Garden Leave - Tips on How to Stay Sharp?

To make the most of your garden leave and set yourself up for success, here's a structured approach based on the most helpful WSO content:

1. Programming Skills

• Start with Python: Python is highly recommended for its popularity in finance, intuitive syntax, and extensive libraries for data analysis and trading. It's a great starting point for someone with no coding experience.
  • Resources: Look into beginner-friendly courses like Codecademy, Coursera (e.g., Python for Everybody), or Udemy.
  • Projects: Build something relevant to your interests, such as a simple back-test for a trading strategy. This will teach you more than unrelated projects like Sudoku solvers.
• SQL: Learn SQL for data manipulation and analysis. It's a critical skill for working with large datasets in finance.
  • Resources: Platforms like DataCamp or Khan Academy offer excellent SQL tutorials.

2. Mathematics and Statistics

• Linear Algebra and Probability: These are foundational for understanding quantitative finance and systematic trading.
  • Resources: Khan Academy and MIT OpenCourseWare are great for brushing up on linear algebra and probability basics.
• Statistics for Trading: Focus on applied statistics, which will help you analyze market data and build models.
  • Resources: Books like Natenberg's Option Volatility and Pricing can provide a practical introduction to statistical concepts in trading.

3. Market Knowledge

• Stay sharp on the markets you want to trade by:
  • Reading Daily: Follow financial news and market commentary to stay updated on macro trends.
  • Analyzing Data: Use your current knowledge of credit and structure to analyze how macro factors impact the assets you trade.
  • Books: Consider reading books on macro trading strategies to deepen your understanding.

4. Balancing Your Time

• Ideal Split:
  • 50% Technical Skills: Dedicate half your time to learning programming and math. Start with Python and linear algebra, then gradually move to more advanced topics.
  • 30% Market Analysis: Spend time analyzing the markets you want to trade, reading news, and understanding macro trends.
  • 20% Practical Application: Work on projects that combine your technical skills with market analysis, such as building a simple trading model or automating a data-scraping tool.

5. Mindset and Strategy

• Start Small: Focus on mastering the basics before moving to advanced topics. For example, learn Python syntax before diving into machine learning.
• Consistency Over Intensity: Dedicate a few hours daily rather than cramming. This will help you retain information better.
• Leverage Your Strengths: Use your micro-level credit analysis skills to bridge the gap to macro trading. For instance, analyze how macroeconomic factors influence structured credit markets.

By following this plan, you'll not only upskill yourself but also position yourself to hit the ground running when your team transitions to the new platform. Remember, the key is to stay consistent and focus on building a strong foundation.

Sources: Programming/Technical Skills for Finance: SQL and Python, Programming/Technical Skills for Finance: SQL and Python, I'm Trying to get into Prop-Trading From a Non-Target School, Advice I give to my incoming analysts, https://www.wallstreetoasis.com/forum/trading/move-to-tech-in-search-of-better-wlb?customgpt=1