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Post Date
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06/16/2010
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Title
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Quantitative Portfolio Manager
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City
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New York
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Recruiter
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Job Description
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Responsible for managing a significant portfolio of US equities, futures, and ETFs using quantitative statistics based arbitrage computer models based on extensive statistical analysis of historical data and leading insights on securities returns dynamics. Apply the models to manage a portfolio of stocks and derivatives within a set of optimally-determined risk parameters. Dynamically manage portfolio risk by evaluating historical and real-time strategy performance. Supervise a team of researchers and developers on a daily basis to design, research and manage sophisticated investment strategies by creating and engineering advanced quantitative financial computer modeling systems to aid in analysis and research of equity securities. Perform research to acquire historical and production data sources needed to build the investment models. Design and develop quantitative mathematical statistical algorithms to link the diverse data sets from various providers. Develop investment models that will make the buy and sell recommendations for the portfolios using advanced quantitative statistics and investment theory to design and program strategies that explicitly forecast risk, return, and trading costs in the developed equity markets. Use quantitative statistics based models to value securities. Conduct ongoing, cutting-edge quantitative research and analysis to enhance existing strategies and to expand into new markets. Develop aspects of successful statistical models, focusing on forecasting and optimization. Hedge delta/beta risk/exposures via dynamic hedging at both portfolio and name-by-name levels. Collaborate with quantitative analysts, programmers and traders of other products to develop and deploy new strategies.
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Requirements
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Utilize the following quantitative skills, tools and technologies in the performance of these duties: machine learning, non-linear regression and optimization, cointegration, and cluster analysis techniques as well as Python, S-plus/R, SAS and C++ to implement statistical arbitrage models. Minimum Requirements: Master’s Degree in Statistics, Mathematics, Physics or Computer Engineering plus 2 years as Director or Quantitative Trader using the following quantitative skills, tools and technologies: machine learning, non-linear regression
and optimization, cointegration, and cluster analysis techniques as well as Python, S-plus/R, SAS and C++ to implement statistical arbitrage models.
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Apply for this position
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