Auto-generated · Last updated May 02, 2026 19:01 UTC
How This Works
No jargon. No black boxes. Here's exactly what we do, where our data comes from, and every strategy we've tested — including the ones that failed.
The Big Idea
Most people trade based on gut feeling or tips. Most of them lose money.
We take a different approach: let the computer try hundreds of strategies on real historical data and keep only the ones that actually would have made money. Not in theory — on real prices going back two years.
Think of it like this: instead of guessing which recipe makes the best cookie, you bake 1,000 batches and see which ones people actually eat.
The 3-Step Process
Step 1 — Scout
Find strategies real traders use. We've collected 429 strategies from TradingView's community — strategies that thousands of real people tested and voted on. We don't make stuff up in a vacuum.
Step 2 — Test
Test each strategy on each asset separately. We run every strategy against 2 years of actual market data for each of our 9 assets independently. The key: we split the data 70/30. The strategy only "sees" the first 70%. Then we test on the remaining 30% it has never seen. This prevents the strategy from just memorizing the past.
Step 3 — Score per asset
Find what works where. A strategy that's great for Bitcoin might be terrible for Apple. Instead of averaging everything together, we score each strategy on each asset individually. That means we can recommend the right strategy for the right market. We've tested 537 strategies so far — 164 are profitable on average, but many more win on specific assets.
What We Track (9 Assets)
We test across different markets to make sure strategies work broadly, not just on one lucky pick:
₿ Bitcoin (BTC-USD)
The biggest cryptocurrency. Trades 24/7, highly volatile.
148 profitable strategies found
Ξ Ethereum (ETH-USD)
Second biggest crypto. Bigger swings than Bitcoin.
147 profitable strategies found
◎ Solana (SOL-USD)
Fast-growing L1 crypto. High volatility, 24/7 trading.
151 profitable strategies found
◆ S&P 500 ETF (SPY)
Tracks the 500 biggest US companies. The benchmark.
168 profitable strategies found
◆ Nasdaq 100 ETF (QQQ)
Heavy on tech — Apple, Microsoft, Nvidia, Meta.
163 profitable strategies found
🥇 Gold Futures (GC=F)
The classic safe haven. Inversely correlated with risk assets.
199 profitable strategies found
🥈 Silver Futures (SI=F)
Industrial metal meets precious metal. More volatile than gold.
385 profitable strategies found
🍎 Apple (AAPL)
World's most valuable company. Relatively stable.
273 profitable strategies found
⚡ Tesla (TSLA)
Famously volatile. Good stress test for strategies.
190 profitable strategies found
We're adding more over time — gold, oil, sector ETFs, more individual stocks. We want to prove the system works on these first.
Best Strategy Per Asset
Different markets need different strategies. Here's the current top performer for each asset, scored on the 30% of data it never saw during training:
₿ Bitcoin
+1.871 Sharpe 🟢
Chaos Volatility Breakout (ATR + Breakout)-VM
Return: +38.8% · Max drawdown: 15% · 1 trades · 100% win rate
Ξ Ethereum
+2.350 Sharpe 🟢
RSI Divergence Strategy with SL/TP
Return: +16.8% · Max drawdown: 4% · 5 trades · 80% win rate
◎ Solana
+2.525 Sharpe 🟢
EVO_1144_c4cbc12d
Return: +78.9% · Max drawdown: 20% · 3 trades · 1% win rate
◆ S&P 500 ETF
+1.586 Sharpe 🟢
EVO_0010_0c1eece0
Return: +17.9% · Max drawdown: 5% · 7 trades · 71% win rate
◆ Nasdaq 100 ETF
+2.223 Sharpe 🟢
RSI Divergence Strategy with SL/TP
Return: +8.9% · Max drawdown: 1% · 2 trades · 100% win rate
🥇 Gold Futures
+3.045 Sharpe 🟢
Ichimoku Strategy CDI
Return: +42.5% · Max drawdown: 9% · 10 trades · 70% win rate
🥈 Silver Futures
+3.852 Sharpe 🟢
EVO_1133_0ae6f856
Return: +99.5% · Max drawdown: 11% · 24 trades · 71% win rate
🍎 Apple
+1.752 Sharpe 🟢
MACD Strategy
Return: +20.8% · Max drawdown: 8% · 10 trades · 60% win rate
⚡ Tesla
+1.802 Sharpe 🟢
Futures Calendar Spread Mean Reversion Strategy
Return: +25.6% · Max drawdown: 12% · 15 trades · 80% win rate
Where We Get Our Data (59 Signals)
We pull from 7 different sources, all free and publicly available:
📈 Yahoo Finance
Prices for all stocks, ETFs, and crypto. Plus macro indicators like the VIX, Treasury yields, gold, oil, and the US dollar index.
Free, no account needed
😱 alternative.me
The Crypto Fear & Greed Index — a daily 0-100 score of crypto investor sentiment. 8 years of history.
Free, no account needed
⛓️ Blockchain.info
Bitcoin on-chain data: active addresses, hash rate, mempool, miner revenue, transaction volume.
Free, no account needed
🦎 CoinGecko
Crypto market structure: market caps, Bitcoin dominance, and exchange volume.
Free, no account needed
🏛️ FRED (Federal Reserve)
Official US economic data: inflation (CPI), unemployment, Fed funds rate, money supply, GDP, and yield curve data.
Free with key
📊 TradingView
Community-shared trading strategies. 429 strategies collected from their public library.
Free, public API
🔮 Hyperliquid
Perpetual futures data: funding rates, open interest, futures-vs-spot premium, and derivatives volume for BTC and ETH. Institutional-grade sentiment signals.
Free, no auth needed
That gives us 59 data signals — not just price, but fear levels, inflation, Federal Reserve actions, Bitcoin miner behavior, derivatives sentiment, money flows between sectors, and more.
Key Terms (Plain English)
Sharpe Ratio"Did you make money without scary drops?" Above 0 = profitable. Above 1.0 = good. Below 0 = lost money. Our primary scorecard.
Max DrawdownThe worst peak-to-valley drop. If $10K became $6K before recovering, that's 40% drawdown. Lower is better.
Walk-Forward TestOur anti-cheating method. Train on old data, test on newer data it's never seen. Like studying chapters 1-7 and being tested on 8-10.
Per-Asset ScoringWe test every strategy on every asset separately. A strategy might be amazing for QQQ (+2.2 Sharpe) but terrible for BTC (-1.5). Per-asset scoring catches that instead of averaging it away.
Funding RateWhat leveraged traders pay each hour on perpetual futures. Extreme funding = crowded trade = potential reversal signal.
EMA / SMAMoving averages that smooth price to show the trend. When a short-term average crosses above a long-term one, that's often a buy signal.
MACDMomentum indicator. When the MACD line crosses above its signal line = bullish momentum. Below = bearish.
VIXWall Street's fear gauge. Below 15 = calm. 15-25 = normal. Above 25 = nervous. Above 35 = panic.
Fear & GreedCrypto sentiment score (0-100). Below 25 = Extreme Fear (historically good to buy). Above 75 = Extreme Greed (historically good to sell).
Yield CurveDifference between long and short-term bond rates. When it inverts (goes negative), it has preceded every US recession in 50 years.
All Tested Strategies (537 total)
Full transparency. Here are the top 164 strategies that are profitable on average across all 9 assets, followed by a summary of the rest. We show our losses too — that's how you know the wins are real.
EVO_1371_1251fc96
BTC: +1.80 · ETH: +1.07 · SOL: +2.14 · SPY: +0.34 · QQQ: +1.05 · GC=F: +1.18 · SI=F: +2.47 · AAPL: +1.38 · TSLA: +0.87
EVO_1394_6730cca1
BTC: +1.80 · ETH: +1.07 · SOL: +2.14 · SPY: +0.34 · QQQ: +1.05 · GC=F: +1.18 · SI=F: +2.47 · AAPL: +1.38 · TSLA: +0.87
EVO_1450_0fc36cb7
BTC: +1.80 · ETH: +1.07 · SOL: +2.14 · SPY: +0.34 · QQQ: +1.05 · GC=F: +1.18 · SI=F: +2.47 · AAPL: +1.38 · TSLA: +0.87
EVO_1535_e8ac2066
BTC: +1.80 · ETH: +1.07 · SOL: +2.14 · SPY: +0.34 · QQQ: +1.05 · GC=F: +1.18 · SI=F: +2.47 · AAPL: +1.38 · TSLA: +0.87
EVO_1574_5c81d4c7
BTC: +1.80 · ETH: +1.07 · SOL: +2.14 · SPY: +0.34 · QQQ: +1.05 · GC=F: +1.18 · SI=F: +2.47 · AAPL: +1.38 · TSLA: +0.87
EVO_1614_f39f0d01
BTC: +1.80 · ETH: +1.07 · SOL: +2.14 · SPY: +0.34 · QQQ: +1.05 · GC=F: +1.18 · SI=F: +2.47 · AAPL: +1.38 · TSLA: +0.87
EVO_1718_c3a14467
BTC: +1.80 · ETH: +1.07 · SOL: +2.14 · SPY: +0.34 · QQQ: +1.05 · GC=F: +1.18 · SI=F: +2.47 · AAPL: +1.38 · TSLA: +0.87
EVO_1887_a79498fd
BTC: +1.80 · ETH: +1.07 · SOL: +2.14 · SPY: +0.34 · QQQ: +1.05 · GC=F: +1.18 · SI=F: +2.47 · AAPL: +1.38 · TSLA: +0.87
EVO_1922_f734d715
BTC: +1.80 · ETH: +1.07 · SOL: +2.14 · SPY: +0.34 · QQQ: +1.05 · GC=F: +1.18 · SI=F: +2.47 · AAPL: +1.38 · TSLA: +0.87
EVO_1985_40e089b5
BTC: +1.80 · ETH: +1.07 · SOL: +2.14 · SPY: +0.34 · QQQ: +1.05 · GC=F: +1.18 · SI=F: +2.47 · AAPL: +1.38 · TSLA: +0.87
+ 373 more
Negative average Sharpe
These strategies lost money on average across all 9 assets. Some may still be profitable on individual assets — check the per-asset leaderboard.
0 ran successfully · 0 crashed during translation · 537 total tested
What We've Learned
Per-asset scoring is essential
A strategy averaging +0.3 across 9 assets might be hiding a +2.2 on QQQ and a -1.5 on BTC. Per-asset scoring finds winners that averaging would bury.
Translation quality matters more than quantity
We hand-translate every strategy from TradingView's Pine Script to Python. Automated translations inflated 81% of scores. Manual verification caught it — every number on this page has been verified.
Most strategies fail
Only 164 out of 537 strategies are profitable on average. That's a 30% hit rate. The value isn't finding strategies that work — it's eliminating the hundreds that don't.
Derivatives data adds signal
Funding rates, open interest, and futures premium from Hyperliquid tell us what leveraged traders are doing. When funding goes extreme, reversals follow. Most retail tools don't track this.
Different markets, different strategies
No single strategy wins everywhere. AAPL has 273 profitable strategies while BTC only has 148. The system's strength is matching the right strategy to the right market.
🧬 Evolution Engine
Beyond testing existing strategies, we now evolve new ones using genetic algorithms. The system takes the best-performing strategies, mutates their parameters, breeds traits between different strategies, and keeps only the offspring that beat their parents.
How Evolution Works
1. Select: Pick top performers as parents.
2. Mutate: Tweak parameters (lookback periods, thresholds, multipliers) by ±30%.
3. Breed: Combine parameters from two different winning strategies.
4. Test: Backtest the offspring on all 9 assets using walk-forward validation.
5. Keep or Kill: Only offspring that beat their parent's average Sharpe ratio survive. Everything else gets discarded.
Why It Works
Most strategies use the same handful of indicators (MACD, RSI, Bollinger Bands) but with different parameter values. The "right" values depend on the market's rhythm, which changes over time. Evolution finds better parameter combinations by trying thousands of variations and keeping winners — like natural selection for trading logic.
Built-In Safeguards
We use the same walk-forward validation for evolved strategies as original ones — train on 70%, test on 30% the strategy has never seen. Evolved strategies must beat their parent by at least 0.01 Sharpe to survive, preventing noise from sneaking through. Every evolved strategy includes a full lineage record (parents, generation, mutation type).
What's Honest
⚠️ Limitations we want you to know:
• Backtesting isn't a crystal ball. Past performance ≠ future results.
• 537 strategies tested so far. We're adding more continuously.
• Crypto is harder than equities — fewer strategies survive, especially in bear markets.
• 9 assets is a small universe. Growing it is on the roadmap.
• Pine Script translation can introduce subtle bugs. We hand-verify, but edge cases exist.
• This is not financial advice. We share research openly, but your money is your responsibility.
See the Live Signals →