Lick Tester - Aster Hunter Backtester

A comprehensive backtesting platform designed to optimize settings for the Aster Lick Hunter Node application. This tool provides real-time liquidation tracking and strategy optimization capabilities to generate optimal trading parameters for AsterDEX strategies.

⚠️ DEVELOPMENT WARNING: This application is currently in active development and should be considered experimental. All trading strategies, optimizations, and backtesting results generated by this tool should be assumed to be unprofitable until thoroughly validated. Do not use any generated settings for live trading without extensive testing and verification. Trading cryptocurrencies involves substantial risk of loss.

Note: This backtesting tool is used to test and optimize trading strategies, generating settings that can then be applied to the Aster Lick Hunter Node for live trading.

Features

• Real-time Liquidation Tracking: Monitor liquidations from AsterDX exchange
• Interactive Charts: Price analysis with TradingView-style interface
• Backtesting Engine: Test trading strategies against historical data
• Strategy Optimization: Parameter optimization with wallet balance validation
• Threshold System: Cumulative volume-based trading strategy options

Screenshots

Main Dashboard

The main dashboard showing real-time liquidation tracking, price charts, trades, and liquidation analytics

Strategy Optimization

Strategy optimization interface showing backtesting progress and price chart with liquidations

Quick Start

git clone https://github.com/birdbathd/lick_tester
cd lick_tester
npm install
# Copy liquidation.db from Aster Lick Hunter Node and place in data/ (optional)
npm start

Prerequisites: You can optionally use the liquidation.db file from the Aster Lick Hunter Node application for additional historical data analysis, but this tool also monitors liquidations independently.

Access the dashboard at http://localhost:3020

Configuration

Port Configuration

Default port is 3020. To change:

Environment Variable:

PORT=3002 npm start

Edit server.js: Change DEFAULT_PORT = 3020 in the configuration section.

Trading Parameters

Configure liquidation thresholds, leverage, and risk management settings in the web interface or config file.

Usage

1. Monitor Liquidations: View real-time liquidation events and volume data
2. Backtest Strategies: Test trading parameters against historical liquidation data
3. Optimize Parameters: Find optimal strategy settings using the Config Hunter
4. Analyze Performance: Compare instant vs threshold-based trading systems

Backtesting Systems

Instant System

Simulates trades immediately when liquidation volume exceeds threshold.

Threshold System

Accumulates liquidations over time window, simulates trades when cumulative volume exceeds threshold.

Backtesting Assumptions & Caveats

⚠️ Important: The backtesting engine makes several assumptions that may not reflect real-world trading conditions. Results should be considered optimistic estimates.

Trading Costs & Market Impact

Fees (10 basis points = 0.10%)

• Applied to both entry and exit of every trade
• Assumes taker fees (market orders) for realistic modeling
• Higher than typical maker fees to account for urgency during liquidation events

Slippage (8 basis points = 0.08%)

• Applied to both entry and exit prices
• Accounts for adverse price movement when executing trades
• Conservative estimate for normal market conditions
• Caveat: During actual liquidation cascades, slippage could be significantly higher

Price Execution

• Entries use "next candle open" price + slippage
• Exits use exact TP/SL levels - slippage
• Caveat: Real execution may face partial fills, requotes, or rejected orders

Market Assumptions

Liquidity

• Assumes unlimited liquidity at calculated prices
• Reality: Large liquidation events often reduce available liquidity
• Impact: Real trades might get worse fills or partial execution

Order Execution

• Perfect TP/SL execution at exact levels
• Reality: Stop losses may slip during volatile periods
• Reality: Take profits might not fill completely at target levels

Position Management

Tie Resolution

• When both TP and SL hit in same candle, assumes "worst case" (SL hit first)
• Reality: Actual outcome depends on intrabar price action

Recommended Usage

1. Use results as upper bounds - actual performance will likely be lower
2. Apply additional safety margins to any generated parameters
3. Paper trade strategies before live implementation
4. Start with smaller position sizes than backtests suggest
5. Monitor real execution costs and adjust models accordingly

The backtesting tool is designed to find potentially profitable strategies, but real-world execution introduces additional challenges not captured in these simulations.

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request

Acknowledgments

This project is a backtesting and optimization tool designed to work with the Aster Lick Hunter Node application by CryptoGnome.

The Lick Tester generates optimized trading parameters and settings through backtesting, which can then be applied to the Aster Lick Hunter Node for live trading execution.

Charts powered by TradingView Lightweight Charts - professional financial charts for web applications.

License

MIT

See LICENSE file for details.