Financial Engineering Practitioners Seminar: Rahel Jhirad
Date: October 19, 2015 from 6:00 pm to 7:30 pm EDT
Location: Davis Auditorium, CEPSR Building
Contact: For further information regarding this event, please contact IEOR Department by sending email to .
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Title: An Economist's Perspective on Finance, Big Data and Digital Media

Abstract: In many ways the success of financial markets was due to the alignment of reliable data,compute power, financial engineering and, strong foundations in sound economic and financial theory. I focus on the value that economic frameworks provide in giving context and insight within finance.  I will present an economic model of bid ask spreads and volatility and contrast it with a financial engineering approach. 

We are witnessing the burgeoning of Big Data and applications to IoT, Consumer Behavior, Security. We now have access to petabytes of data, unprecedented ways of generating compute power by parallelization, and now commoditized machine learning algorithms. However, the cautionary message is: applying all these three resources without domain knowledge is problematic. What does economics bring to the table? What frameworks might prove useful in thinking about consumer behavior?  I will present a case study for modeling churn within a large financial services company.

Lastly I will discuss the problems and challenges we work on at Hearst.

Bio: Rahel Jhirad is Director of Data Science at Hearst where she works with content, audience, ads and digital media. She has worked in the space of Big Data since 2010 and consulted with Fortune 100 companies leveraging machine learning, domain expertise, modeling, time series and econometrics tools to solve and address business challenges. She is passionate about big data and cross-disciplinary literacy and started a popular Meetup called Economics and Big Data. Rahel has extensive experience working in the financial sector at Mocatta Metals, Morgan Stanley, Salomon Brothers, and TD as a quant, a trader and risk manager. Rahel holds a PhD in Economics from Princeton, and MS in Mathematics from NYU.