Chasing higher monthly returns with leveraged ETFs: full results
I recently expanded my testing to include long-term daily data for leveraged ETFs like TQQQ, SOXL, SPXL, and UPRO.
Maximizing Monthly Returns: Why Volatility Isn’t a Shortcut
I recently expanded my testing to include long-term daily data for leveraged ETFs like TQQQ, SOXL, SPXL, and UPRO. The goal was to see if focusing on high-volatility assets or specific Mean Reversion (MR) strategies could push monthly returns higher. After running these through my standard evaluation pipeline, the results were a clear reality check.
The Volatility Trap
I tested whether targeting stocks with higher volatility or using ATR (Average True Range) to set limit orders would boost performance. My hypothesis was that catching bigger moves would lead to higher returns.
| Strategy | Monthly Return | PF | Max DD |
|---|---|---|---|
| Baseline (thr10, f20, max 5) | +1.14% | 1.56 | -26.1% |
| High Volatility Priority (f25, x4) | +1.04% | - | - |
| High Volatility Tier (f33, x3) | +0.88% | - | - |
| ATR-linked Limit Orders | +1.00% | - | - |
| While the profit per trade did increase as volatility grew (from +42.5bp in low-volatility assets to +88.0bp in high-volatility ones), the risk measured by ATR increased proportionally. The edge-to-noise ratio remained stuck at approximately 0.2. In other words, chasing larger price swings doesn’t increase your edge; it just increases the noise you are trying to filter. None of these variations managed to outperform my baseline strategy. |
Mean Reversion in Leveraged ETFs
I also tested an MR strategy on these ETFs (buying at -2% when RSI2 < 10, exiting at SMA5). The profit per trade was impressive, averaging +110 to +135bp over the full period and peaking at +330 to +400bp between 2023 and 2026. However, the signals were extremely rare. With only four tickers, the capital utilization rate hovered between 5% and 11%. Even with a high win rate (86 to 89%) and a strong PF (3.5 to 7.1), the monthly return only reached +0.33% to +0.76%. For context, simply holding TQQQ during this period would have yielded +2.99% monthly, though it would have come with a punishing -81.8% drawdown.
The Reality of “Easy” Daily Gains
There is a common belief that because markets move several percent a day, capturing a 0.5% daily gain should be easy. My data suggests otherwise:
- Noise vs. Edge: While daily ranges fluctuate between 2% and 4.5%, the unconditional intraday drift is only +1.1bp per day. Over 99.9% of daily price movement is essentially unpredictable noise.
- The Math of 0.5%: A 0.5% daily return compounds to roughly 11% monthly or 3.5x annually. To achieve this consistently, you would need a daily win rate of about 62%. My OOS (out-of-sample) testing shows a maximum win rate of 52%, which drops to coin-flip levels once trading costs are factored in.
- Liquidity Provision: True edge only appears when you provide liquidity during panic-induced dips. The market pays you for being there when things crash, not for clocking in every single day.
Verdict
Statistical evidence does not support the idea of achieving 5 to 8% monthly returns using spot stocks and technical indicators. Even holding the highest-performing assets of this era (like NVDA or TQQQ) results in returns of ~2.7 to 2.9% but forces you to endure drawdowns of 80% or more. If you seek higher returns, the paths are limited and come with significant trade-offs: applying leverage to proven edges (which often conflicts with the desire for low-drawdown, unleveraged trading), using high-k (kurtosis) models in FX, or expanding the universe to hundreds of small, volatile stocks. Even then, reaching a 5 to 8% monthly return remains unlikely.
How this connects
This verification builds on earlier ones (what failed before and what I tried this time, comparisons between approaches).