Quantitative Trading | Generated by AI

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Transitioning from a full-stack development background with 10 years of experience to quantitative trading is an exciting move! Your programming skills in Java, Spring, and app development provide a solid foundation, but quantitative trading requires a blend of finance, mathematics, statistics, and advanced programming tailored to algorithmic strategies. Since you’re new to this domain and aspire to reach the level of firms like D.E. Shaw, Bridgewater, or legendary investors like George Soros and Ray Dalio, I’ll outline a roadmap to get you started and progressively build expertise.

Step 1: Understand the Basics of Quantitative Trading

Quantitative trading involves using mathematical models, statistical techniques, and algorithms to identify and execute trading opportunities. It’s different from traditional discretionary trading because it relies heavily on data analysis and automation.

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Step 2: Build Core Quantitative Skills

Quantitative trading relies heavily on mathematics and statistics, which you’ll need to master.

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Step 3: Dive into Algorithmic Trading

Now, focus on designing and implementing trading algorithms.

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Step 4: Incorporate GPU and Deep Learning

Top firms like D.E. Shaw and Bridgewater use advanced tech like GPUs and deep learning for predictive modeling and optimization.

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Step 5: Emulate Top Firms and Investors

To reach the level of D.E. Shaw, Bridgewater, Soros, or Dalio, you’ll need a mix of technical prowess, market intuition, and strategic thinking.

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Roadmap Summary

  1. Months 1-3: Learn finance basics, Python, and simple strategies. Backtest with TigerOpen.
  2. Months 4-6: Master stats, time-series analysis, and algorithmic trading. Build 2-3 strategies.
  3. Months 7-12: Dive into ML/DL, use GPUs, and refine strategies with real-time data.
  4. Year 2: Focus on latency (C++ if HFT interests you), portfolio management, and macro insights.
  5. Year 3+: Develop a unique edge (e.g., novel data source, ML model) and test with live capital.

Practical Tips

With your programming experience, you’re already ahead of many beginners. Focus on bridging the finance and math gaps, and iteratively build complexity. Reaching D.E. Shaw or Bridgewater’s level takes years, but consistent learning and experimentation will get you there. What’s your next step—deepening Python skills or exploring a specific strategy?


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