The quest for the holy grail of trading strategies is real—especially in the volatile world of cryptocurrency markets. When you see eye-catching backtest results like “83% win rate” and “935% returns,” it’s natural to feel both excitement and skepticism. Are these numbers too good to be true? Can a simple combination of technical indicators really deliver consistent profits?
In this deep dive, we’ll analyze a much-discussed ADX-based trading strategy featured in a popular YouTube video titled “83% Win Rate, 935% Return: Revealing the King of Indicators – ADX’s Ultimate Strategy.” We’ll break down its components, test its performance across different market conditions, and assess whether it holds up under real-world scrutiny.
Using data from Bitcoin (BTC) and Ethereum (ETH) on the 1-hour timeframe, we'll explore how this strategy performs during bull and bear markets—and whether retail traders can realistically replicate the results without coding skills or expensive tools.
Understanding the ADX Trading Strategy
This strategy combines four well-known technical indicators:
- Stochastic RSI
- EMA 200 (Exponential Moving Average)
- ADX (Average Directional Index)
- ATR (Average True Range)
Indicator Settings
- Stochastic RSI: Default settings
- EMA: 200-period
- ADX: Only the main ADX line used, threshold at 50
- ATR: Period 8, multiplier 1.5 (used for stop-loss)
Entry Rules
Long Entry Conditions:
- Price must be above the EMA 200
- Stochastic RSI must be below 20 (oversold) and show a bullish crossover (golden cross)
- ADX must be above 50, indicating strong trend strength
Short Entry Conditions:
- Price must be below the EMA 200
- Stochastic RSI must be above 80 (overbought) and show a bearish crossover (death cross)
- ADX must exceed 50
The original backtest covered BTC/USDT from January 8, 2020, to July 1, 2022—905 days with 100 trades. The claimed results? A staggering 83% win rate and 935.12% total return, using a 1:1 risk-reward ratio.
But how reliable are these numbers? Let’s put them to the test.
Real-World Backtesting: Does It Hold Up?
Due to platform limitations, our analysis focuses on two key periods: 2021 (bull market) and 2022 through August 9 (bear market). We evaluate both BTC and ETH on the 1-hour chart with a fixed 1:1 risk-reward setup.
Bitcoin (BTC) Performance
Bear Market (Jan 1 – Aug 9, 2022)
- Total signals: 28
- Win rate: 64%
- Long trades: 41.67% success
- Short trades: 81.25% success
- Profit per $500 trade: $73.68
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With a starting capital of $500 and 10x leverage ($50 per trade), net profit reaches approximately 14.7%—not bad, but far from the viral claims.
Bull Market (Full Year 2021)
- Win rate: 56.25%
- Long vs. short performance nearly balanced (58.33% vs. 55%)
- Overall profitable, but momentum favored longs slightly
Combining both years:
- Total trades: 60
- Winning trades: 36
- Aggregate win rate: 60%
While still solid, this falls short of the original claim of 83%. Trend-following systems often shine in strong directional markets—but struggle when volatility shifts.
Ethereum (ETH): A Better Fit?
Interestingly, ETH showed stronger results under the same rules.
Bear Market (Jan 1 – Aug 9, 2022)
- Total signals: 32
- Win rate: 78%
- Long win rate: 88.89%
- Short win rate: 73.91%
- Profit per $500 trade: $247.41
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Net return jumps to ~49.5% with leveraged trading—significantly outperforming BTC during the same period.
Bull Market (2021)
- Win rate: 56.25%
- Longs performed better (65%) than shorts (47.83%)
Combined performance (Jan 2021 – Aug 2022):
- Total trades: 75
- Winners: 49
- Overall win rate: 65.33%
This suggests that ETH may be more responsive to this ADX-driven system, possibly due to higher volatility and stronger trending behavior compared to BTC.
Timeframe Sensitivity & Optimization
One critical insight: timeframe matters.
On BTC’s 4-hour chart, performance improves significantly:
- Win rate increases to 71.47%
- Fewer trades (lower frequency), but captures larger moves
However, reduced trade count means fewer opportunities—ideal for patient traders who prefer quality over quantity.
We also tested an optimized version by adjusting the ATR multiplier from 1.5 to 2.0, effectively widening stop-loss levels.
Results were striking:
- BTC bear market win rate → 73.08%
- ETH bear market win rate → 84.38%
Wider stops allowed trades more room to breathe, reducing premature exits during pullbacks—a common pitfall in choppy markets.
Key Takeaways & Practical Insights
While no strategy guarantees perpetual profits, this ADX-based approach demonstrates several strengths:
✅ Works best in strong trending environments
✅ Excels in bear markets, particularly for short entries
✅ Performs better on altcoins like ETH than on BTC
✅ Benefits from optimization (e.g., ATR adjustments)
✅ Offers clear, rule-based entries—ideal for automation
But beware of overfitting. High win rates in backtests don’t always translate to live trading success due to slippage, execution delays, and emotional decision-making.
Frequently Asked Questions (FAQ)
Q: Is an 83% win rate realistic in crypto trading?
A: While possible in specific backtests, such high win rates are rare in live trading. Market conditions change rapidly, and past performance doesn’t guarantee future results.
Q: Why does this strategy work better on Ethereum than Bitcoin?
A: ETH tends to exhibit stronger momentum swings and higher volatility, making it more responsive to trend-following signals like ADX crossovers.
Q: Can I automate this strategy without coding?
A: Yes—platforms like TradingView allow basic automation via alerts. For full bot integration, consider connecting to supported exchanges through APIs.
Q: What’s the biggest risk with this ADX strategy?
A: False signals during sideways or consolidating markets. Since ADX > 50 indicates strong trends, it may fail when markets lack direction.
Q: How important is position sizing?
A: Crucial. Even with a 65% win rate, poor money management can turn a winning system into a losing one. Always use consistent risk-per-trade (e.g., 1–2%).
Q: Should I rely solely on this strategy?
A: No single strategy works forever. Combine this with price action analysis, volume confirmation, and macro trend awareness for better outcomes.
Final Thoughts
The so-called “holy grail” of trading rarely exists—but what we’ve seen here is a robust, rules-based framework that delivers consistent results under certain conditions.
It’s not magic—it’s methodology.
Whether you're building a quant model or refining your manual trading plan, this ADX-centered strategy offers valuable lessons in signal filtering, trend confirmation, and risk control.
👉 Start testing your own strategies with powerful trading tools today
Remember: sustainable success comes not from chasing viral wins, but from disciplined execution, continuous testing, and adaptive learning.
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