Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth.
JOB RESPONSIBILITIES
The internal alpha capture (IAC) team is focused on developing and implementing scalable long/short equity investment strategies that leverage insights from discretionary portfolio managers and analysts, using sophisticated risk management, portfolio construction and execution techniques.
This is an opportunity for students and researchers in quantitative finance, behavioral finance, and statistics to apply these techniques to solve niche practical investment challenges specific to a platform of equity portfolio managers. Specific responsibilities will include:
End-to-end quantitative research project management including data exploration, cleaning and management, research hypothesis testing based on economic rationale, statistical/regression modeling, realistic simulation analysis, and presentation of results to the broader group.
DESIRABLE CANDIDATES
Undergraduate, Masters, or PhD candidates or higher in finance, computer science, mathematics, or other quantitative discipline
Strong analytical and quantitative skills, particularly related to quantitative equity investing
Sound economic intuition when it comes to validating investment hypotheses
We are looking for an experienced Macro Quant Researcher to join our team in Taipei.
Responsibilities
Develop macro-focused systematic trading strategies in liquid secondary markets.
Conduct research to identify data-driven signals and market inefficiencies.
Collaborate with team members on research and development initiatives.
Requirements
B.S., M.S., or Ph.D. degree in economics, finance, computer science, physics, or other quantitative discipline.
2+ years of experience in quantitative research or systematic trading at a bank, hedge fund, or asset manager.
Experience with systematic trading strategies for any secondary market product (e.g., Taiwan index futures, BTC, etc.) using tools beyond Excel or MultiCharts.
Proficiency in Python or C++ and familiarity with database query languages (SQL or NoSQL).
Demonstrable ability to conduct independent research utilizing large datasets.
Detail-oriented, willingness to take ownership of his/her work, and ability to work both independently and within a small team.
Quantitative Researchers are responsible for independently conducting quantitative financial research with a focus on statistical and predictive models.
About Cubist
Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.
Role
Quantitative Researchers are responsible for independently conducting quantitative financial research with a focus on statistical and predictive models. Successful researchers manage all aspects of the research process including methodology selection, data collection and analysis, testing, prototyping, backtesting, and performance monitoring.
Desirable Candidates
M.S., Ph.D., or Ph.D. candidates in finance, computer science, mathematics, physics, or other quantitative discipline.
Programming in any of the following: C++, C#, Java, or Python.
Strong analytical and quantitative skills.
Keen interest in quantitative research and metrics driven decision making.
Demonstrated ability to conduct independent research utilizing large data sets.
Detail-oriented.
Passion for spotting trends in data.
Willingness to take ownership of his/her work, working both independently and within a small team.
Ability to work under pressure.
Prior experience developing, researching, or implementing quantitative models for equities is preferred, but not required. We will provide training for new researchers without finance backgrounds.