Liquidity Monitor & Order Book Analysis

Description

Real-time order book depth analysis and liquidity monitoring for optimal trade execution.

Features

• Order Book Depth - Track bid/ask depth at multiple levels
• Liquidity Scoring - Rate asset liquidity (A-F grade)
• Spread Analysis - Bid-ask spread monitoring with alerts
• Slippage Estimator - Predict slippage for order sizes
• Whale Detection - Identify large orders/walls
• Imbalance Alerts - Order book imbalance notifications
• VWAP Tracking - Volume-weighted average price
• Execution Quality - Post-trade analysis vs benchmarks

Use Cases

1. Optimal Entry - Wait for better liquidity before entry
2. Exit Planning - Size exits based on available liquidity
3. Market Making - Identify spread opportunities
4. Whale Following - Track large order movements
5. HFT Signals - Microstructure-based signals

Commands

liquidity check BTC/USDT
orderbook depth ETH/USDT --levels 20
slippage estimate BTC/USDT --size 50000
spread alert BTC/USDT --max 0.1%
whale watch BTC/USDT --min-size 1000000
vwap track SPY --window 1d
execution analyze --trade-id xyz123
liquidity heatmap --top 50

Parameters

Parameter	Type	Default	Description
levels	int	10	Order book depth levels
min_size	float	10000	Minimum USD for whale detection
spread_alert	float	0.5%	Alert when spread exceeds
imbalance_ratio	float	2.0	Bid/ask imbalance threshold
update_interval	string	1s	Real-time update frequency
exchange	string	auto	Exchange for order book data

Liquidity Grades

Grade	Spread	Depth ($1M)	Description
A+	<0.01%	>$50M	Institutional grade
A	<0.05%	>$10M	Highly liquid
B	<0.1%	>$1M	Good liquidity
C	<0.5%	>$100K	Moderate
D	<1%	>$10K	Thin
F	>1%	<$10K	Illiquid - avoid

Outputs

• Real-time order book visualization
• Liquidity score and grade
• Slippage estimates for order sizes
• Whale order alerts
• Spread history charts
• Execution quality reports

Technical Implementation

• WebSocket connections to exchange order books
• Redis for real-time data caching
• Time-series database for historical depth
• Streaming aggregation for VWAP
• ML models for slippage prediction

Risk Considerations

• Order books can be spoofed (fake orders)
• Liquidity can evaporate quickly in volatility
• Different exchanges have different depth
• Latency matters for execution decisions