Quantitative Research

As a Quantitative Researcher at PHNX Securities, you will play a crucial role in researching, designing, and validating data-driven trading strategies in equity markets. Your responsibilities will include handling the full trading cycle, from ideation and model development to back testing, portfolio construction, and live monitoring by transforming market insights into executable trading systems. Key Responsibilities: - Research, develop, and implement statistical models and algorithms for systematic equity trading. - Evaluate strategy performance, perform back testing, and optimize signal pipelines. - Work with key stakeholders to productionize new strategies and trading ideas. - Apply machine learning techniques such as auto-regression, auto-correlation, and Principal Component Analysis to enhance predictive power. - Explore trading ideas by analyzing market data, market microstructure, and alternate data for patterns. - Build and maintain Python-based back testing frameworks for price, volume, and fundamental data. - Conduct portfolio-level simulations using mean-variance optimization, risk parity, and volatility targeting. - Monitor live performance, analyze deviations from back-tested expectations, and recalibrate models. - Automate recurring research tasks including data ingestion, signal generation, and performance tracking. Qualifications & Experience: - A Bachelors, Masters or PhD degree in Mathematics, Statistics, Computer Science, or equivalent STEM degree. - 12 years of experience in quantitative research, algorithmic trading, quantitative developer. - Strong proficiency in Python, R, Java, and C++. - Solid understanding of statistical modeling, time-series forecasting, and machine learning. - Hands-on experience with financial data APIs (Yahoo Finance, NSE data, or broker APIs). - Proficiency in SQL or similar database tools. - Solid data-mining and analysis skills, including experience dealing with a large amount of data/tick data. - Solid understanding of derivatives markets, options pricing, and volatility dynamics. As a Quantitative Researcher at PHNX Securities, you will play a crucial role in researching, designing, and validating data-driven trading strategies in equity markets. Your responsibilities will include handling the full trading cycle, from ideation and model development to back testing, portfolio construction, and live monitoring by transforming market insights into executable trading systems. Key Responsibilities: - Research, develop, and implement statistical models and algorithms for systematic equity trading. - Evaluate strategy performance, perform back testing, and optimize signal pipelines. - Work with key stakeholders to productionize new strategies and trading ideas. - Apply machine learning techniques such as auto-regression, auto-correlation, and Principal Component Analysis to enhance predictive power. - Explore trading ideas by analyzing market data, market microstructure, and alternate data for patterns. - Build and maintain Python-based back testing frameworks for price, volume, and fundamental data. - Conduct portfolio-level simulations using mean-variance optimization, risk parity, and volatility targeting. - Monitor live performance, analyze deviations from back-tested expectations, and recalibrate models. - Automate recurring research tasks including data ingestion, signal generation, and performance tracking. Qualifications & Experience: - A Bachelors, Masters or PhD degree in Mathematics, Statistics, Computer Science, or equivalent STEM degree. - 12 years of experience in quantitative research, algorithmic trading, quantitative developer. - Strong proficiency in Python, R, Java, and C++. - Solid understanding of statistical modeling, time-series forecasting, and machine learning. - Hands-on experience with financial data APIs (Yahoo Finance, NSE data, or broker APIs). - Proficiency in SQL or similar database tools. - Solid data-mining and analysis skills, including experience dealing with a large amount of data/tick data. - Solid understanding of derivatives markets, options pricing, and volatility dynamics.