GhostGauge — Brand Card (v1.1)
This document defines GhostGauge's public narrative (what it is, who it's for), naming conventions (G-Score vs GRS), band labels, tone, and ready-to-use copy. It exists so UI text, social posts, and docs stay consistent. Keep this file in sync with live config and methodology versions.
GhostGauge — Brand Card (v1.1)
A short, practical guide to what GhostGauge is, how it speaks, and how to present it to people with zero context.
Brand at a glance
- What it is: A daily, transparent, factor-weighted market risk dashboard for Bitcoin. It compresses diverse data into a single 0–100 G-Score (higher = higher risk) with full driver transparency.
- Who it's for: Hedge-fund PMs, quants, sophisticated retail, and market-curious readers who want signal over noise.
- Why it exists: To help people frame risk, not predict price. Decision support—clear, repeatable, explainable.
- Where it lives: GhostGauge at ghostgauge.com; analysis voice from GrayGhost (author of the TWIMM newsletter).
- How it feels: Professional, analytical, modern UI—occasional, tasteful noir accents (mainly in social/newsletter, not the app).
Brand architecture
- Platform / Product: GhostGauge
The destination and tool (dashboard, drivers, methodology, history/CSV, BTC⇄Gold, Sats per Dollar, Alerts). - Author / Persona: GrayGhost
Byline & narrative lens in newsletter/social. On-site copy stays sober; persona is a light flourish. - Metric (formal): GrayGhost Risk Score (GRS v3)
Methods, whitepaper, code comments, API/docs. - Metric (everyday): G-Score
Headlines, UI chips, social posts, casual usage.
One-liner & elevator pitch
- One-liner: GhostGauge turns market chaos into a single, transparent G-Score so you can calibrate risk at a glance.
- 30-second pitch: GhostGauge blends liquidity, momentum, term structure, macro, and social/attention into a 0–100 G-Score (higher = higher risk). Every input is sourced, time-stamped, normalized, and blended with outlier control and EWMA smoothing. No black boxes—click through to see the drivers and download the history.
Positioning & proof
- Positioning: Transparent risk telemetry for crypto + macro.
- Promise: Signals, not hype. Methods before marketing.
- Proof points:
- Five-pillar model with published inputs & weights (35/25/20/10/10).
- Winsorized z-scores → logistic 0–100; stale data auto-excluded with weight re-normalization.
- Factor History CSVs updated daily; Provenance with source notes, schema tripwires, and fallbacks.
- ETF Flows via robust parser (21-day sum) with staleness & outlier guards.
- Optional small adjustments: cycle residual & spike detector—capped and disclosed.
- Clear risk bands and plain-English playbook.
Audience & use cases
- PMs/Quants: Fast regime check; portfolio guardrails; risk-on/risk-off framing.
- Sophisticated retail: Sanity check against headlines & influencer noise.
- Media/Creators: Reliable daily artifact to cite/embed.
- You (GrayGhost): Anchor for weekly commentary and cross-asset context.
Messaging pillars (what we talk about)
- Transparency — clear inputs, weights, freshness.
- Discipline — stable methodology; versioned updates.
- Context — show drivers, not just a number.
- Restraint — risk framing ≠ trade signals.
- Macro-aware — liquidity and cross-market data matter.
Voice & tone
- Primary: Crisp, neutral, specific. Short sentences. No predictions.
- Persona seasoning (optional): A brief noir-tinged line in social/newsletter—not in the app chrome.
- Always include: UTC timestamp and a path to methodology.
Ready-to-use lines
- "Signals, not hype."
- "One score, five pillars, zero mystery."
- "Transparent risk for macro + crypto."
Naming & notation
Public names
- G-Score (BTC) / Bitcoin G-Score
- (Future-ready) G-Score (ETH)
- GhostGauge: product/site
- XAU Lens: BTC↔Gold module
- Sats Lens: Satoshis per Dollar module
- Alerts: zero-cross & band-change notices
Formal references
- GRS v3 — GrayGhost Risk Score, versioned methodology.
- Modules: Drivers, Methodology, History, XAU Lens, Sats Lens, Alerts.
Risk bands (display + copy — align with app defaults)
- 0–14 Aggressive Buying
- 15–34 Regular DCA Buying
- 35–49 Moderate Buying
- 50–64 Hold & Wait
- 65–79 Reduce Risk
- 80–100 High Risk
(Note: these bands are configurable in app config; keep brand copy in sync with the live config and use live config as main source)
Slugs / API / data keys (examples)
- gscore_btc, grs_version=3
- pillar_liquidity, pillar_momentum, pillar_leverage, pillar_macro, pillar_social
Do / Don't (naming)
- Do: Use G-Score in UI/social; use GRS in docs/methods.
- Do: Qualify asset explicitly (e.g., "Bitcoin G-Score").
- Don't: Call it an "index" or imply trade signals.
- Don't: Use sensational qualifiers ("warning!", "guaranteed!", etc.).
Headline / subhead templates
Dashboard H1
Today's Bitcoin G-Score: [value]
Dashboard subhead / tooltip
The GrayGhost Risk Score (GRS v3) blends five pillars into a transparent 0–100 risk measure.
Drivers section
Drivers — Liquidity · Momentum · Term Structure · Macro · Social
Band legend (match live config)
0–14 Aggressive Buying · 15–34 Regular DCA Buying · 35–49 Moderate Buying · 50–64 Hold & Wait · 65–79 Reduce Risk · 80–100 High Risk
Methodology CTA
Methodology (GRS v3) — inputs, normalization, weights, and staleness handling
SEO title
GhostGauge — Bitcoin G-Score (0–100 multi-factor market risk)
SEO description
Daily, transparent, factor-weighted risk for BTC. Liquidity, momentum, term structure, macro, social. Signals, not hype.
Social & newsletter patterns
Crossing-band alert (X/Twitter, from @grayghost)
Bitcoin G-Score just crossed 70 — High risk. Drivers + chart on GhostGauge. ghostgauge.com
Weekly wrap (TWIMM)
W/W Δ: 58 → 66. Liquidity led; term structure cooled. Full breakdown in Drivers. ghostgauge.com
Multi-asset tease (future)
ETH G-Score: 48 (Hold & Wait). Compare BTC/ETH drivers on GhostGauge.
Persona-seasoned alt (sparingly)
"The street's loud. Signals aren't. BTC G-Score 72 — High."
How the metric works (brief public summary)
- Inputs → Pillars: Liquidity/Flows (35%), Momentum/Valuation (25%), Term Structure/Leverage (20%), Macro (10%), Social/Attention (10%).
- Normalization: Winsorize tails → z-score vs history → apply direction (invert where "more = less risk") → logistic 0–100.
- Smoothing: EWMA with configurable half-life; stale data excluded with weight re-normalization.
- Transparency: Every input sourced, timestamped, and downloadable as CSV.