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Big Data is the New Currency - New York City

Top industry experts and practitioners debated the future of big data monetization, issues surrounding data privacy, and data protection strategies in capital markets. You may request access to slides and full videos. Watch our previous event highlights video for what to expect.

Slides and Videos of Each Session

Introduction: Big Data a Big Opportunity

While data monetization becomes a crucial part of their strategy, financial institutions must address the risks associated with data privacy, the sourcing of alternative data, data leaks and security breaches, and learn how to mitigate those risks.

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The Coming Political Fight over Personal Information and Who Owns those Data

Given the substantial and fast-growing value of individuals' data on Google or Facebook, Robert explores the emerging question of whether the data are people’s personal property or belong to the companies that use their resources to collect, organize, analyze and rent or sell them. In this context, he examines the emerging political and policy responses to the new business model based on monetizing people’s personal information.

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How Much is that Byte Worth? Quantifying the Value of Information

Learn the difference between data and information, and why this distinction is important. Gain a greater understanding of the complexities of valuing information. Take away some practical advice for considering the value of information in financial services organizations.

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Panel - How Much is Your Personal Data Worth?

Our expert panelists discuss how governments and corporations go about harvesting this information, what they do with it, who they provide it to, whether it is right or wrong and even how much money is being made at the expense of your data privacy. The panel will also address concerns over data protection in a world where the rise of “Business A.I.” seems unstoppable.

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Enhancing Quantamental Signals with Sentiment

Milind introduces a Quantamental investing model and synopsizes a sentiment signal. He shows how this sentiment signal performs as an overlay. He shows how his approach is effective in anticipating buyouts, which should be of much interest to activists, risk arbitrageurs and speculators on the long side as well as market participants (typically quants), looking to eliminate event risk on the short side.

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Finding Relevant Insights in a Data-Overloaded World

Many fundamental investors are struggling to find useful insights in a world that is becoming "over-abundant" with data. Barry Hurewitz, founder of UBS Evidence Lab, shares findings from extensive research on the investment processes of top investors and the implications on the use of alt data. Slides are not available for this session.

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Asset Managers: It's Time to Monetize Your Own Data

Peter presents a real case study showcasing how a fundamental asset management firm is leveraging RavenPack technology to transform their own emails, messages, and files into trading signals to create alpha generating strategies.

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Novel Mathematical Techniques for Extracting Structure From Text

Gordon explains how to use Independent Component Analysis to reveal latent factors hidden within news sentiment, and how to use latent factor analysis to make predictions.

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The Uses and Misuses of Machine Learning in Finance: What Asset Owners Should Know

Dr. Simonian discusses the types of questions that asset owners should be asking when speaking to managers who claim to use machine learning in their investment process, drawing on his own experience with and solutions to common pitfalls in financial data science research.

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A New Dimension in ESG Investing and Accounting Quality – Quadrophobia

Slides and video are not available for this session.

Panel - Why Natural Language Processing is the Crown Jewel of A.I.

Natural language processing (NLP) is a key area of research in Artificial Intelligence (AI) that helps computers understand, interpret and manipulate human language. Will machines ever really understand language?

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Machine learning based Transaction Cost Analysis in Algorithmic Trading

Swagato formulates a methodology using machine learning to sift through troves of order execution data to identify key drivers of algorithm performance and provide actionable recommendations to clients in delivering execution alpha. This approach provides the ability to focus on the important performance drivers and optimize those for further enhancing algorithm performance.

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Getting Dirty: What it Really Takes to Tease Out Alpha from Big Data

In this panel, speakers discuss how financial institutions are going about monetizing non-traditional big data sources to generate both investment and operational alpha.

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Speakers

Last Updated: August 21, 2019

Robert J. Shapiro

Robert J. Shapiro

Economist and Political Adviser

Robert J. Shapiro is former U.S. Under Secretary of Commerce for Economic Affairs and current Chairman of Sonecon, LLC. Dr. Shapiro brings broad knowledge and experience in economics and politics based on his decades of conducting analysis and providing advice to presidents including U.S. president Bill Clinton and British Prime Minister Tony Blair, senators, representatives and governors, as well as foreign leaders and senior executives at numerous Fortune 50 and Fortune 100 companies.

Gordon Ritter

Gordon Ritter

Quantitative Trading Entrepreneur

New York University

Gordon Ritter is 2019 Buy-side Quant of the Year, adjunct professor at New York University and a former senior portfolio manager at systematic hedge fund GSA Capital in New York. Gordon founded his own quantitative trading firm; before that he was a senior portfolio manager at GSA Capital where he designed, built, and managed statistical arbitrage strategies in multiple geographies and asset classes, and directed research.

Javed Jussa

Javed Jussa

Quantitative Strategist

Wolfe Research

Javed Jussa is responsible for alpha signal, Big Data, ESG, and small-cap research and managing the day-to-day operations of the QES team. Prior to Wolfe Research, Javed was the US Head of Quantitative Strategy at Deutsche Bank. Javed also has several years of experience in the investment business with Macquarie Capital, CIBC World Markets, and IBM Consulting. Javed holds a joint Bachelors of Electrical Engineering and Computer Science and an MBA in finance and statistics.

Jason Bloomberg

Jason Bloomberg

Best Selling Author

Jason Bloomberg is a leading IT industry analyst, author, keynote speaker, and globally recognized expert on multiple disruptive trends in enterprise technology and digital transformation. He is ranked #5 on Onalytica’s list of top Digital Transformation influencers for 2018 and #15 on Jax’s list of top DevOps influencers for 2017, the only person to appear on both lists.

Joseph Simonian

Joseph Simonian

Senior Investment Strategist

Acadian Asset Management

Joseph Simonian is a Senior Investment Strategist at Acadian Asset Management. Before joining Acadian, Joseph was the Director of Quantitative Research for the Portfolio Research and Consulting Group at Natixis Investment Managers. Prior to that, he was a principal research analyst in the Global Institutional Solutions Group at Fidelity Investments. He was also previously a vice president at J.P Morgan Asset Management and PIMCO. Joseph is a noted contributor to leading finance journals and is currently the co-editor of the Journal of Financial Data Science and Advisory Board member for the Financial Data Professional Institute.

Barry Hurewitz

Barry Hurewitz

Global Head of UBS Evidence Lab Innovations

UBS

Barry Hurewitz is the Global Head of Evidence Lab Innovations, prior to his current role, Mr. Hurewitz served as Global COO for UBS Investment Research. During Barry's tenure, UBS Research was voted the top global equity research provider in the world by Institutional Investor magazine. Before joining UBS, Mr. Hurewitz was the Global COO of Investment Research at Morgan Stanley, where he founded AlphaWise.

Feargal O'Sullivan

Feargal O'Sullivan

CEO

USAM Group

Feargal O'Sullivan, Chief Executive Officer, is a proven business leader with the rare ability to blend business acumen and deep technical knowledge. With over 20-years of experience at BlackRock, Reuters and NYSE, Feargal understands the needs of clients and vendors in equal measure.

Swagato Acharjee

Swagato Acharjee

Quantitative Strategist

RBC Capital Markets

Swagato is a quantitative researcher in the equities electronic trading team at RBC. His main responsibilities are making enhancements to the electronic trading platform and working with the electronic sales and sales trading team in improving trading performance for clients. After graduating with a PhD in Engineering from Cornell University, he was a quantitative researcher in the electronic trading teams at Citi and Bank of America Merrill Lynch. Prior to joining RBC, he was a researcher and trader at a quantitative hedge fund working on statistical arbitrage strategies and long term factor models.

Yimei Guo

Yimei Guo

Managing Director & Global Head of Investment Research Technology

Morgan Stanley

Yimei Guo is a Managing Director and the Global Head of Investment Research Technology at Morgan Stanley. As a senior technology leader, she is responsible for setting strategy and delivering innovative solutions to drive business outcomes. In recent years, Yimei has been leading strategic initiatives in machine learning, data and analytics, and digital transformation. She was recently named one of IBM’s 2019 Women Leaders in AI. Throughout her 25+ year career, Yimei has built expertise spanning various business and technology areas including Investment Research, Global Capital Markets, Client Relationship Management, Content Management, and Digital Marketing.

Robert Marsh

Robert Marsh

Former Chief Product Officer at Kensho (now S&P)

Robert has more than thirty years’ experience developing and using tools, frameworks and data to solve problems in markets and investing. Previously the Chief Product Officer at Kensho, he was exposed to the challenges vendors face in supporting a varied client base, leading teams of a different culture, and managing through the before and after of a successful acquisition. Prior to this, Robert spent twenty-six years at Tudor working across a range of functions (PM, Strategist, Developer) which resulted in a well-developed understanding of the requirements demanded by large, top performing clients in a high stakes environment.

Milind Sharma

Milind Sharma

CEO

QuantZ Machine Intelligence Technologies

Milind Sharma’s 23 years of market experience span running prop desks at RBC & Deutsche Bank (Saba unit) as well as hedge funds (QuantZ) & mutual funds (MLIM). His funds have won many awards over the years including those from Morningstar, Lipper, WSJ, Battle of the Quants & BattleFin. He was also a co-founder of Quant Strategies at MLIM (now BlackRock) & was co-architect of Raven TM (derivatives risk system) at Ernst & Young. His publications have appeared in JoIM, Risk Books, Elsevier, Wiley etc. In addition to dual MS degrees he was also in the Logic/ AI PhD program at Carnegie Mellon. Other education includes Oxford, Vassar & Wharton.

Bogdan Ianev

Bogdan Ianev

Director of Equity Derivatives Structuring

Credit Suisse

Bogdan Ianev is a Director in Equity Derivatives Structuring at Credit Suisse, where he co-leads the development of volatility-based equity derivatives payoffs and systematic investment strategies for various types of investors. Before to his current role, Mr. Ianev spent 3 years structuring corporate derivative solutions for insurers also at Credit Suisse. Prior to his 12 years at Credit Suisse, Mr. Ianev worked for as an actuary and investment professional at an insurance company. He holds a Master’s degree in Mathematics of Finance from Columbia University and a Bachelor's degree in mathematics from Wabash College. Mr. Ianev is a Fellow of the Society of Actuaries, a member of the American Academy of Actuaries, a certified Financial Risk Manager and a CFA charterholder.

Jib Wilkinson

Jib Wilkinson

Analytics Leader

Deloitte

Jib leads Deloitte Consultings’ Analytics offerings for the Investment Management sector in the U.S. helping buy side and asset servicing clients in major technology and business transformations including data modernization, cloud enablement, data analytics, and operational improvement.

John Arabadjis, PhD

John Arabadjis, PhD

Head of Macro Strategy Products & Analytics

Bank of New York Mellon

John is the Head of Macro Strategy Products & Analytics at Bank of New York Mellon, the group responsible for developing macroeconomic models and analytics for BNYM Markets business and their clients by applying the tools of data science to vast amounts of proprietary, market and macroeconomic data sets. Before joining BNYM, John headed teams of data scientists at State Street, guiding R&D in a number of areas including behavioral finance, alternative data, multi-asset risk management, sustainable investing, private equity and quantitative investment management.

Matthew Bergerman

Matthew Bergerman

Director

DTCC

Matthew Bergerman joined the DTCC Data Products team in July of 2015 as a Director charged with the development of solutions in the Equity, Fixed Income, and Reference Data space. He has worked in the Financial Information industry for over 20 years. He has worked on the vendor side previously in the production of data and the development of data applications at Thomson Financial and Pershing.

Armando Gonzalez

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

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.

Location

When:
Tuesday, September 10th, 2019
8:30 AM - 5:00 PM New York Time

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

Where:
Convene Midtown West
117 W 46th St, NYC, USA

The closest subways are 7th Ave Station, 49 Street Station, and 47-50 Streets - Rockefeller Ctr Station.

Partner Sponsors

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Email events@ravenpack.com to know more.

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Our past events

Video highlights

Big Data is the New Currency, London, May 2019

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