CAN MONKEYS BEAT THE MARKET?
Part 1: Establishing a Baseline Against Buy-and-Hold
38,778
BACKTESTS
100
ASSETS
13
YEARS
7
STAT TESTS
Abstract. This is Part 1 of a multi-part research series. A baseline is established by testing 12 absurd trading strategies—coin flips, dice rolls, and NASA-grade planetary gravitational forces—against buy-and-hold (HODL). After 38,778 backtests with rigorous statistical testing, it is found that stupid strategies can beat HODL, but beating HODL is a trivially low bar. Any strategy with an exit mechanism outperforms during crashes. The real question—can monkeys beat actual professional trading strategies?—will be answered in Part 7, where these same stupid strategies are compared against the full Omega System with 171 metrics.
TABLE OF CONTENTS
1. METHODOLOGY
1.1 Data Collection
Historical OHLCV data was collected from Yahoo Finance via the yfinance API for the top 100 cryptocurrencies by market capitalization. Data spans from September 2014 (BTC inception on the exchange) to January 2026.
| Interval | Date Range | Total Rows | Assets |
|---|---|---|---|
| 1 day | 2014-09-17 → 2026-01-22 | 242,290 | 100 |
| 1 hour | 2024-01-23 → 2026-01-22 | 1,530,832 | 89 |
| 30 min | 2025-11-23 → 2026-01-22 | 251,665 | 89 |
| 15 min | 2025-11-23 → 2026-01-22 | 502,775 | 89 |
| 5 min | 2025-11-23 → 2026-01-22 | 1,487,288 | 89 |
| 1 min | 2026-01-14 → 2026-01-22 | 957,235 | 89 |
Total: 4,972,085 price candles across 5 million+ data points.
1.2 Planetary Data (for Horoscope Strategy)
Actual gravitational forces exerted by celestial bodies on a 1.5kg MacBook located in Turkey were computed using NASA JPL ephemeris data (DE421). For each of the 71,016 unique timestamps, the following were calculated:
- Ecliptic longitude and distance for Sun, Moon, Mercury, Venus, Mars, Jupiter, Saturn
- Gravitational force: F = G × m₁ × m₂ / r² (Newton's Law)
- Net force vector (Fx, Fy) and direction using trigonometric decomposition
1.3 Trading Rules
- Starting capital: $10,000 USD
- Position sizing: 100% (all-in on each trade)
- Trading fee: 0.1% per transaction (Binance spot rate)
- Execution price: Candle close
- Backtests split by calendar year to prevent survivorship bias
- Both NORMAL and REVERSED logic tested for each strategy
1.4 Statistical Rigor
To ensure findings are not statistical flukes, 7 rigorous tests were applied:
- Bonferroni Correction: Adjusts p-value threshold for multiple testing (α/m = 0.05/23)
- Benjamini-Hochberg FDR: Controls false discovery rate
- Cohen's h Effect Size: Measures practical (not just statistical) significance
- Wilson Confidence Intervals: 95% CI for beat rates
- Out-of-Sample Testing: Train (2014-2021) vs Test (2022-2024) split
- Sharpe Ratio Significance: Risk-adjusted return testing
- 5-Fold Cross-Validation: Stability across data slices
2. STRATEGIES
| Strategy | Logic | Avg Trades/Year |
|---|---|---|
| HODL | Buy at start, sell at end | 2 |
| Coin Flip | 50% buy, 50% sell each candle | 151 |
| Dice Roll | 1-2: buy, 3-4: hold, 5-6: sell | 101 |
| Magic 8-Ball | 20 classic responses → buy/hold/sell | 83 |
| Drunk Sailor | Random walk with drifting bias | 117 |
| Fibonacci Fool | Trade only at candle #1,2,3,5,8,13,21... | 11 |
| Lucky 7 | Buy if price ends in 7, sell if ends in 3 | 18 |
| Pi Trader | Use digits of π: 0-3=buy, 4-6=hold, 7-9=sell | 122 |
| Three Red | Buy after 3 red candles, sell after 3 green | 20 |
| FOMO Monkey | Buy on volume spike, panic sell on -2% drop | 32 |
| Horoscope Sun | Buy if net planetary force direction > 0° | 2.5 |
| Horoscope NoSun | Same but excluding Sun's force | 22 |
3. RESULTS
3.1 Statistical Significance (Z-Test)
Each strategy's "beat HODL" rate was tested for significant difference from 50% (random chance):
| Strategy | Beat HODL | N | Z-Score | Result |
|---|---|---|---|---|
| horoscope_sun reversed | 56.4% | 729 | +3.44 | ✓ SIGNIFICANT (p<0.001) |
| fibonacci_fool normal | 53.8% | 730 | +2.07 | ✓ SIGNIFICANT (p<0.05) |
| horoscope_nosun reversed | 53.5% | 723 | +1.90 | Not significant |
| lucky_7 normal | 53.3% | 737 | +1.80 | Not significant |
| coin_flip normal | 45.2% | 732 | -2.59 | ✓ WORSE (p<0.05) |
| coin_flip reversed | 43.2% | 732 | -3.70 | ✓ WORSE (p<0.001) |
| horoscope_nosun normal | 41.8% | 737 | -4.46 | ✓ WORSE (p<0.001) |
🎯 Key Discovery: Horoscope Sun Reversed beats HODL 56.4% of the time (p<0.001, survives Bonferroni). However, see Section 7 for why this doesn't mean what you think it means.
3.2 Performance by Interval
| Interval | Avg Return | Beat HODL | Avg Trades | Verdict |
|---|---|---|---|---|
| 1 day | +2.3% | 48.3% | 62 | ✓ ONLY PROFITABLE |
| 30 min | -21.0% | 25.4% | 258 | ✗ Loss |
| 15 min | -32.3% | 23.2% | 513 | ✗ Loss |
| 1 hour | -35.0% | 23.8% | 1,056 | ✗ Loss |
| 1 min | -47.9% | 31.1% | 1,863 | ✗ Loss |
| 5 min | -48.5% | 21.4% | 1,509 | ✗ Loss |
Conclusion: Only daily-interval trading is profitable. Higher frequencies are destroyed by fees.
3.3 Fee Impact Analysis
The 0.1% trading fee compounds devastatingly:
| Strategy | Trades | Fee Paid | Actual Return | If No Fee |
|---|---|---|---|---|
| coin_flip | 151 | -15.1% | -5.7% | +9.5% |
| pi_trader | 122 | -12.2% | -1.5% | +10.7% |
| horoscope_sun reversed | 3 | -0.3% | +32.9% | +33.1% |
| fibonacci_fool | 11 | -1.1% | +5.7% | +6.8% |
Finding: Coin flip would be +9.5% profitable without fees. With 0.1% fee × 151 trades = 15.1% lost to fees, turning it into -5.7% loss.
3.4 Trade Frequency Impact
| Trades/Year | Avg Return | Beat HODL | Samples |
|---|---|---|---|
| 0-9 | +6.9% | 48.3% | 3,977 |
| 10-49 | +7.9% | 50.6% | 5,934 |
| 50-99 | -1.1% | 51.6% | 1,148 |
| 100-199 | -6.8% | 45.7% | 4,857 |
| 200+ | -9.5% | 25.9% | 212 |
3.5 Bitcoin 4-Year Cycle
| Cycle Position | Avg HODL Return | Interpretation |
|---|---|---|
| Post-Halving Year | +818.4% | 🚀 Massive gains (2013, 2017, 2021) |
| Mid-Cycle | +389.2% | Still strong |
| Pre-Halving | +366.0% | Accumulation phase |
| Halving Year | +224.0% | Event anticipation |
4. COIN-BASED ANALYSIS
4.1 Top 20 Coins Where Strategies Work Best
| Asset | Beat HODL | Tests | Avg HODL | Best Return | Notes |
|---|---|---|---|---|---|
| APT-USD | 81.1% | 106 | -49.6% | +362.4% | New coin, volatile |
| COMP-USD | 74.2% | 62 | -96.6% | +304.2% | DeFi token |
| CRV-USD | 68.9% | 132 | -33.5% | +274.8% | Curve Finance |
| ZIL-USD | 67.6% | 176 | -37.2% | +285.9% | Zilliqa |
| AUDIO-USD | 65.9% | 132 | -23.7% | +275.4% | Audius |
| BAL-USD | 64.3% | 154 | -28.9% | +264.6% | Balancer |
| GALA-USD | 63.6% | 132 | -16.7% | +483.5% | Gaming |
| 1INCH-USD | 62.9% | 132 | -9.9% | +387.7% | DEX aggregator |
| FLOW-USD | 62.9% | 132 | -26.2% | +460.0% | NFT chain |
| AVAX-USD | 61.1% | 131 | +4.0% | +288.9% | L1 chain |
Pattern: Strategies work best on volatile, declining coins where being OUT of the market is advantageous.
4.2 Bottom 20 Coins Where Strategies Fail
| Asset | Beat HODL | Tests | Avg HODL | Notes |
|---|---|---|---|---|
| USDC-USD | 11.6% | 198 | +0.0% | Stablecoin (fees only) |
| TUSD-USD | 14.6% | 198 | -0.1% | Stablecoin |
| DAI-USD | 15.9% | 176 | +0.0% | Stablecoin |
| USDT-USD | 15.9% | 220 | -0.1% | Stablecoin |
| BNB-USD | 29.8% | 198 | +81.0% | Strong performer |
| ETH-USD | 30.4% | 217 | +91.5% | Strong performer |
| BTC-USD | 30.7% | 264 | +58.2% | Strong performer |
Pattern: Strategies fail on stablecoins (pure fee loss) and strong performers (HODL wins).
4.3 Major Coins - Best Strategy Per Coin
| Coin | Best Strategy | Beat HODL | Avg Return |
|---|---|---|---|
| BTC-USD | horoscope_sun reversed | 58.3% | +40.5% |
| ETH-USD | fibonacci_fool normal | 62.5% | +15.1% |
| BNB-USD | fomo_monkey reversed | 55.6% | +93.7% |
| SOL-USD | coin_flip normal | 60.0% | +42.5% |
| XRP-USD | fibonacci_fool normal | 66.7% | +9.7% |
| ADA-USD | magic_8ball reversed | 75.0% | +31.0% |
| DOGE-USD | magic_8ball normal | 87.5% | +51.1% |
| DOT-USD | horoscope_sun reversed | 71.4% | +73.1% |
| LINK-USD | horoscope_nosun reversed | 55.6% | +91.4% |
| AVAX-USD | dice_roll reversed | 83.3% | -4.2% |
4.4 Portfolio Simulation (2019-2024)
Starting with $10,000, compounding yearly returns:
| Portfolio | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | Final |
|---|---|---|---|---|---|---|---|
| Astro Only | +17.6% | +20.7% | +137.2% | -6.4% | +79.3% | +86.5% | $105,326 |
| Top 2 Only | +2.7% | +26.3% | +109.0% | -17.5% | +74.5% | +36.7% | $53,374 |
| Pure HODL | +8.8% | +110.2% | +125.3% | -72.3% | +73.9% | +11.1% | $27,568 |
| All Stupid | -0.7% | +28.6% | +74.7% | -35.8% | +46.1% | +17.2% | $24,529 |
| Bank Deposit | +2.0% | +0.5% | +0.1% | +1.0% | +4.5% | +5.0% | $11,367 |
| Random Only | -1.8% | +34.4% | +44.8% | -51.2% | +17.1% | -0.7% | $10,828 |
🚀 Shocking Result: "Astro Only" portfolio (horoscope_sun + horoscope_nosun reversed) turned $10,000 into $105,326 over 6 years—nearly 4× better than pure HODL!
5. WHY HOROSCOPE WORKS
The horoscope_sun strategy trades based on the net gravitational force direction from all planets on a MacBook in Turkey. Here's why the REVERSED version works:
- Sun direction > 0 for ~186 days/year (spring/summer)
- Sun direction < 0 for ~179 days/year (fall/winter)
| Logic | Spring/Summer | Fall/Winter | Result |
|---|---|---|---|
| NORMAL | BUY | SELL | 47.3% beat HODL |
| REVERSED | SELL | BUY | 56.4% beat HODL |
Insight: Crypto historically performs better in Q4 (fall/winter). The reversed horoscope accidentally captures this seasonality by being OUT during summer and IN during winter.
6. KEY FINDINGS (Part 1)
| # | Finding | Evidence | Implication |
|---|---|---|---|
| 1 | Stupid strategies beat HODL | 56.4% beat rate (p<0.001) | But HODL is a low bar |
| 2 | ALL strategies excel in BEAR markets only | 81-85% in crashes, 7-41% in bulls | Exit mechanism is the "edge" |
| 3 | Effect size is NEGLIGIBLE | Cohen's h = 0.128 | Practical advantage is tiny |
| 4 | Beating HODL ≠ Beating the market | HODL loses 70% in crashes | Need to test vs real strategies |
| 5 | Fees destroy high-frequency trading | 200+ trades: only 25.9% win | Trading less = winning more |
| 6 | Daily interval is the only profitable one | +2.3% avg vs -48.5% for 5-min | Slower = better |
| 7 | Cross-validation shows HIGH variance | σ = 28.2% across folds | Results are unstable |
| 8 | Random baseline is ~45% (not 50%) | Coin flip: 45.2%, Z=-2.59 | Fees skew baseline down |
Part 1 Limitation: HODL is not a fair benchmark—it's the absence of strategy. To truly test if "monkeys can beat the market," comparison against actual professional trading strategies is required. This comparison will be conducted in Part 7.
7. STATISTICAL RIGOR ANALYSIS
To ensure findings aren't statistical flukes, rigorous hypothesis testing methods used in academic research were applied.
7.1 Multiple Testing Correction
Problem: Testing 23 strategies at α=0.05 means ~1.2 false positives expected by chance alone.
Solution: Apply Bonferroni correction (α/m = 0.05/23 = 0.00217) and FDR (Benjamini-Hochberg).
| Strategy | p-value | Bonferroni | FDR |
|---|---|---|---|
| horoscope_sun reversed | 0.000572 | ✓ SURVIVES | ✓ SURVIVES |
| horoscope_nosun normal | 0.000008 | ✓ SURVIVES | ✓ SURVIVES |
| coin_flip reversed | 0.000219 | ✓ SURVIVES | ✓ SURVIVES |
| pi_trader normal | 0.001180 | ✓ SURVIVES | ✓ SURVIVES |
| coin_flip normal | 0.009674 | ✗ FAILS | ✓ SURVIVES |
| fibonacci_fool normal | 0.038205 | ✗ FAILS | ✗ FAILS |
⚠️ Critical Update: After Bonferroni correction, horoscope_sun reversed remains significant, but fibonacci_fool normal does NOT survive the stricter threshold.
7.2 Effect Size (Cohen's h)
Problem: p-values tell IF an effect exists, not HOW BIG it is. Large samples can make tiny effects "significant."
Interpretation: |h| < 0.2 = negligible, 0.2-0.5 = small, 0.5-0.8 = medium, > 0.8 = large
| Strategy | Beat% | Cohen's h | Effect Size |
|---|---|---|---|
| horoscope_sun reversed | 56.4% | +0.128 | NEGLIGIBLE |
| fibonacci_fool normal | 53.8% | +0.077 | NEGLIGIBLE |
| horoscope_nosun reversed | 53.5% | +0.071 | NEGLIGIBLE |
Reality Check: Even the best strategy has NEGLIGIBLE practical effect size. Statistically significant ≠ practically meaningful.
7.3 Out-of-Sample Testing
Problem: Patterns found in historical data might not hold in the future (overfitting).
Solution: Split data: Training (2014-2021) vs Testing (2022-2024).
| Strategy | Train (2014-2021) | Test (2022-2024) | Verdict |
|---|---|---|---|
| horoscope_sun reversed | 44.4% | 63.4% | ✓ IMPROVES |
| fibonacci_fool normal | 42.5% | 60.4% | ✓ IMPROVES |
| lucky_7 normal | 43.8% | 58.9% | ✓ IMPROVES |
| horoscope_nosun normal | 44.3% | 40.3% | ✗ DECLINES |
7.4 Performance by Market Condition
This is the most important finding. Backtests were split by market conditions:
- Bull: HODL return > 50%
- Bear: HODL return < -30%
- Sideways: Between -30% and +50%
| Strategy | Bull Market | Bear Market | Sideways | Best In |
|---|---|---|---|---|
| horoscope_sun reversed | 41.3% | 81.2% | 40.6% | BEAR |
| coin_flip normal | 7.8% | 84.1% | 33.6% | BEAR |
| dice_roll normal | 11.2% | 85.3% | 35.7% | BEAR |
| three_red reversed | 17.1% | 83.5% | 33.2% | BEAR |
🔥 DEVASTATING DISCOVERY: ALL strategies beat HODL primarily in BEAR MARKETS! This makes perfect sense—when the market crashes, HODL loses money, and ANY strategy that sells sometimes will outperform. The "skill" of stupid strategies is simply having an exit mechanism.
7.5 Sharpe Ratio Analysis
Sharpe Ratio = (Return - Risk-free) / Volatility. Higher = better risk-adjusted returns.
| Strategy | Avg Return | StdDev | Sharpe | Significant? |
|---|---|---|---|---|
| horoscope_nosun reversed | +29.3% | 86.3% | 0.339 | ✓ (Z=8.87) |
| horoscope_sun reversed | +32.9% | 108.4% | 0.304 | ✓ (Z=8.01) |
| HODL | +19.9% | 111.9% | 0.178 | ✓ (Z=4.79) |
| three_red reversed | +12.4% | 87.3% | 0.143 | ✓ (Z=3.84) |
| coin_flip normal | -5.7% | 72.8% | -0.078 | NO |
7.6 Cross-Validation Stability
5-fold cross-validation tests if results hold across different data slices:
| Strategy | Mean | StdDev | 95% CI | Stable? |
|---|---|---|---|---|
| horoscope_sun reversed | 56.7% | 28.2% | [1.3% - 112.0%] | ⚠️ UNSTABLE |
| three_red reversed | 47.5% | 8.0% | [31.8% - 63.3%] | ⚠️ UNSTABLE |
| coin_flip normal | 45.1% | 7.3% | [30.8% - 59.3%] | ⚠️ UNSTABLE |
Warning: High variance (28.2% std for horoscope_sun) means results vary wildly across different time periods.
7.7 Statistical Rigor Summary
| Test | horoscope_sun reversed | Interpretation |
|---|---|---|
| Raw p-value | 0.0006 | Highly significant |
| Bonferroni corrected | ✓ SURVIVES | Survives strictest correction |
| Effect size (Cohen's h) | 0.128 (NEGLIGIBLE) | Practical impact is tiny |
| 95% Confidence Interval | [52.8% - 59.9%] | Does NOT overlap 50% |
| Out-of-Sample (2022-24) | 63.4% beat rate | Works on unseen data |
| Bear Market Performance | 81.2% beat rate | Excels when HODL crashes |
| Bull Market Performance | 41.3% beat rate | Fails when HODL runs |
| Cross-Validation Stability | σ = 28.2% | Highly variable |
8. CONCLUSIONS
Part 1 Findings
After applying rigorous statistical testing:
- Can stupid strategies beat HODL? YES—horoscope_sun reversed achieves 56.4% (p<0.001, survives Bonferroni).
- But beating HODL is a LOW BAR. Any exit mechanism beats buy-and-hold during crashes. HODL is not a trading strategy—it's the absence of one.
- Effect size is NEGLIGIBLE. Cohen's h = 0.128 means the practical advantage is tiny.
- Results are UNSTABLE. 28% standard deviation across cross-validation folds.
Part 1 Verdict: Beating HODL proves nothing. HODL loses 70% in bear markets—of course any strategy with a sell button outperforms. This is like celebrating that you can outrun a parked car.
The Real Question
The true test isn't "Can monkeys beat doing nothing?" It's:
- Can monkeys beat RSI?
- Can monkeys beat MACD?
- Can monkeys beat Bollinger Bands?
- Can monkeys beat machine learning models?
These legitimate trading strategies also have exit mechanisms. They also avoid holding through crashes. If stupid strategies can beat THEM, that would be truly remarkable.
🔮 Coming in Part 7: The full Omega System (171 metrics across 6 levels) will be compared against these same stupid strategies. Then the ultimate question will be answered: Do coin flips and horoscopes beat actual trading intelligence?
Research Series Roadmap
| Part | Title | Status |
|---|---|---|
| 1 | Can Monkeys Beat HODL? (Baseline) | ✓ COMPLETE |
| 2 | Applying Monkey Strategies to Stock Markets | Coming Soon |
| 3 | Implementing Legitimate Quant Strategies | Coming Soon |
| 4 | Monkeys vs. Professional Strategies (THE MAIN EVENT) | Coming Soon |
| 5 | Complete Summary & Meta-Analysis | Coming Soon |
| 6 | Live AI Agent Trading | Coming Soon |
Final Verdict for Part 1: Stupid strategies beat HODL, but that's not impressive—HODL is a terrible benchmark. The real question is whether randomness can compete with actual trading intelligence. Stay tuned for Part 7, where it will be determined if a coin flip can beat a 171-metric trading system.
APPENDIX: STRATEGY CODE
# COIN FLIP
for close in prices:
if random.random() < 0.5: # HEADS
if cash > 0: position = cash * 0.999 / close; cash = 0
else: # TAILS
if position > 0: cash = position * close * 0.999; position = 0
# HOROSCOPE (NASA Gravity) - REVERSED
for timestamp, close, net_direction in data:
if net_direction > 0: # Planets pull NORTH → SELL (reversed)
if position > 0: cash = position * close * 0.999; position = 0
else: # Planets pull SOUTH → BUY (reversed)
if cash > 0: position = cash * 0.999 / close; cash = 0
# FIBONACCI FOOL
fibs = {1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987...}
for i, close in enumerate(prices):
if (i + 1) in fibs: # Trade at Fibonacci candle numbers
# Alternate buy/sell
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