Most important skills for macro/RV/FI

For those wanting to build a great career in macro/RV/FI space, what would you rank as the most important skills to focus on? How are you thinking about allocating your focus across different technical/other areas?

I'm trying to get ahead and grow as much as possible, but really having a hard time prioritizing between areas such as:

  • Coding (and what kind of coding to focus on!)
  • Statistics
  • General mathematics (how much will this really help?)
  • Product knowledge
  • General market knowledge (for instance how much time to spend reading sell-side pieces)
  • Machine learning/AI (will this really move the needle?)
  • Economics

I suppose I'm really thinking about this from the perspective of what to spend my time on at work (for example whenever have downtime) and in my free time.

11 Comments
 

Based on the most helpful WSO content, here are the key skills and areas to focus on for building a successful career in the macro, relative value (RV), and fixed income (FI) space:

Key Skills and Areas to Focus On:

  1. Coding and Programming:

    • Languages: Python, R, Matlab.
    • Importance: Extensive programming experience is crucial as the industry has become more quantitative. It opens up more job opportunities.
  2. Statistics and Mathematics:

    • Statistics: Essential for forecasting and time series analysis.
    • Mathematics: Important for understanding derivative pricing, stochastic calculus, and other quantitative methods.
  3. Product Knowledge:

    • Fixed Income Products: Understanding rates, FX, commodities, and inflation.
    • Derivatives: Knowledge of options, futures, and other non-linear instruments.
  4. General Market Knowledge:

    • Macro Strategies: Familiarize yourself with carry, relative value, basis, trend following/momentum, policy, and "bread & butter" trades.
    • Technical Analysis: Understand positioning (in futures) and sentiment (street surveys), and option positioning.
  5. Economics:

    • Macro Understanding: Regularly commit time to independent macro analysis. A strong understanding of macroeconomic principles is essential.
  6. Machine Learning/AI:

    • Relevance: While not explicitly mentioned, having a grasp of machine learning and AI can be beneficial, especially in quantitative roles.

Prioritization:

  • Work Downtime:

    • Focus on coding and programming skills, as they are highly valued and can significantly enhance your job prospects.
    • Spend time on statistics and mathematics to strengthen your quantitative analysis capabilities.
  • Free Time:

    • Deepen your product knowledge and general market knowledge by reading sell-side pieces and other relevant materials.
    • Regularly analyze macroeconomic trends and strategies to stay updated.

By balancing your focus across these areas, you can build a robust skill set that will help you excel in the macro, RV, and FI space.

Sources: Q&A: Rates & Macro Research/Strategy - Career Path, Technical Topics, Education, etc., https://www.wallstreetoasis.com/forum/hedge-fund/developing-macro-understanding?customgpt=1, Q&A: Non-Target School to Portfolio Manager at a Top Hedge Fund – 6 Years Out of Undergrad, Global macro recruiting - a primer, Most Valuable Hard Skills?

I'm an AI bot trained on the most helpful WSO content across 17+ years.
 

Thanks for your help and substack again! May I ask that is it possible for a finance-major student to pursue a career at macro? I feel a deep lack of math and coding and really confused about how to self-study math or maybe have to transite into a phd program for math and code.

 

DonalDayUmTray & MacroJunkie thanks for this feedback. Pretty interesting you say this as many seem to emphasize the importance of programming/math/stats over the finance stuff like product and market knowledge. After few years in the game, does the answer of prioritizing market and product knowledge still apply?

What you're saying does resonate and aligns what I've been thinking as well. I do see the merits of the quanty stuff but it just feels like there is so much to learn on the actual markets side and even learning that part takes a lot of time and effort.

 
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