As a Quantitative Researcher specializing in High Frequency Trading (HFT) in the futures markets, your primary responsibility will be to develop and implement sophisticated trading strategies using quantitative models and advanced statistical techniques. You will work closely with a team of traders, developers, and researchers to identify profitable opportunities and optimize trading performance in fast-paced, high-volume environments.
Key Responsibilities:
- Research and Development: Conduct in-depth quantitative research to identify alpha signals and develop predictive models for high frequency trading strategies in futures or equities markets.
- Data Analysis: Analyze large datasets to uncover patterns, correlations, and anomalies that can be exploited for trading opportunities.
- Model Development: Design, implement, and backtest trading algorithms using advanced mathematical and statistical techniques, machine learning, and optimization methods.
- Strategy Optimization: Continuously refine and optimize trading strategies to maximize profitability while managing risk and minimizing transaction costs.
- Market Monitoring: Monitor real-time market conditions and performance metrics to identify and react to changing market dynamics swiftly.
- Collaboration: Work closely with traders, developers, and other stakeholders to translate research findings into actionable trading strategies and contribute to the overall success of the trading desk.
- Documentation and Reporting: Document research findings, methodologies, and performance metrics, and prepare reports for internal stakeholders and regulatory compliance.
- Stay Current: Keep abreast of industry trends, market developments, and emerging technologies in quantitative finance and high frequency trading.
Qualifications:
- Advanced degree (Ph.D. or Master's) in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, Finance, or related disciplines.
- Strong quantitative skills and proficiency in programming languages such as Python, R, MATLAB, or C++ for data analysis, modeling, and algorithm development.
- Deep understanding of financial markets, trading dynamics, and market microstructure, with specific expertise in futures.
- Experience with high frequency trading strategies, market making, order execution, and algorithmic trading systems.
- Knowledge of statistical techniques, time series analysis, machine learning, and optimization methods applied to financial data.
- Excellent problem-solving abilities, attention to detail, and ability to thrive in a fast-paced, dynamic environment.
- Strong communication and collaboration skills, with the ability to work effectively in a team-oriented setting.
- Prior experience in quantitative research or trading roles within a financial institution, hedge fund, proprietary trading firm, or similar environment is highly desirable.
