Quantitative Analyst

Q1: What industry are you in?
A1: I’m in trading/investment as a Quantitative Analyst in a hedge fund.

Q2: Can you tell us about your personal work background and career path?
A2: My career journey has been focused on quantitative analysis and data-driven roles. I hold a Bachelor's degree in Finance and Information Systems and a Master's degree in Financial Engineering. I began my career as a Data Analyst, where I honed my skills in data processing and visualization, and later transitioned into a Quantitative Analyst role, specializing in trading strategies and blockchain research. I have participated in various projects and competitions, including the Crypto Portfolio Challenge and LSEG-CUHK Trading Competition, showcasing my expertise in machine learning and financial modeling, which reflects my commitment to continuous growth in finance, data science, and technology.

Q3: What are the responsibilities of your current role, and what do you enjoy about it?
A3: In my current role as a Quantitative Analyst at a hedge fund, my responsibilities include conducting research on trading strategies, developing machine learning models, optimizing strategies through backtesting, exploring cryptocurrency projects, and building proprietary trading systems. I am also involved in workflow automation tasks such as data conversion and verification. What I enjoy most about this role is the opportunity to delve deep into quantitative finance, apply cutting-edge technologies to solve complex problems requiring you to think out of the box, and continuously learn and innovate in the dynamic field of blockchain and cryptocurrency.

Q4: Could you share a memorable professional experience?
A4: One of my most memorable professional experiences occurred shortly after I joined my current company. Drawing on my previous studies and project experience, I proposed a new approach to market data aggregation by introducing different bar types. Additionally, I developed a new trading strategy based on one of these specific bar types. The backtesting results of this strategy were outstanding, with an annualized return exceeding 130%. I was thrilled with the success of creating my first profitable trading strategy for the company, which was highly appreciated by my supervisors.

Data aggregation: combining trade data to analyze market trends and make informed decisions. For example, the price info of trades can be aggregated into open, high, low and close in every 5 mins interval.

Bar types: different ways of the trade data aggregation

Q5: What personality traits are well-suited for this profession?

A5: In the realm of quantitative analysis, data processing, and financial modeling, several key personality traits are beneficial.

• Attention to Detail: Ensures accuracy in data analysis and model building.

• Strong Analytical Skills: Aids in interpreting complex data and deriving meaningful insights.

• Problem-Solving Abilities: Essential for tackling intricate financial challenges.

• Adaptability: Valuable in the fast-paced and evolving financial industry.

• Effective Communication Skills: Important for presenting findings and collaborating with team members.

• Passion for Continuous Learning: Vital for staying updated on industry trends and technological advancements.

Q6: Are there any considerations or limitations in this profession?
A6: One consideration is the need for continuous learning and upskilling due to the rapidly evolving nature of technology and financial markets. Keeping up with advancements in machine learning, data analytics, and financial instruments is crucial. Additionally, the profession may involve long hours of data analysis and model building, requiring a high level of focus.

Q7: How can someone enter this profession, and what are the promotion opportunities?
A7: Entering the profession of quantitative analysis and financial modeling typically requires an educational background in fields like finance, mathematics, or computer science. Pursuing relevant courses, certifications, and internships can provide valuable experience.

Promotion opportunities in this field often depend on gaining expertise in quantitative techniques, demonstrating proficiency in data analysis and modeling, and showing a track record of successful projects. Advancement may involve taking on more complex projects, leading teams, and specializing in specific areas such as algorithmic trading or risk management. Continuous learning, networking, and staying updated with industry trends are key to unlocking promotion opportunities in quantitative analysis.

Some work-related photos below

I have traveled to Dubai at the beginning of 2024 for a business trip

Sample of the P&L Plot to Be Produced and Analyzed in Our Research

By Ko Wai Mei,Erica, a Quantitative Analyst and Team Head in a hedge fund

Top thumbnail designed by Freepik