A high-frequency paper trading framework for building and testing autonomous crypto trading agents with multi-indicator technical analysis.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install hft-paper-trader
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install hft-paper-trader using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is HFT Paper Trader?
The HFT Paper Trader is a sophisticated framework designed for Openclaw Skills that enables developers to build, test, and refine autonomous crypto trading agents. It bridges the gap between raw market data and actionable execution by implementing a multi-indicator TA engine (RSI, MACD, EMA, BB, OBV, StochRSI) that generates objective signal scores for paper trading.
By utilizing this skill within the Openclaw Skills ecosystem, developers can simulate high-frequency trading environments without financial risk, targeting hundreds of trades per day to validate complex trading logic and position sizing strategies.
HFT Paper Trader Use Cases
- Simulate high-frequency crypto trading (300+ trades/day) using real-time market data.
- Backtest complex technical analysis strategies across a wide watchlist including BTC, ETH, and SOL.
- Refine autonomous agent decision-making using the Kelly criterion for position sizing.
- Audit and improve trading logic through automated lesson logging and performance tracking in the Openclaw Skills environment.
How HFT Paper Trader Works
- Market Data Retrieval: The skill pulls public API data from Binance for assets on the defined watchlist.
- TA Engine Processing: It calculates seven distinct technical indicators to generate a confluence score between -10 and +10.
- Position Sizing: Using the Kelly criterion (quarter-Kelly), it determines the optimal 0.05% risk per trade based on current NAV.
- Execution: It updates the paper portfolio and records every transaction in a ledger for full transparency.
- Feedback Loop: The system logs losses into a lessons file to help the Openclaw Skills agent adapt its future logic.
HFT Paper Trader Setup
To get started with this skill, initialize your environment using the following commands:
# Install the HFT Paper Trader skill
openclaw install hft-paper-trader
# Configure the local environment and Binance API connection
hft-paper-trader --setup
# Start the trading simulation for the entire watchlist
hft-paper-trader scan --all
HFT Paper Trader Data Schema & Taxonomy
The HFT Paper Trader maintains a structured data ecosystem to ensure all Openclaw Skills activities are auditable:
| File | Format | Description |
|---|---|---|
| PORTFOLIO.json | JSON | Current net asset value (NAV), balances, and open positions. |
| LEDGER.csv | CSV | Audit trail containing entry price, stop-loss, targets, and trade outcomes. |
| lessons.md | Markdown | A self-improvement log used by the agent to document and learn from losses. |
HFT Paper Trader Advanced Features
- OBV Divergence Detection: Automatically identifies hidden accumulation or distribution patterns to improve entry accuracy.
- Multi-indicator Confluence: Integrates seven different technical indicators into a single, weighted signal score for better signal-to-noise ratios.
- Risk Drawdown Controls: Built-in safety mechanism that triggers an auto-pause if the daily NAV drops by 2%.
- Autonomous Watchlist Scanning: Efficiently monitors over 20 top-tier crypto assets simultaneously within the Openclaw Skills framework.
SKILL.md
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