allocation rather than a foundational portfolio core. Investors must size positions with extreme caution and treat the results purely as historical simulation research, especially since live forward-verification is still pending. Those seeking steady capital preservation, low volatility, or reliable liquidity should avoid this high-variance rotation model altogether.
Frequently Asked Questions
How risky is the Growth-Value Style Selection strategy?
It belongs to the Aggressive tier due to its -34.0% maximum drawdown and heavy reliance on 3x leveraged ETFs like TQQQ and UPRO. Furthermore, a deflated Sharpe ratio of 0.61 means the strategy’s backtest results may reflect selection luck rather than genuine structural alpha.
Can this strategy be traded live today?
While its constituent ETFs trade actively on public exchanges, this model should not be deployed as a verified live system because its paper-trading record is still in progress. Investors must treat it as experimental research rather than a forward-tested commercial strategy.
What key assumptions does the backtest rely on?
The simulation assumes disciplined monthly rebalancing, seamless rotation into TLT and GLD when SPY breaches its 200-day moving average, and verified calculation integrity across data, costs, and leverage accounting. However, it assumes that historical style momentum patterns will persist despite failing critical out-of-sample and data-mining robustness checks.
| Period | 2016-10-24 – 2026-10-06 |
| Universe | TQQQ, UPRO, SPXL, TLT, GLD, SHY |
| Years with a gain | 9 of 11 |
| Price data | FinanceDataReader daily bars |
What this does not prove. Signals are computed only from bars that closed before the session they trade. Full assumptions, including which integrity checks are unverified: avalonquant.com/methodology.
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📊 Live strategy performance and daily quant briefings: avalonquant.com
📄 Original paper: Style Investing (Journal of Financial Economics, 2003)
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