A quantitative overview of cross-venue structural stability, liquidity trajectories, and intraday regime transitions.
1. Regime & Volatility Analysis
The market maintained a dominant Absorption regime, accounting for 119230 state blocks, indicating structural stability. Despite this, 26 instances of Failed Expansion were recorded, demonstrating rejected breakout attempts. Localized Liquidation Cascades (48 events) and Momentum Exhaustion (38 events) introduced transient volatility within specific venues.
Verified Execution & Macro Proofs:
- (See Verified Execution below)
Verified Execution & Macro Proofs
• 45.20 bps (Source Date: 2026-06-24)
Extract the raw multi-venue Parquet tick data for this epoch via thrunode_archive
It visualizes the structural behavior of Bitcoin across the industry's most important trading venues.
- Venues (Y): Specific markets from Spot to Perps.
- Time (X): 24-hour day broken into 48 discrete 30-minute segments.
- Teal Blocks: Absorption. Passive liquidity absorbing aggressive flow.
- Brightness: Bright = High Conviction. Faint = Transitional/Noisy.
- White Lines: Abrupt Structural Transitions.
- Grey Line (Hurst): Price persistence (High = trend, Low = noise).
2. Liquidation Risks & Funding Trajectories
Funding rates on [Deribit BTC-PERPETUAL] exhibited persistent negative divergence, indicating sustained short pressure. Conversely, [Hyperliquid BTC] recorded a positive funding Z-score, suggesting fragmented sentiment. Despite a prevailing "Clean" leverage state, localized liquidation cascades on [OkxInverse BTC-USD] and [BybitInverse BTCUSD] introduced long/short squeeze risks, particularly in inverse perpetuals.
Verified Execution & Macro Proofs:
- (See Verified Execution below)
Verified Execution & Macro Proofs
• baseline risk-free levels
Extract the raw multi-venue Parquet tick data for this epoch via thrunode_archive
This chart is the Squeeze Radar, a specialized risk map for Bitcoin derivative markets. It visualizes the "tension" in the market by tracking where the most dangerous liquidation risks are building up across major exchanges.
The chart is divided into four sections based on two critical factors: Position Crowdedness (Vertical Axis) and Holding Cost (Horizontal Axis).
- The Red Zone (Top-Right - "Long Squeeze Danger"): This is the danger zone. Positions here have rising Open Interest (more people piling in) and high Funding Rates (buyers are paying a premium to stay long). If the price drops slightly, these "crowded longs" may be forced to sell all at once, causing a crash.
- The Green Zone (Bottom-Left - "Short Covering Exhaustion"): This is the "relief" zone. Positions here have falling Open Interest (shorts are closing) and negative Funding (sellers are paying buyers). This usually signals that a downward move is running out of steam.
- The Circles (Nodes): The solid circles represent where those exchanges ended the day.
- The Size of the Circle: The larger the circle, the more trading volume that exchange handled.
- The Dashed Trails (Trajectories): These "scribbles" are the most important part—they show the path each exchange took over the last 24 hours. Instead of just a single data point, you can see the "journey" of the market sentiment.
3. Passive Liquidity & CVD Divergences
| Venue/Instrument | Event Type | Time (UTC) | Confidence | Key Metric |
|---|---|---|---|---|
| [OkxLinear BTC-USDT] | Passive Absorption | 1 min ago | 0.8000 | efficiency_ratio: 0.1198, vpin: 0.7320 |
| [Deribit BTC_USDC-PERPETUAL] | Passive Absorption | 1 min ago | 0.8000 | efficiency_ratio: 0.1164, vpin: 0.7243 |
| [CoinbaseSpot BTC-USD] | Passive Absorption | 4 min ago | 0.8000 | efficiency_ratio: 0.1257, vpin: 0.7709 |
| [OkxInverse BTC-USD] | Liquidation Cascade | 2.0 hours ago | 0.7000 | oi_velocity: -25.03, leverage_tier: Clean |
| [BybitInverse BTCUSD] | Liquidation Cascade | 2.0 hours ago | 0.7000 | oi_velocity: -21.48, leverage_tier: Clean |
| [OkxInverse BTC-USD] | Momentum Exhaustion | 2s ago | 0.7500 | OI Velocity: -10.50 BPS |
| [Bybit BTCUSDT] | Momentum Exhaustion | 5s ago | 0.7500 | OI Velocity: -26.88 BPS |
| [OkxInverse BTC-USD] | Failed Expansion | 15 minutes ago | 0.6000 | exit_regime: Indeterminate |
| [Deribit BTC-PERPETUAL] | Failed Expansion | 15 minutes ago | 0.6000 | exit_regime: Indeterminate |
Passive liquidity walls were evident across multiple venues, with [OkxLinear BTC-USDT], [Deribit BTC_USDC-PERPETUAL], and [CoinbaseSpot BTC-USD] absorbing aggressive selling. Orderbook imbalances manifested as liquidation cascades on [OkxInverse BTC-USD] and [BybitInverse BTCUSD]. CVD divergences were indicated by momentum exhaustion on [OkxInverse BTC-USD] and [Bybit BTCUSDT], suggesting depleted informed flow.
Verified Execution & Macro Proofs:
- (See Verified Execution below)
Verified Execution & Macro Proofs
• 420,000,000 USDT (220,000,000 USDT on Ethereum, 100,000,000 USDT on Ethereum, 100,000,000 USDT on Ethereum)
Extract the raw multi-venue Parquet tick data for this epoch via thrunode_archive
This chart visualizes the true macroeconomic divergence between Global Spot and Derivative markets. By aggregating liquidity across all canonical exchanges, it acts as a highly sensitive gauge for systemic buying or selling pressure.
CVD tracks aggressive market orders (market buys minus market sells). We aggregate this across all canonical exchanges into two distinct curves:
- Spot CVD (The "Real" Demand): Tracks actual asset accumulation. When this rises, actual assets are being bought and removed from order books.
- Perp CVD (The Speculative Demand): Tracks derivative traders using leverage. Divergences (e.g., Perp CVD rising while Spot CVD drops) often signal fragile, easily-liquidated trends.
- Order Book Imbalance (Background): The background heatmap shows the structural weight of passive limit orders. Brighter colors indicate passive liquidity walls stepping in to absorb aggressive volume.
- Macro Events (Vertical Lines): We filter billions of daily ticks to cluster systemic structural events—like Global Liquidation Cascades or massive Block Trades—across multiple exchanges simultaneously.
4. Nearest Historical Structural Analogs (FAISS Similarity)
Algorithmic nearest neighbors based on order-flow efficiency, VPIN toxicity, Hurst exponent, and derivatives reflexivity: