Building a Trading Bot

Introduction

• Discussing liquidations in hand trading.
• Showing how to build a trading bot step by step.
• Importance of not diving directly into bot development without proper research.

Liquidation Statistics

• Big liquidations in hand traders' positions noted: 812k, 378k, 1 million, etc.
• Stressed that these are emotional trades leading to liquidations.

Steps to Build a Trading Bot

1. Research

   • Use resources like Google Scholar, YouTube, and trading forums.
   • Identify potential trading strategies.

2. Back Test

   • Code in Python to test strategies on past data.
   • Note: Past performance is not guaranteed for future results but helps in improving the likelihood of success.
   • Importance of back-testing highlighted through various examples.

3. Implement

   • Build out the trading bot with tested strategies.
   • Use risk management strategies, stop losses, and entry techniques.

Market Regimes Discussed

• Mentioned Jim Simon's eight market regimes:
  • Bull market
  • Bear market
  • Range-bound market
  • High volatility market
  • Low volatility market
  • Economic boom
  • Economic recession
  • Crisis market

Example of Breakout Trading Strategy

• Build breakout bots for upward market trends.
• Strategies included are:
  • Trend trading
  • Momentum trading
  • Breakout strategies with entry on significant price movements and volume confirmation.

Tips for Effective Breakout Trading Systems

• Multi-Timeframe Analysis: Use higher timeframes for significant resistance levels.
• Volume Confirmation: Confirm breakouts are backed by increased volume.
• Risk Management: Ensure position sizing aligns with market conditions.
• Optimize: Adjust for high probability trades.

Tools and Conducting Research

• Emphasized the use of tools and keeping meticulous records.
• Suggested keeping a notion file for tracking strategies, results, and improvements.

Liquidation and Trading Analysis

• On-screen analytics of current market trades, prices, and liquidations.
• Discussed the psychological aspect of trading versus algorithmic trading.

Resources and Community Support

• Mentioned the Boot Camp for deep dives into algorithmic trading processes.
• Shared knowledge on how to program in Python specific to trading bots.
• Included discussion on community and peer support among traders.

Final Thoughts

• Encouraged participants to stay vigilant in their trading and continue educating themselves.
• "Trade with knowledge, not emotion".

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Practical Applications

• The bot built will execute trades with programmed parameters including stop losses, and entries based on researched strategies.
• Links to resources may be provided in future videos/scripts.