Agenda

Mitch Ackles is the founder and CEO of Hedge Fund PR, and the global president and spokesman of the Hedge Fund Association, an international non-profit organization that promotes the understanding and development of the hedge fund industry.

With over 20 years experience, Mitch has a track record of excellence. He has executed campaigns for hedge funds, political and economic leaders, service providers, luminaries, conferences, charitable organizations and local, national and global hedge fund groups. Previously, Mitch was marketing director for vFinance, VP of hedge fund capital introduction for Global Partners Group and worldwide marketing manager for Dow Jones TradeStation. Mitch holds a B.A. in PR and communications, is fluent in English and Spanish, and manages reputations for some of the brightest minds and brands in the hedge fund industry.

When raising visibility, his efforts have resulted in thousands of successes, including product and company awards, news articles, cover stories, speaking engagements, broadcast interviews, events, alliances, and product placements on TV and in books, blogs, and movies. His contact network is coveted and includes virtually every editor, reporter, producer, blogger, lawmaker and influencer that has used the term hedge fund. In times when a low profile is preferred, Mitch has insulated clients from the press, influenced search engines, and provided guidance on communicating with media, investors, employees, and counterparties.

Mitch is devoted to service, demonstrated by the pro-bono support of non-profit organizations. As Hedge Fund Association president and spokesman, Mitch is an advocate for the entire hedge fund community. For HFA, he directs media relations, member events and lobbying on Capitol Hill. Mitch also serves as the media contact for Help For Children, a global charitable organization which raises funds for programs that work to prevent and treat child abuse and A Leg To Stand On, a non-profit organization providing free orthopedic care to children in the developing world.

Mark Yusko is the Founder, CEO and Chief Investment Officer of Morgan Creek Capital Management. Prior to forming Morgan Creek, Mr. Yusko was President, Chief Investment Officer and Founder of UNC Management Company, the Endowment investment office for the University of North Carolina at Chapel Hill, from 1998 to 2004. Throughout his tenure, he directly oversaw strategic and tactical asset allocation recommendations to the Investment Fund Board, investment manager selection, manager performance evaluation, spending policy management and performance reporting. Total assets under management were $1.5 billion ($1.2 billion in endowment assets and $300 million in working capital). Until 1998, Mr. Yusko was the Senior Investment Director for the University of Notre Dame Investment Office where he joined as the Assistant Investment Officer in October of 1993. He worked with the Chief Investment Officer in all aspects of Endowment Management. Mr. Yusko received his Bachelor of Science Degree, with Honors, in Biology and Chemistry from the University of Notre Dame and a Master of Business Administration in Accounting and Finance from the University of Chicago. Mr. Yusko is an Advisory Board member of a number of private capital partnerships and alternative investment programs and has served as a consultant on alternative investments to a select group of institutions. Mr. Yusko is an Investment Committee member of the MCNC Endowment, President and Chairman of the Investment Committee of The Hesburgh-Yusko Scholars Foundation at the University of Notre Dame, and President and Head of the Investment Committee of the Morgan Creek Foundation.

• Using AI-enhanced predictive analytics to improve investment and trading strategies
• Alternative data to generate new investment ideas
• Is cognitive collaboration between human and AI the best of both worlds?

Mike O’Rourke has spent 18 years of his two-decade-long career in technology at Nasdaq. As Global Head of Machine Intelligence and Data Services, he leads Nasdaq’s machine intelligence Innovation Lab that combines proprietary data with advanced analytics and machine learning to produce high-impact results for customers, including the Lab’s newest products: Trading Insights and the Nasdaq Analytics Hub.

• Demonstrate the value of unstructured data with Natural Language Processing to company disclosures
• Reacting to the qualitative information reported in firms’ disclosures by investors
• Corporate problems in 10-K and 10-Q filings on average leads to share price underperformance over the following quarter and future negative earnings surprises

• Supervised Learning – Predicting Market Trends
• Unsupervised Learning – Identifying Correlations
• Deep Learning
• Reinforcement Learning

Prior to co-founding RebellionResearch.com in 2007, Mr. Fleiss served as a Principal at KMF Partners LP, a long-short US equity fund. Mr. Fleiss began his investment career as an analyst for Sloate, Weisman, Murray & Co which was acquired by Neuberger Berman. Mr. Fleiss developed investment algorithms with the firm’s CEO, Laura Sloate who is now a partner at Neuberger Berman and is one of the investors featured in Peter Tanous’ book Investment Gurus. Mr. Fleiss received a BA Degree from Amherst College.

• Confluence of big data, data science, machine learning, and computing power
• Differentiating factors of ALIS
• Upending investment management with technology and engineering

• Selecting stocks with Reinforcement Learning algorithms.
• Adjustments by NLP and Bayesian Statistics techniques.
• High-Performance Computer infrastructure for this framework.
• Backtesting

Juan Pablo Braña is a co-founding partner and Chief Data Officer at Eye Capital, a technology company which develops trading algorithms based on Artificial Intelligence and implements its own multi-market FIX and DMA platform with strong cryptographic and security properties being a pioneer in Algorithmic Trading in the Argentinian markets.

Mr. Braña has a strong academic background as a researcher and professor of Data Science in the financial arena with more than 15 years of experience in Statistics and Applied Math in the industry. He developed braiNY algorithm which is based on Reinforcement Learning techniques, Bayesian Statistics, and Natural Language Processing selects stocks from U.S. markets and manages an equities portfolio. He also designed globalEYE, an algorithm which operates in U.S., London, Hong Kong and Spain markets and also uses Markov Process techniques. Both strategies have shown excellent returns and are on continuing development.

Mr. Braña is part of a multidisciplinary team at Eye Capital, composed by Alexis Sarghel who leads the High-Performance Computing Department, Alejandra M. J. Litterio in the Research and Computational Linguistics area, Federico Massa specialist in Cybersecurity, Nicolás Paladini and Adrian Raguza, both in charge of the finance and business affairs.

• When the unexpected happens
• Determining the correct strategy
• Cybersecurity and privacy issues

• Why are Deep Learning and HFT needed together in asset management and why now?
• How is deep Learning applied in trading? What’s the secret sauce?
• Demystifying deep learning – understanding the intuition behind the strategy

• Preparing for the big data revolution
  
• Using machine learning to create predictive models
  
• Are you part of the change or will you be overthrown?

His commentary and research have appeared in leading business publications such as the Wall Street Journal, Financial Times, CNBC, among many others. Armando holds degrees in Economics and International Business Administration from the American University in Paris and is a recognized speaker at academic and business conferences across the globe.

• Using RL to maximize final (or cumulative) reward
• Deep Q –Learning: From self-driving cars to quant strategies
• Alternatives (evolutionary strategies) and Future (beyond simple Bellman’s equation)

• How to start and overcomes common obstacles
• Overfitting: Overcoming a big cause of poor performance
• Challenges and potential that lie ahead

Jeffrey currently works as the Chief Data Scientist at AB, formerly known as AllianceBernstein, a leading global investment management, and research firm, where he is building a data science team and leading all of the data science initiatives. Prior to AB, he was the Vice President and Head of Data Science at Silicon Valley Data Science, a boutique consulting firm focusing on data science, data engineering, and data strategy consulting. Jeffrey led a team of Ph.D. computer scientists, statisticians, and scientists from various domains to help Fortune 500 companies transform their businesses using data science and emerging data technologies.

With extensive experience in applying a wide range of data science techniques to develop analytic, predictive, and prescriptive solutions, he has expertise in combining high-performance computing and modern data technology to analyze massive databases to generate analytic insights for strategic decision making. Jeffrey held various positions before SVDS, including the Head of Risk Analytics and Quantitative Research at Charles Schwab Corporation, Director of Financial Risk Management Consulting at KPMG, Assistant Director at Moody’s Analytics, and Assistant Professor of Economics at Virginia Tech. During his doctoral study and the last two years of his undergraduate study, Jeffrey worked in research teams at RAND Corporation, the World Bank, the Wharton School, and University of Pennsylvania School of Medicine. Jeffrey holds a Ph.D. and an M.A. in Economics (with a focus on econometrics) from the University of Pennsylvania and a B.S. in Mathematics and Economics from UCLA.

Enjoy a glass of champagne whilst networking with other like-minded individuals on topics that are of most interest to you and fellow delegates.

• Changes in Investment Industry
• Use of Big and Alternative Data
• Application of Machine Learning methods

Marko 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 Ph.D. 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.

• Sourcing alternative data sets
• Building an Alpha library of predictive machine learning models
• Combining data sets to strengthen alpha generation

Tim is a co-founder and CEO of BattleFin Asset Management which is an S.E.C. registered investment adviser.  He is CIO of the BattleFin Alternative Data and Machine Learning Strategy.  Tim is also responsible for strategy selection and for external allocations.  He has over 20 years of experience in the financial services industry.  Most recently Tim was the President and a Partner at Lion’s Path Capital, a hedge fund strategy incubator.  He sat on the Lion’s Path Investment Committee and identified and on-boarded 30 fundamental portfolio managers since the launch in 2009.  From January 2006 until 2009, Mr. Harrington was a Vice President at J.P. Morgan Ventures where he was in charge of Global Technology, Media & Telecom Investments and served as a Portfolio Manager. From February 2002 until January 2006 he was a Telecom & Media Portfolio Manager at Sigma Capital, a subsidiary of SAC Capital and managed a team of four investment professionals. Mr. Harrington graduated from Columbia College in 1998.  He was a member of the Columbia University Judiciary Board as well as a member of the varsity crew team.

• Applying network analysis concepts for optimal asset allocation
• Influence of market regimes on portfolio performance and robustness

He is very interested in the application of state-of-the-art algorithms and numerical methods in wealth and investment management and in high-performance computing.

Prior to joining Bank of America Merrill Lynch, Cristian was a front office quant for Wachovia and Wells Fargo. After supporting interest rate trading desk, he was the lead quant for FX and Commodities trading desks.

He has a Ph.D. from Florida State University in computational and applied mathematics, and MSc degrees from University of Paris XI and University of Craiova.

• Discovering profitable strategies
• How to replicate profitable trades under dynamic market conditions

• Challenges of forming the team: How to attract talent
• Synergy or conflict in the team
• Mixing the old and new

Harold joined Segmint from General Electric Asset Management (GEAM) where he developed investment algorithms for fixed income and equities in his role as the Quantitative Strategist & Senior Data Scientist. Prior to GEAM, Harold led a group at Infosys Data Science where he implemented Big Data Hadoop technology architecture and solutions for Fortune 500 companies.

Earlier in his career, Harold held various data science roles at Citi Group and Wyndham Worldwide.

Harold holds a Bachelor of Integrated Information Systems and a Master of Business Administration in Finance from Long Island University.

• Overcoming “algorithm aversion” of asset managers
• Driving adoption of systematic processes with discretionary managers
• Towards integrated human-machine interactive investing

Norman Niemer leads a quant & data science team for the Chief Investment Officer at UBS O’Connor, the hedge fund unit of UBS, where he leverages machine learning and AI to build investment strategies and systematize fundamental investment processes. He is also responsible for both the business as well as technical aspects of multiple innovation projects that augment human decision makers with machine intelligence. Outside of investment management, he has led teams that built data- and AI-based products that won several high profile coding competitions including Techcrunch NY, Fintech NY and Mastercard Masters of Code NY. Prior to UBS O’Connor, Norman worked at Caxton Associates and Morgan Stanley as well as startup hedge funds and he even founded a tech company in high school! He holds a MS Financial Engineering from Columbia University and a BS in Banking and Finance from Cass Business School (London).

• What can machine learning do wrong and how to avoid the pitfalls
• Dangers of data mining and overfitting, and how to prevent them
• How to sell the concept of using AI to automate investment for clients and investors

Pamela Finelli is the Global Head of Equity Derivatives Research for Deutsche Bank.  Her team provides an in-depth analysis and ideas across a broad range of equity derivatives and delta-one instruments.  She also co-leads Data Innovation Research at Deutsche – a group responsible for leveraging developments in Artificial Intelligence and Big Data.

Pamela started her career in at Bankers Trust Fixed Income Derivatives in a trading risk role and then moved to Equity Derivatives Strategy for Deutsche Bank in NY.  She was a lead architect for eDerivatives.db.com, Deutsche Bank’s award-winning data and analytics website.  From 2007 to 2014, she was based in London and led DB’s European equity volatility, dividend and index-based research group  Her team was ranked #1 in the European Institutional Investor survey from 2010-2014.

Pamela lives in NJ with her husband and three children.  She currently serves on committees for several charitable organizations in her community and was appointed to the Girls’ Board of the UK Chance to Shine charity while she was in London.

Dr. Arun Verma
Quantitative Researcher
Bloomberg LP

Dr. Arun Verma joined the Bloomberg Quantitative Research group in 2003. Prior to that, he earned his Ph.D from Cornell University in the areas of computer science & applied mathematics. At Bloomberg, Mr. Verma’s work initially focused on Stochastic Volatility Models for Derivatives & Exotics pricing and hedging. More recently, he has enjoyed working at the intersection of diverse areas such as data science (for structured data such as financial time series & unstructured data such as sentiment analysis using NLP), innovative quantitative & machine learning methods for statistical arbitrage, and, interactive Visualization & Analytics to help reveal embedded signals from the data.

Mr. Rusakov previously founded Open Capital, a global holding and investment company with assets and portfolio companies in the USA, Europe, and Russia.  Prior to that, he worked for Apax Partners where he was involved in $1 billion worth of buy-outs worldwide.  He started his career in the Mergers & Acquisitions team of Morgan Stanley in London.

Andrej holds an MBA from Harvard Business School and an
MSc. (Summa Cum Laude) in Mathematics (Statistics and Theory of Probabilities) from the Department of Mechanics & Mathematics of Moscow State University.

Andrej is a serial entrepreneur having launched multiple businesses utilizing his team building, leadership, and investing expertise.

At CIT, Ben is now responsible for model development, research and analysis of credit and default risk. This includes probability of default, loss severity & stress testing (CCAR, DFAST). Ben joined CIT in 2015 and is based in New Jersey.

Before joining CIT, he was an Absolute Return Portfolio Manager and Senior Quantitative Researcher at FFTW (a subsidiary of BNP Paribas). Prior to that, he was with Aspect Capital as the Research Manager for financial engineering. Ben started his career at Deutsche Bank as a member of the quantitative research and portfolio construction team. He has 16 years of alternative investment experience.

Ben has a BA in Economics (with honors) from The University of Manchester and an MSc in Mathematical Finance from Imperial College London. He serves as a Director of the Society of Quantitative Analysts (SQA) – which celebrated its 50th-anniversary last year – and sits on the Big Data Advisory Board at Rutgers.

Post-Conference Workshop B: Implementing State-of-the-Art AI and Machine Learning Algorithms for Use in Trading & Capital Markets

• Applying machine learning algorithms to trading decisions
• Developing automated trading strategies based on high performing models
• Understanding the real-world challenges of implementing machine learning based trading strategies