Patrick Edlinger

Patrick Edlinger

@ UBS

About Patrick Edlinger

Patrick Edlinger is a financial professional with extensive experience in trading and risk management. He currently works at UBS, focusing on hedging strategies and optimization techniques to enhance financial portfolios.

Work at UBS

Patrick Edlinger has been employed at UBS since 2014, where he has accumulated ten years of experience. His role involves a strong focus on hedging strategies aimed at effectively managing risk within trading portfolios. This position allows him to apply his expertise in optimization techniques, which are essential for enhancing the risk profile of financial portfolios.

Previous Experience at Barclays Investment Bank

Prior to his tenure at UBS, Patrick Edlinger worked at Barclays Investment Bank as an IPV analyst from 2013 to 2014. During this one-year period, he contributed to the analysis and validation of pricing models, which are critical for ensuring the accuracy of financial instruments.

Previous Experience at Bank of America

Patrick Edlinger also has experience at Bank of America, where he worked in Structured Credit Trading from 2010 to 2012. Over the course of two years, he was involved in trading activities related to structured credit products, gaining valuable insights into the complexities of credit markets.

Education and Expertise

Patrick Edlinger studied at CentraleSupélec from 2005 to 2008, where he developed a strong foundation in quantitative analysis and financial engineering. His education has equipped him with the necessary skills to excel in the financial sector, particularly in areas such as database administration and modeling.

Technical Skills and Proficiencies

Patrick Edlinger possesses advanced skills in Microsoft Excel and SQL, which he utilizes for data analysis and financial modeling. He is proficient in multiple programming languages and tools, including C++, Python, MATLAB, and VBA. These technical skills support his work in quantitative analysis and enhance his ability to manage and structure data effectively.

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