Why Big Data Finance?

Big Data Finance Conference, now in its 7th consecutive year, is the only FOR QUANTS, BY QUANTS event in the space. 

Every year, we build the conference exactly how we want an ideal conference to be. 

We cover the latest research, trends and data, all of which are directly and immediately applicable in the Big Data Finance space.


SCHEDULE (subject to change)

Thursday, May 9, 2019
Big Data Advances in Investment Management

9:00 AM – 12:00 PM
Big Data Application Workshop (Details TBA)
12:00 PM – 1:00 PM
Main Conference Registration
1:00 PM – 1:15 PM 
Remarks, Victoria Averbukh, Director, Cornell Financial Engineering 
1:15 PM – 1:30 PM
Remarks, Prof. Marco Avellaneda, NYU Courant
1:30 PM – 2:15 PM
Keynote: Dr. Ali Nazari, CIO and Founder, Data Capital Management
“Sourcing Returns from Data: Trends, Challenges and Applications”
2:15 PM – 3:00 PM
Panel, Data Application Trends in Investment Management
– Gurraj Sandha, Global Head of Risk for State Street Verus, AI Investments
– Ali Nazari, CIO and Founder, Data Capital Management
– John Paul “JP” Milciunas, Venyture Partner, Bionic
– Moderator, TBA
3:00 PM – 3:15 PM
Coffee Break
3:15 PM – 4:00 PM
Rajesh Krishnamachari, Head of Data Science, Bank of America Merrill Lynch
“Advances in Big Data Applications to Investment Management: Latest Techniques”
4:00 – 4:45 PM
Keynote, TBA
4:45 PM – 5:00 PM
Dr. Victoria Averbukh, Closing Remarks
5:00 PM – 6:00 PM
Networking Reception

Friday, May 10, 2019
Infrastructure, Machine Learning, Blockchain

8:30 AM – 9:00 AM
9:00 AM – 9:15 AM
Opening Remarks, Dr. Victoria Averbukh
9:15 AM – 10:00 AM
Wilfred Daye, Head of Financial Markets at OK Coin
“Blockchain revival: What’s in store”
10:00 AM – 10:45 AM
Blockchain Panel: Opportunities, Challenges, and Techniques for Blockchain as a Market Currency”
  • Wilfred Daye, Head of Financial Markets at OK Coin
  • Vlad Mamut, CEO & Co-founder, Apoji, Inc
  • TBA
  • Moderator, TBA
10:45 AM – 11:00 AM
Coffee Break
11:00 AM – 12:00 PM
Infrastructure Panel: Requirements, Challenges, Tools and Practical Issues in Big Data Implementation
  • TBA
  • Moderator TBA
12:00 PM – 1:00 PM
1:00 PM – 1:45 PM
Irene Aldridge, Managing Director, Research, AbleMarkets, Adjunct Professor, CFEM, Cornell Tech
Big Data Techniques in Finance: Beyond Econometrics and Data Mining
Big Data is often considered an extension of Econometrics. This talk gives a survey of now-mainstream Big Data techniques just gaining the traction in Finance that extend far beyond traditional data analysis. The Big Data techniques discussed do away with rigidity and limitations of Econometrics, provide in-depth inferences often without the need for hypotheses, and lay foundation for the true artificial intelligence models poised to revolutionize the field of Finance in the next 5-10 years.
1:45 PM – 2:30 PM
Abena Owusu, Rensselaer Polytechnic Institute
“Extracting Risk Using Natural Language Processing”
We use unsupervised machine learning techniques to
identify and define the risk culture of 840 bank holding companies
(BHCs) using their SEC 10-K filings. We develop a two-dimensional
dictionary, using risk culture frameworks and Loughran and McDonald’s
(2014) sentiment dictionary, to extract paragraph level features
reflecting sentiments for risk culture topics in the 10-K reports.
Our principal component analysis results show that the uncertainty,
litigious and constraining risk culture features extracted from the
text documents are important in identifying the risk culture of
banks. Using a two-stage clustering approach, we cluster the 10-K
reports into three distinct risk culture clusters: good, fair and
poor. We validate our cluster analysis results against quantitative
bank risk measures, governance and performance indicators and find
that banks within our good risk culture cluster have higher Z-Score,
Tier 1 capital, profitability and cash ratios, and a lower standard
deviation of ROA, relative to banks in the poor risk culture cluster.
Our clustering results also show that the size of a bank and the
financial time period for which the evaluation is made can become
important determinants for risk culture. 
2:30 PM – 2:45 PM
Coffee Break
2:45 PM – 3:30 PM
Qiang Song, Data Scientist, Thasos Group
“Deploying Location Data”
3:30 PM – 4:15 PM
James Baker, Suite LLC, “News and volatility”
An investigation of how diversity of news article sentiment can prefigure changes in market volatility. This will use a variety of natural language processing techniques to determine a measure of news sentiment diversity for a stock, then use that measure as an input to a neural network classifier to predict market changes.
4:15 PM – 5:00 PM
Hyunyoung Choi, S&P Global
Credit Risk Analytics/ Building business case for Alternative data
Alternative data in finance has become an important input in the investment process. Alternative data can be compiled from various sources such as financial transactions, sensors, mobile devices, satellites, public records, and the internet and it is compared with the traditional data sources such as investor presentations, SEC filings, and press releases. The challenge we face in developing the alternative data product is to educate the market so that they understand the value of new data. Internet search data offers a window into the information-gathering activities of many people. Such data has proven itself a useful resource in a number of domains, as researchers have established links between online search data and reports of flu infections, the popularity of films, games and music on their release, unemployment rates, tourist traffic, stock returns and trading volumes in U.S. stock markets. We propose the Kensho Finance Stress Indicator (KFSI) that measures consumer’s financial stress through their search behavior. KFSI is a strong leading indicator of financial stress in addition to traditional financial data. In order to show the use case with alternative data, we built Credit Risk Analytics leveraging KFSI. Credit Risk Analytics includes KFSI, net charge off forecast from a predictive model forecasting the net charge offs and a solution to comply with CECL requirement.

5:00 PM – 5:15 PM
Closing Remarks

Learn the latest techniques to beat competition

Hear from top academics, data scientists and quants about the latest theory and its applications to Finance. 

Explore best practices and interact with the top practitioners in the industry. Learn hands-on techniques, strategies and trends from the frontlines.

Meet industry colleagues

Already registered attendees of Big Data Finance 2019 include representatives from such major investment managers as Lord, Abbett, Inc., top academics from Cornell University and NYU Courant, and many others. 

Last year’s Big Data Finance conference was attended by senior executives from industry stalwarts such as Two Sigma, Point 72, Goldman Sachs, Lord Abbett, Vanguard, WorldQuant, Millennium Partners, Eaton Vance, Alliance Bernstein and many others.

Major asset management experts join BDF year after year

Attendees' top reasons to join BDF (survey)
Learn Latest Techniques
Latest Techniques 86%
Learn Implementation Strategies
Implementation Strategies 78%
Learn Industry Trends
Industry Trends 100%
Build Industry Networks
Networking 92%

Big Data Finance = The Original and Best Financial Data Science Conference

2 full days of ideas, results and networking, 7 continuous years of dedication, exploration and research


Learn the latest Big Data break-throughs, implementation approaches and techniques


Understand the empirical results of theories and current best practices in the industry


Enjoy camaraderie of industry colleagues and make useful connections for business and career development


Every dollar you contribute goes to Big Data research in Finance

What past participants say about Big Data Finance

Multi-billion dollar portfolio manager

Mutual Fund

"Great content and interesting people"


Major Hedge Fund

"Trending topics and to-the-point discussions. Very relevant to my work."

Quantitative Researcher

Global Investment Bank

"The conference gives me lots of great ideas."

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