98 lines
3 KiB
Markdown
98 lines
3 KiB
Markdown
# Build Your Own Crypto Trading Bot – Course Repository
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Welcome to the private repository for the **"Build Your Own Crypto Trading Bot – Hands-On Course with Alex"** by QuantJourney.
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This repository contains materials, templates, and code samples used during the 6 live sessions held in June 2025.
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> ⚠️ This repository is for registered participants only.
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---
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## Content Overview
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**Session 1: Foundations & Data Structures**
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- Set up Python, IDE, and required libraries
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- Pandas basics for financial time series
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- Understanding OHLCV format
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- Create your first crypto DataFrame with sample data
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**Session 2: Data Acquisition & Exchange Connectivity**
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- WebSocket basics for real-time crypto feeds (Binance focus)
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- Fail-safe reconnection logic and error handling
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- Logging basics for live systems
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- Build tools: order flow scanner, liquidation monitor, funding rate tracker
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**Session 3: Data Processing & Technical Analysis**
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- API access using CCXT
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- Handle rate limits and API error scenarios
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- Reconnect & retry mechanisms
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- Use pandas-ta to compute SMA, EMA, RSI
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- Create your own indicator pipeline
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**Session 4: Strategy Development & Backtesting**
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- Overview of strategy types (trend, mean reversion)
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- Backtesting with `backtesting.py`
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- Compute Sharpe ratio, drawdown, profit factor
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- Add position sizing, SL/TP, and walk-forward logic
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- Adjust for fees, slippage, and latency
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**Session 5: Bot Architecture & Implementation**
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- Bot system design: event-driven vs loop-based
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- Core components: order manager, position tracker, error handler
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- Risk constraints: daily limits, max size
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- Logging & monitoring structure
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- Write the engine core for your bot
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**Session 6: Live Trading & Deployment**
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- API keys and secure credential handling
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- Deployment targets: local, VPS, cloud (e.g., Hetzner)
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- Running 24/7: restart logic, alerting
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- Final bot launch + testing in production
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- Send alerts via Telegram or email
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---
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## 🤖 AI-Enhanced Trading
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Bonus section:
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- Use ChatGPT/Claude for strategy suggestions
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- Integrate AI-based filters or signal generation
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- Let LLMs help you refactor and extend your logic
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---
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## 📁 Repository Structure
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```text
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/Session_01/ # Foundations & DataFrame Handling
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/Session_02/ # WebSockets & Real-Time Feed Tools
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/Session_03/ # Indicators & Analysis
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/Session_04/ # Backtesting + Strategy Logic
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/Session_05/ # Trading Bot Core Engine
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/Session_06/ # Live Deployment and Monitoring
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/templates/ # Starter and final bot code
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/utils/ # Helper scripts for logging, reconnection, etc.
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README.md # You are here
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```
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---
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## 🛠 Requirements
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- Python 3.10+
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- Install dependencies per session in each folder or via a top-level `requirements.txt` (provided)
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---
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## 📫 Support
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You can reach Alex directly at [alex@quantjourney.pro](mailto:alex@quantjourney.pro) for post-course support (1 week included).
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---
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## ⚠️ Disclaimer
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This project is for **educational use only**. No financial advice. Always trade with caution and use proper risk management.
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---
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Happy coding – and trade smart.
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QuantJourney Team
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