Comprehensive Crypto Trading System Development
Budget: ₹37,500 – ₹75,000 INR
Market Making & Arbitrage System — Requirements Document
1. System Overview
Build a crypto trading system that:
• Provides market making across multiple exchanges.
• Provides arbitrage trading between exchanges when profitable opportunities exist.
• Allows full control through an Admin Panel.
• Offers account monitoring for customers (Customer Panel).
• Is scalable, modular, and secure.
2. Features
A. Market Making Bot
• Multi-Exchange Support: Binance, KuCoin, Gate.io, OKX, MEXC, etc.
• Token Coverage: Add/remove tokens easily from frontend.
• Spread Management:
◦ Configure bid-ask spread per token and per exchange.
◦ Auto-adjust spread based on market volatility.
• Order Volume Control:
◦ Define min/max order sizes.
◦ Randomize slight variations to make activity look natural.
• Order Update Logic:
◦ Cancel and replace stale orders periodically (e.g., every X seconds).
◦ Keep X depth levels filled on both sides.
• API Key Management:
◦ Each exchange connection managed securely.
◦ API keys stored encrypted.
B. Arbitrage Bot
• Price Monitoring:
◦ Real-time monitoring of all exchange prices.
◦ Identify profitable arbitrage opportunities instantly.
• Execution Strategy:
◦ Simultaneous execution (atomic style) - Buy on cheaper exchange, Sell on expensive exchange at same time.
• Order Matching:
◦ Trade with real traders only: Detect and avoid matching your own market-making orders.
• Configurable Parameters:
◦ Min profit % required to trigger trade.
◦ Max funds allocation per arbitrage trade.
◦ Cooldown period between arbitrages.
• Exchange Fees Handling:
◦ Incorporate trading fees into arbitrage profit calculations.
C. Admin Panel (Backend + Frontend)
• Dashboard:
◦ Overview of balances across all exchanges.
◦ Real-time PnL (Profit and Loss) reporting.
• Market Making Controls:
◦ Set price range, spread, volume per token per exchange.
◦ Pause/resume bots.
• Arbitrage Bot Controls:
◦ Turn arbitrage on/off.
◦ Set parameters for arbitrage (min profit, max funds per trade, etc.).
• Alerts and Notifications:
◦ Set threshold alerts (low balance, failed orders, etc.).
• Audit Logs:
◦ All actions logged with timestamp and user info.
D. Customer Panel
• Account Monitoring:
◦ View balances across all exchanges.
◦ View active orders and positions.
• Reports:
◦ Daily/weekly/monthly trade reports.
◦ Separate reporting for market-making and arbitrage profits.
• Simple clean UI:
◦ Focused on viewing, not controlling.
E. Reporting Module
• Trade Reports:
◦ Total number of trades per token per exchange.
◦ PnL per token, per exchange.
◦ Arbitrage profits separately.
• Export Options:
◦ Excel, CSV, PDF exports.
• Performance Metrics:
◦ ROI %, win rate, avg profit per arbitrage, etc.
F. Intelligent Features
• Fake Trade Detection:
◦ Algorithms to check if order book is manipulated.
• Auto-Adaptation:
◦ If liquidity is thin, bot reduces order size automatically.
• Real-Volume Protection:
◦ Only place orders if reasonable volume on the exchange exists (avoid isolated trades).
• Retry Mechanism:
◦ Retry failed orders with exponential backoff.
• Time-in-Force Options:
◦ Use FOK (Fill or Kill), IOC (Immediate or Cancel), GTC (Good Till Cancelled) based on strategy.
G. Security Requirements
• Encryption:
◦ API keys encrypted at rest and in transit.
• Authentication:
◦ Admin panel login with MFA (Multi-Factor Authentication).
• Role-based Access Control:
◦ Admin vs Customer separation clearly enforced.
• IP Whitelisting Option:
◦ Allow access to APIs only from trusted IPs.
H. Technical Requirements
• Language: Python (backend bots), React/Vue (frontend).
• Database: PostgreSQL (for trades, settings, logs).
• Websocket Integration: For real-time updates from exchanges.
• Scalability:
◦ Microservice architecture recommended (separate services for market making, arbitrage, frontend, backend).
• Hosting:
◦ Preferably cloud-based (AWS, GCP) with Kubernetes for scalability.
Additional Recommendations
• Use ccxt library (or custom wrappers) to standardize API connections.
• Include backtesting module to simulate strategies before live deployment.
• Add simulation mode for new tokens before going real live trading.
• Create watchdog service to monitor bots' health and auto-restart if crash detected.
Example Frontend Layout
• Admin Dashboard
◦ [Token Settings] [Exchange Settings] [Bots Control] [Reports] [Audit Logs]
• Customer Dashboard
◦ [Balances] [Trade Reports] [Performance]
Will need intigration with at least 5 Exchanges for now - Exchange intigration should be modular and adding exchange should be easy.. exchanges needed for now are .. LBank , Pancake Swap, WEEX , Binance, ConDCX
1. System Overview
Build a crypto trading system that:
• Provides market making across multiple exchanges.
• Provides arbitrage trading between exchanges when profitable opportunities exist.
• Allows full control through an Admin Panel.
• Offers account monitoring for customers (Customer Panel).
• Is scalable, modular, and secure.
2. Features
A. Market Making Bot
• Multi-Exchange Support: Binance, KuCoin, Gate.io, OKX, MEXC, etc.
• Token Coverage: Add/remove tokens easily from frontend.
• Spread Management:
◦ Configure bid-ask spread per token and per exchange.
◦ Auto-adjust spread based on market volatility.
• Order Volume Control:
◦ Define min/max order sizes.
◦ Randomize slight variations to make activity look natural.
• Order Update Logic:
◦ Cancel and replace stale orders periodically (e.g., every X seconds).
◦ Keep X depth levels filled on both sides.
• API Key Management:
◦ Each exchange connection managed securely.
◦ API keys stored encrypted.
B. Arbitrage Bot
• Price Monitoring:
◦ Real-time monitoring of all exchange prices.
◦ Identify profitable arbitrage opportunities instantly.
• Execution Strategy:
◦ Simultaneous execution (atomic style) - Buy on cheaper exchange, Sell on expensive exchange at same time.
• Order Matching:
◦ Trade with real traders only: Detect and avoid matching your own market-making orders.
• Configurable Parameters:
◦ Min profit % required to trigger trade.
◦ Max funds allocation per arbitrage trade.
◦ Cooldown period between arbitrages.
• Exchange Fees Handling:
◦ Incorporate trading fees into arbitrage profit calculations.
C. Admin Panel (Backend + Frontend)
• Dashboard:
◦ Overview of balances across all exchanges.
◦ Real-time PnL (Profit and Loss) reporting.
• Market Making Controls:
◦ Set price range, spread, volume per token per exchange.
◦ Pause/resume bots.
• Arbitrage Bot Controls:
◦ Turn arbitrage on/off.
◦ Set parameters for arbitrage (min profit, max funds per trade, etc.).
• Alerts and Notifications:
◦ Set threshold alerts (low balance, failed orders, etc.).
• Audit Logs:
◦ All actions logged with timestamp and user info.
D. Customer Panel
• Account Monitoring:
◦ View balances across all exchanges.
◦ View active orders and positions.
• Reports:
◦ Daily/weekly/monthly trade reports.
◦ Separate reporting for market-making and arbitrage profits.
• Simple clean UI:
◦ Focused on viewing, not controlling.
E. Reporting Module
• Trade Reports:
◦ Total number of trades per token per exchange.
◦ PnL per token, per exchange.
◦ Arbitrage profits separately.
• Export Options:
◦ Excel, CSV, PDF exports.
• Performance Metrics:
◦ ROI %, win rate, avg profit per arbitrage, etc.
F. Intelligent Features
• Fake Trade Detection:
◦ Algorithms to check if order book is manipulated.
• Auto-Adaptation:
◦ If liquidity is thin, bot reduces order size automatically.
• Real-Volume Protection:
◦ Only place orders if reasonable volume on the exchange exists (avoid isolated trades).
• Retry Mechanism:
◦ Retry failed orders with exponential backoff.
• Time-in-Force Options:
◦ Use FOK (Fill or Kill), IOC (Immediate or Cancel), GTC (Good Till Cancelled) based on strategy.
G. Security Requirements
• Encryption:
◦ API keys encrypted at rest and in transit.
• Authentication:
◦ Admin panel login with MFA (Multi-Factor Authentication).
• Role-based Access Control:
◦ Admin vs Customer separation clearly enforced.
• IP Whitelisting Option:
◦ Allow access to APIs only from trusted IPs.
H. Technical Requirements
• Language: Python (backend bots), React/Vue (frontend).
• Database: PostgreSQL (for trades, settings, logs).
• Websocket Integration: For real-time updates from exchanges.
• Scalability:
◦ Microservice architecture recommended (separate services for market making, arbitrage, frontend, backend).
• Hosting:
◦ Preferably cloud-based (AWS, GCP) with Kubernetes for scalability.
Additional Recommendations
• Use ccxt library (or custom wrappers) to standardize API connections.
• Include backtesting module to simulate strategies before live deployment.
• Add simulation mode for new tokens before going real live trading.
• Create watchdog service to monitor bots' health and auto-restart if crash detected.
Example Frontend Layout
• Admin Dashboard
◦ [Token Settings] [Exchange Settings] [Bots Control] [Reports] [Audit Logs]
• Customer Dashboard
◦ [Balances] [Trade Reports] [Performance]
Will need intigration with at least 5 Exchanges for now - Exchange intigration should be modular and adding exchange should be easy.. exchanges needed for now are .. LBank , Pancake Swap, WEEX , Binance, ConDCX