Quant Finance Salaries and Compensation in Asia in 2024

In today's competitive job market, having a clear understanding of compensation expectations can help you make informed decisions. This article shares the typical skills needed and latest quant finance salary and compensation data in Asia from the Guide, offering you a comprehensive overview of what you can expect across six career paths.

Quant Finance Salaries and Compensation in Asia

Portfolio Management

Professionals working in Portfolio Management are responsible for asset allocation and portfolio construction. They initiate trades and monitor portfolios and their exposures carefully. Quants working in portfolio management need strong quantitative and mathematical modeling, coding, analytical thinking, and communication skills. They must possess an extensive knowledge of the various asset classes, the firm’s investment products, and products that are available in the broader financial market.

Risk Management

Quants working in risk management need strong quantitative and financial modeling skills, proficiency with programming, knowledge of various methods including “Value-at-Risk” (VaR and its variants), as well as statistical models and simulations to evaluate the risk exposure for an asset or across an entire portfolio of assets. They must have knowledge of stochastic calculus, Monte Carlo, PDEs, and other numerical techniques. They also need familiarity with financial markets, including the most recent regulatory developments. 

Quant Strategies and Research

Professionals working in quant strategies and research have a detailed knowledge of mathematical and statistical models. They also require knowledge of financial mathematics and stochastic calculus. They have good programming skills in Python or C++, and may have skills in R, MATLAB, or SAS as well. Knowledge of machine learning and natural language processing techniques is increasingly in demand.

Data Science and Machine Learning

Professionals working in data science and machine learning need to have a deep understanding of algorithms, as well as specific domains such as natural language processing or signal processing, to help identify and assess patterns in the data. They must possess strong quantitative analysis skills, a solid grasp of AI and machine learning techniques, and familiarity with programming languages commonly used in the field, with Python being particularly important.

Roles in this career path require significant knowledge of models and programming. These jobs tend to sit within the research area of an organization. Firms that are active in data science and machine learning include investment banks, asset managers, hedge funds, and technology companies that offer consulting services to the financial industry. There are also opportunities for quants in tech organizations that develop software products for the financial industry.

Technology

Quants in technology will have excellent coding skills in Python, C, C++, or C#, for example. They should also have a good understanding of computational mathematics, software engineering, and financial products. They tend to work on projects with several teams if they are in a large organization, so having domain expertise combined with good skills in collaboration and communication will be helpful.

Quant Trading

Quant traders must have deep knowledge of quantitative and statistical analysis, and strong programming skills in Python or C++, for example. They may have experience with machine learning techniques as well. Psychology is very important for quant traders and trading job candidates must demonstrate that they thrive in extremely competitive environments and can handle pressure well.