Wall Street and the New Data Paradigm at PAW Financial, Oct 29 – Nov 2

Trading is already mainly automated. The next wave is about deploying predictive models that can connect the dots from different alternative data sources to provide an edge to the decision-making process for investors.

Predictive Analytics World for Financial Services - How Machine Learning Delivers Value to Hedge Funds - Wall Street Interview
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Interview with Predictive Analytics World Speaker

Anasse Bari, University Professor of Computer Science

In anticipation of his upcoming conference presentation, Wall Street and the New Data Paradigm at Predictive Analytics World for Financial in New York, Oct 29-Nov 2, 2017, PAW Founder Eric Siegel asked Anasse Bari, Clinical Assistant Professor of Computer Science at New York University, a few questions about his work in predictive analytics.

Professor Anasse Bari of New York University, formerly with the World Bank, is steadily becoming the go-to advisor for Wall Street. Although an outsider, he is providing data-driven insights that can help Wall Street hedge funds and other institutions make sound investment decisions.

Q: Harvard Business Review proclaimed that data scientist is the Sexiest Job of the 21st Century. In your role at New York University, how do you prepare your students to become data scientists?

A: In the graduate predictive analytics course I teach, my aim is to equip the next generation of data scientists for a successful profession in data analytics by teaching them the algorithms and tools they need to discover hidden similarities in data, effectively mine decisions’ rules, and ultimately, predict the outcomes of specific events. Read the full answer here.

Q: In your research work with predictive analytics in finance, what behavior or outcome do your models predict?

A: Access to information has always been the sine qua non to being successful on Wall Street. Investors base their decisions on traditional data sources, such as quarterly earnings reports, financial statement filings to the U.S. Securities and Exchange Commission (SEC), and sometimes the so-called “expert networks.”

My research on predictive analytics in finance involves developing an evidence-based decision support framework to model financial markets. The framework mines data sources to generate an array of hypotheses and their associated evidence. In one part of our study, we build models that can predict earnings and post-earnings of stock-price movements by probing the wisdom of crowds using alternative data sources. Read the full answer here.

Q: How does predictive analytics deliver value to hedge funds and Wall Street firms? What is one specific way in which it can actively drive decisions or operations?

A: PA is already reshaping the financial landscape. Trading for the most part has become automated, and portfolios can be automatically generated. The next wave is about deploying predictive models that can connect the dots from different alternative data sources to provide an edge to the decision-making process for investors. Shipping data, for instance, has been used to forecast Apple iPhone sales. Since most Apple products are produced in China, it was discovered that there is a correlation and causality between Apple shipment numbers and iPhone sales. Read the full answer here.

Q: What is the main take-away from your research?

A: Extracted insights from alternative data sources can provide a competitive imperative for investment strategies in the short and long term. There is a consistent predictive correlation between opinion mining scores based on the wisdom of crowds as seen in news articles, Twitter and other data sources, and the movements of financial markets. Read the full answer here.

See Anasse Bari's presentation: Wall Street and the New Data Paradigm at Preditctive Analytics World for Financial in New York, October 29 - November 2.

What else will you see at Predictive Analytics World for Financial?

View the full agenda, surrounded by 7 Workshops and register today.

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PAW Financial is co-located with PAW Business and PAW Healthcare. Cross Registration options are available.

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