Generation AI: The New Data-Driven Investor

RavenPack Research Symposium - Generation AI: The New Data-Driven Investor

RavenPack’s events have become global, with attendance exceeding 250 buy-side professionals at the London Big Data and Machine Learning Revolution in April 2018. RavenPack Research Symposium returns to New York on September 12th. Industry buzz is that RavenPack’s Research Symposium is the “must attend event” for quantitative investors and financial professionals that are serious about Big Data.

Agenda

Expect a full day of thought provoking presentations and panel discussions focusing on the impact of Artificial Intelligence (AI) and Big Data in the modern investment process. Speakers will present their research and views on the latest alternative data sets, machine learning techniques, and big data technologies reshaping the way we invest and trade globally.

With content very much research-driven and examples of real world use cases of alternative data and AI in the investment process. See below the session titles and abstracts from our confirmed speakers .

Last Updated: September 4, 2018

9:30 am Registration Starts

Light breakfast served.

10:00 am Welcoming Remarks
Is Big Data a Big Opportunity - or a Big Problem?

Armando Gonzalez, CEO, RavenPack

Armando will discuss how the big data revolution is changing the way decisions are made in finance as we rely more on data and analysis, and less on intuition and experience, and why this is disrupting the very nature of human thinking.

10:15 am Keynote
The World of Alphas

Nitish Maini, General Manager, Virtual Research Center / Vice President, Portfolio Management, WorldQuant

In this presentation, Nitish will provide an overview of the quantitative research process and share how the use of AI, ML & data creates value in this process. He will also discuss how the space of alphas are defined in a quantitative world and what could be a systematic approach towards building a diversified quantitative portfolio.

10:50 am News Patterns Matter When Constructing Sentiment Trading Strategies

Peter Hafez, Chief Data Scientist, RavenPack

The Big Data revolution has enabled new ways of constructing orthogonal alpha signals around alternative data. In contrast with market data, most alternative data, and especially news, is available in an uninterrupted fashion, 24 hours a day, 7 days a week. In this presentation, Peter will showcase RavenPack’s latest research on how intraday news patterns dictate the construction and implementation of sentiment strategies across thousands of news sources. He will show how to detect these intraday news patterns and how to take advantage of them for profit when constructing trading strategies.

11:20 am Machine learning for Future Fundamentals Estimation

Dr. Ronnie Shah, Director and Head of U.S. Quantitative Research and Quantitative Investment Solutions, Deutsche Bank

We develop a new technique to estimate “fundamental acceleration” using a machine learning lasso technique to forecast fundamental values. Estimating future fundamentals helps resolve the lack of timeliness of past fundamental data when constructing value metrics. The dynamic nature of fundamental forecasting improves capital allocation across sources of expected return. As we show, adding fundamental acceleration to typically constructed value or “1/P” strategies improves risk-adjusted performance by 80%.

For compliance reason, slides and video are not available.

11:40 am Big Data and Machine Learning in Investing: Current Misconceptions and the Path Ahead

Rajesh T. Krishnamachari, Head of Data Science - Equities, Bank of America Merrill Lynch

The talk will clarify the difference in the role played by new data vis-a-vis the role played by new analysis techniques. We will also classify data science techniques based on their academic provenance. We argue for certain areas/regimes possessing the most and the least potential for application of big data analysis techniques.

12:00 pm Lunch & Learn

While lunch is being served as a buffet style, you can also join the below workshops.

Test Drive the New RavenPack Data Platform
Animated by Kevin Crosbie, Chief Product Officer, and Ash Sharma, Director of Text Analytics, RavenPack
Session 1: 12:20 pm - 12:40 pm
Session 2: 12:50 pm - 13:10 pm
Both sessions are identical and take place in Hub 1
Reproducible Finance with R.
Jonathan Regenstein, Director of Financial Services at RStudio, will introduce the R programming language and explore packages for analyzing and visualizing financial data.
12:40 pm - 13:10 pm in Hub 2

13:15 pm Panel: Big Data, Big Impact: How Data is Reshaping the Modern Investor

Moderator: Tim Harrington, CEO, BattleFin Group
Panelists:
- Matei Zatreanu, CEO / Founder, System2
- Milind Sharma, CEO, QuantZ Machine Intelligence Technologies
- Rajesh Krishnamachari, Head of Data Science - Equities, Bank of America Merrill Lynch
- Peter Hafez, Chief Data Scientist, RavenPack

Today, most financial institutions are working hard to adopt a data-driven approach. Although many asset management firms, banks and hedge funds are beginning to disrupt their analytics landscapes by gathering immense volumes of data assets, these companies are at varying levels of Big Data maturity. Firms able to access huge amounts of data possess a valuable asset that when combined with the ability to analyze it, are outpacing those living in oblivion. In this panel, we discuss how financial institutions can ensure that the potential of Big Data is actually realized by: 1) leveraging the breadth, volume and timeliness of available data; 2) developing machine intelligence that is continuously learning and improving; and 3) understanding the economics that make a data strategy work.

14:15 pm Multi-Dimensional Analysis of News Sentiment Factors

Dr. George Bonne, Executive Director, Equity Factor Research, MSCI

George will present his latest research on news sentiment signals in the framework of the Barra equity factor models. He will evaluate factors constructed from the latest generation of RavenPack data, whereby highlighting improvements over previous versions in coverage, cross-sectional explanatory power and factor returns. George will also demonstrate how the results are robust to factor formulation, geography, and time period.

14:35 pm The Neural Networks Survival Kit for Quants

Matthew Dixon, Assistant Professor of Finance and Statistics, Illinois Institute of Technology

Using examples ranging from portfolio construction to algorithmic trading, this talk will explain neural networks as a non-parametric econometrics technique. Matthew will also provide various examples illustrating the tradeoffs between using Deep Q-learning versus supervised deep learning for predictive modeling with signals such as news sentiment.

14:55 pm Break

Coffee & tea will be served.

15:25 pm Profiting from CAPEX Announcements

Hong Li, Head of U.S. Equity Quantitative Research, Managing Director, Citi Research

In this presentation, we study CAPEX as an stock selection (alpha) factor. We have found that buying stocks with recent CAPEX announcements outperform the market over the long run while high CAPEX stocks based on accounting reports tend to underperform.

For compliance reason, slides and video are not available.

You can however access the key results and comments by Peter Hafez on the methodology used on the underlying white paper on " CitiBank's take on CAPEX announcement strategies using RavenPack data ."

15:50 pm Panel: Will Artificial Intelligence Create a ‘Useless Class’ of Financial Professionals?

Moderator: Bartt Charles Kellermann, Founder and CEO, Global Capital Acquisition
Panelists:
- Matthew Dixon, Assistant Professor of Finance and Statistics, Illinois Institute of Technology
- Sara Castellanos, Emerging Technologies Reporter, The Wall Street Journal
- Igor Halperin, Research Professor of Financial Machine Learning, NYU Tandon School of Engineering

Are machines likely to become smarter than humans? Is Artificial Intelligence (AI) creating a “useless class” of investors and traders? It isn’t hard to miss the warnings. In the race to make computers more intelligent than us, we are bringing forth the end of days of the traditional investor. In this panel, we debate whether finance professionals will be pushed out of employment by intelligent machines. What should we do with all the superfluous brokers, bankers, and traders once we have highly intelligent algorithms that can do almost everything better than they can? Consequently, will new professions emerge and what will they look like? Will these new jobs be completely reliant on AI and will people lack the basic ability to make their own decisions? What skills will people need to reinvent themselves quickly enough to survive in the industry?

16:50 pm Closing Remarks

17:00 pm Cocktail Reception at the Venue

We invite you to join us for some well deserved drinks and canapes after the conference.

Speakers

The speaker line-up is final. We have invited several top buy and sell-side professionals, as well as academics. Below are confirmed speakers:

Last Updated: September 4, 2018

Nitish Maini
General Manager, Virtual Research Center / Vice President, Portfolio Management
WorldQuant

Nitish specializes in building the trading and business strategy for Virtual Research Center. He is also involved in setting up the research environment for WorldQuant’s new offices and building collaborations with academia for the firm. Nitish has gained exposure to a variety of areas, including risk, consulting, business development, quantitative research and trading.

Rajesh T. Krishnamachari
Head of Data Science, Equities
Bank of America Merrill Lynch

Rajesh expertise is on utilizing big/alternative data and machine learning / A.I. algorithms. He is undergoing research signals for systematic trading across asset classes by coupling data analysis with market intuition. Previously, he was Investment Strategist at JP Morgan.

Bartt Charles Kellermann
Founder and CEO
Global Capital Acquisition

Bartt Kellermann is the founder and host of Battle of the CRYPTOS and Battle of the Quants. An industry leader in Quantitative Finance, Bartt founded Global Capital Acquisitions (GCA) in 2002, a hedge fund consulting firm focused on bringing clients smart, innovative investment strategies in the alternative investment space.

Matthew Dixon
Assistant Professor of Finance and Statistics
Illinois Institute of Technology

Matthew published over 20 peer reviewed publications on deep learning and financial modeling, has been cited in Bloomberg Markets and the Financial Times as an AI in fintech expert, and is a frequently invited speaker in Silicon Valley and on Wall Street. He has consulted for several prop trading and asset management firms around AI and is the co-founder of the Thalesians.

Hong Li
Head of U.S. Equity Quantitative Research | Managing Director
Citi Research

Hong began his career in 1997 as an analyst in the Equity Derivatives Research group of Salomon Brothers, one of the predecessors of Citi. He has published numerous papers on academic and industry journals, such as Journal of Portfolio Management, Risk, and Journal of American Statistical Association.

Dr. Ronnie Shah
Director and Head of U.S. Quantitative Research and Quantitative Investment Solutions
Deutsche Bank

Prior to Deutsche Bank, Dr. Ronnie Shah led quantitative research efforts in various senior roles for Gerstein Fisher Funds, Dimensional Fund Advisors and for the Scientific Active Equity team at BlackRock. His research has been published in various financial journals. He also serves as an adjunct professor of Finance at the University of Texas McCombs School of Business.

Tim Harrington
CEO
BattleFin Group

Tim Harrington is the CEO of BattleFin Group, the global trading tournaments set to democratically identify the best liquid investment strategies across asset classes and geographies. With over 20 years of experience in the financial services industry, Tim worked his way through the investment world, and is now focused on algorithmic and big data related investing strategies.

Matei Zatreanu
CEO / Founder
System2

Matei founded System2 on the belief that fundamental investing will be augmented by data-driven technology. He previously played a leading role in the data initiative of a large global hedge fund. There, he sourced alternative data from hundreds of vendors and performed research studies.

Dr. George Bonne
Executive Director, Equity Factor Research
MSCI

George Bonne, PhD, PRM joined MSCI in 2016 as Executive Director of Equity Factor Research, where he and his team work to create new and innovative factors to be used in MSCI’s analytics and index products. Current projects involve creating new Sentiment factors derived from options, short interest, and estimates data, as well as exploring alternative big data sources and algorithms.

Igor Halperin
Research Professor of Financial Machine Learning
NYU Tandon School of Engineering

Igor is Research Professor of Financial Machine Learning at NYU Tandon School of Engineering. His research focuses on using methods of Reinforcement Learning, Information Theory, neuroscience and physics for financial problems such as portfolio optimization, dynamic risk management, and inference of sequential decision-making processes of financial agents.

Sara Castellanos
Emerging Technologies Reporter
The Wall Street Journal

Sara is an award-winning reporter at Wall Street Journal covering emerging technologies such as quantum computing, artificial intelligence and augmented reality and how they’re being used at Fortune 500 companies. Sara is also the co-producer of WSJ's Future of Everything podcast episodes, "The Age of Quantum Computing is (Almost) Here" and "The Global Race for Quantum Computing Supremacy."

Milind Sharma
CEO
QuantZ Machine Intelligence Technologies

Milind has 20 years of market experience. Prior to launching QuantZ Machine Intelligence Technologies, he managed a Prop Trading desk at RBC, served as Director and Senior Proprietary Trader at Deutsche Bank and was co-founder of Quant Strategies at MLIM (now BlackRock) with approx $30 Billion in AUM. He has published extensively on hedge funds (JoIM, Risk Books, Wiley etc.).

Jonathan Regenstein
Director of Financial Services
RStudio

Jonathan is the Director of Financial Services practice at RStudio and the author of "Reproducible Finance with R: Code Flows and Shiny Apps for Portfolio Management" (CRC Press) and writes the "Reproducible Finance" blog series for RStudio. Prior to joining RStudio, he worked at J.P. Morgan. He studied international relations at Harvard University and did graduate work in political economy at Emory University.

Armando Gonzalez
CEO
RavenPack

Armando Gonzalez is President & CEO of RavenPack, the leading provider of big data analytics for financial institutions. Armando is an expert in applied big data and artificial intelligence technologies. He has designed systems that turn unstructured content into structured data, primarily for financial trading applications. Armando is widely regarded as one of the most knowledgeable authorities on automated text and sentiment analysis.

Peter Hafez
Chief Data Scientist
RavenPack

Peter is a pioneer in the field of applied news analytics, bringing alternative data to banks and hedge funds. He has more than 15 years of experience in quantitative finance with companies such as Standard & Poor's, Credit Suisse First Boston, and Saxo Bank.