Ravenpack Research Symposium: Sep 19

Complimentary but sign up soon as seating is limited!  Official event site: https://www.ravenpack.com/event/5th-annual-research-symposium-big-data-machine-learning/

5th Annual RavenPack Research Symposium: The Big Data & Machine Learning Revolution

An excellent lineup of financial practitioners and academics will present research and insights on these hot topics in fintech.

The Big Data & Machine Learning Revolution

RavenPack’s prestigious annual event has experienced growing interest, with attendance last year exceeding 200 buy-side professionals. Word on the street is RavenPack’s research symposium is a “must attend event” for quantitative investors and financial professionals that are serious about Big Data.

Join us at 10 on the Park, Time Warner Center’s renowned location in the heart of Midtown Manhattan, and hear an excellent set of senior finance professionals share their latest research and experience with big data and machine learning.

Register to reserve your place and be informed on updates to the agenda. The event is free to attend for financial professionals.

When:
Tuesday Sept 19
9:00 am – 5:00 pm EDT

Where
10 On the Park at Time Warner Center
60 Columbus Circle, 10th Floor, NYC

A cocktail reception will be held at the conference venue from 5:00 pm.

Speakers – last updated June 26th

  • Marko Kolanovic, Global Head of Quantitative and Derivatives Strategy, J.P. Morgan
  • Ichihan Tai, Portfolio Manager / Head of Data Science, Tokio Marine Asset Management
  • Hedi Benamar, Economist, Board of Governors of the Federal Reserve System
  • Rajesh Tembarai Krishnamachari, Vice President, Quantitative and Derivatives Strategy, J.P. Morgan
  • Peter Hafez, Chief Data Scientist, RavenPack

Register here: https://www.ravenpack.com/event/5th-annual-research-symposium-big-data-machine-learning/

Speaker Biographies

Marko Kolanovic, PhD
Global Head of Quantitative and Derivatives Strategy, J.P. Morgan

Marko KolanovicMarko Kolanovic is the Global Head of Macro Quantitative and Derivatives Strategy team at J.P. Morgan. His team is responsible for developing macro, derivatives and quantitative equity strategies, as well as systematic cross-asset portfolios for clients. His team currently holds 5 top rankings in the Institutional Investor surveys in the US, Asia and Europe, and Marko individually ranks #1 in the category of Americas Equity Derivatives. Prior to joining J.P. Morgan, Dr. Kolanovic was Global Head of Derivatives and Quantitative Equity Strategies at Bear Stearns and a derivatives research analyst at Merrill Lynch. His trading methods have been implemented by major hedge funds and investment offices around the world. Dr. Kolanovic’ s work is frequently quoted in financial press, and for his timely and accurate short term forecasts of stock market returns, the media dubbed him ‘The Man who moves Markets’ (CNBC) and ‘Gandalf’ (Bloomberg). Marko graduated from New York University with a PhD in theoretical high-energy physics. He has developed a number of scientific theories/models, and has authored top-cited research publications. He currently resides in New York City.

Ichihan Tai
Portfolio Manager / Head of Data Science, Tokio Marine Asset Management (USA) Ltd.

Ichihan TaiIchihan is responsible for systematic event-driven strategies at Tokio Marine Asset Management (USA) Ltd., an asset management subsidiary of Japan’s oldest and largest non-life insurance company, Tokio Marine Holdings. He manages the entire data driven investment processes from vendor selection, data engineering, alpha research, trade execution, to pitch book development. Prior to joining Tokio Marine, he was responsible for leveraging data science to accelerate large-scale organizational transformations at Goldman Sachs. Ichihan holds a B.S. and a M.S. in Engineering from the University of Michigan and received a doctoral training at the George Washington University.

Hedi Benamar
Economist – Global Capital Markets, Board of Governors of the Federal Reserve System

Hedi Benamar is an economist at the Board of Governors of the Federal Reserve System. His research interests focus on behavioral finance and market microstructure. He holds a PhD in Finance from HEC Paris (France) and a MSc in Applied Mathematics from the University Paris Dauphine (France).

Rajesh T. Krishnamachari, PhD
Vice President, Quantitative and Derivatives Strategy, J.P. Morgan

Rajesh T KrishnamachariRajesh Tembarai Krishnamachari is a researcher on systematic cross-asset (Equity/FX/Commodity/Rates; Delta-one and Derivative-based) strategies with the Macro Quantitative and Derivatives Strategy team. Before joining the team, he was a quant with the Equity Derivatives QR at J.P. Morgan, where his research spanned both high-frequency algorithmic trading as well as equity quantitative strategy development. Dr. Krishnamachari ‘s extensive and highly-cited research record includes 1 book and 7 papers on signal processing & machine learning, 3 papers on mathematics, and 13 papers on social sciences & economics. Dr. Krishnamachari was educated at New York University, University of Colorado and Indian Institute of Technology, Madras.

Peter Hafez
Chief Data Scientist, RavenPack

Peter HafezPeter Hafez is the head of data science at RavenPack, the leading provider of real-time news and social media analysis. Since joining RavenPack in 2008, he’s been a pioneer in the field of applied news analytics bringing alternative data insights to the world’s top banks and hedge funds. Peter has more than 15 years of experience in quantitative finance with companies such as Standard & Poor’s, Credit Suisse First Boston, and Saxo Bank. He holds a Master’s degree in Quantitative Finance from Sir John Cass Business School along with an undergraduate degree in Economics from Copenhagen University. Peter is a recognized speaker at quant finance conferences on alternative data and AI, and has given lectures at some of the world’s top academic institutions including London Business School, Courant Institute of Mathematics at NYU, and Imperial College London.