What Is Risk? (And Why It Matters)
Risk isn't a villain. It's the range of possible outcomes—and the cost of being wrong. Bitcoin G-Score turns today's market conditions into a 0–100 read so you can size decisions like an adult.
🎯 Risk in Plain English
Risk isn't "bad." It's the range of possible outcomes around what you expect and the price you pay to chase returns. Think football odds: even if you're sure the better team will win, the spread and payout decide if the bet makes sense. If the reward doesn't match the risk, you pass.
Markets work the same way. Conditions can be quiet and forgiving or hot and jumpy. Bitcoin G-Score turns that backdrop into a 0–100 read: higher = a crowdier, more fragile tape where small shocks hit harder; lower = calmer conditions that have historically offered better entry points.
Remember: It's context, not advice. The number doesn't predict tomorrow; it tells you how forgiving or unforgiving the environment is so you can size your conviction accordingly.
🧠 The 3-Part Mental Model
🎲 Odds
How likely are things to go right vs wrong? Likelihoods, not certainties.
💰 Payoff
If you're right/wrong, how big is it? Size of right/wrong outcomes.
🎒 Backpack
How much time/capital/emotional room do you have? Your capacity to handle swings.
Bitcoin G-Score = the field conditions.
Green field: good footing (mistakes hurt less).
Red field: slippery turf (small slips become big falls).
🔢 From Idea to Number: The Bitcoin G-Score
Five pillars normalized to history, winsorized, mapped to 0–100, combined by fixed weights. Small Cycle/Spike adjustments, shown as pills. No advice; just conditions.
📊 Bands That Translate Numbers
Aggressive Buying (0-14)
Market gives you a friendlier spread. Historically better entry points.
Regular DCA Buying (15-34)
Good conditions for regular purchases. Continue your strategy.
Moderate Buying (35-49)
Balanced conditions. Reduce position size and be more selective.
Hold & Wait (50-64)
Hold existing positions. Wait for better conditions.
Reduce Risk (65-79)
Consider taking profits. The spread is getting tough.
High Risk (80-100)
Tough spread—mistakes cost more. Size down your conviction.
Informational framing only. These bands provide context, not commands.
🎭 Quick Analogies That Land
Point Spread
A great team at –14 isn't the same bet as –3. Higher G-Score = a worse spread for buyers. Even if you're confident in the outcome, the payout has to justify the risk.
Example:
G-Score 30: Like betting on the favorite at –3 (good value). G-Score 80: Like betting on the favorite at –14 (tough spread).
High score ≠ crash tomorrow. It means less forgiveness if you're early or wrong.
🔗 How to Use This with the Dashboard
Dashboard Checklist:
- ✓Check Freshness (UTC timestamps)
- ✓Scan Cycle & Spike pills
- ✓See each factor's risk, weight, contribution
- ✓Open History to view recent trend/CSV
Quick Links:
❓ FAQ
Does a 70 mean sell?
No. It means conditions are crowded and less forgiving. Use it to calibrate your conviction, not to chase trades.
Is this a timing tool?
It's a context tool. It tells you about market conditions, not when to buy or sell.
Why not "signals"?
Signals without context break more people than they help. Context helps you make better decisions.
What if inputs are stale?
We label Stale/Very Stale; treat the read with caution. Fresh data is more reliable.
📖 Micro Glossary
Breadth (21d)
X of 15 ETFs had net inflows over 21 trading days. More = more distributed demand.
HHI
Flow concentration. Higher = crowded in few funds; lower = spread out.
BMSB
20-week SMA / 21-week EMA support band.
Contribution
Factor score × weight.
ETF Flows
Daily net money moving into/out of Bitcoin ETFs. Positive = buying pressure.
Market Share
Percentage of total ETF flows captured by each fund. Shows dominance.
Trend Analysis
Directional movement pattern (up/down/stable) based on recent data.
Confidence Interval
Statistical range showing prediction reliability (60-95%).
ARIMA
AutoRegressive Integrated Moving Average - time series forecasting model.
LSTM
Long Short-Term Memory neural network for pattern recognition.
Ensemble Method
Combining multiple ML models for better accuracy than any single model.
MAPE
Mean Absolute Percentage Error - measures prediction accuracy.
RMSE
Root Mean Square Error - measures prediction precision.
⚠️ Important Reminder
Informational only. No recommendations. This tool provides context about market conditions, not investment advice. Always check timestamps and use your own judgment.
New here?
Risk isn't a villain, it's the range of outcomes and the cost of being wrong. Bitcoin G-Score turns today's Bitcoin market conditions into a 0–100 read (higher = riskier). Use bands as context, not commands: low = friendlier spread, mid = neutral, high = less forgiving. Check timestamps, Cycle/Spike pills, and factor contributions to see what's driving the tape.
Try the Risk Score
Hold & Wait
Hold existing positions. Wait for better conditions.