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Market Timing, Big Data and Machine Learning

September 22, 2016 @ 5:00 pm - 7:00 pm

| $15.00

 

“There is a stigma against market timing.  This stigma existed for good reasons, but the explosion of vast data sets and new analytical techniques has now made timing the market possible.  Just as it was considered irresponsible to time the market over the last 30 years, it will be considered irresponsible NOT to time the market in the next 30 years.”

— Blair Hull

 

On Thursday, September 22, Chicago QWAFAFEW and Trading Technologies will cosponsor a meeting focusing on two computation-intensive alpha strategies. The speakers will be Blair Hull, most recently founder of Ketchum Trading, and Matthew Dixon of the Illinois Institute of Technology’s Stuart School of Business and founder of Quiota, LLC. Hull, a mover in financial markets for more than 30 years, researched a data driven trading strategy and last June launched the HTUS ETF based on it. Dixon is prolific researcher in the fields of machine learning and high performance computation.

The meeting will take place at Trading Technologies offices at 222 South Riverside Plaza. Doors will open at 5:00 pm for conversation, light food and drinks. The event will start at 5:30 pm and officially end at 7:00.

Bair Hull will address the following topics:

  • Prior research and theory regarding return predictability
  • Combining large numbers of predictors to improve forecast accuracy
  • Prediction methodology
  • Back-tested and live results

Matthew Dixon will address the following topics:

  • Deep learning as an approach for multi-instrument predictions
  • Building prediction classifiers and integrating them into algorithmic trading strategies
  • Implementation aspects, including many-core architecture design considerations
  • Use of level I and II CME futures history

Link to Hull’s paper “A Practitioner’s Defense of Return Predictability,” written with Xiao Qiao: papers.ssrn.com/abstract_id=2609814.

Link to Dixon’s paper “Classification-Based Financial Markets Prediction Using Deep Neural Networks,” written with Diego Klabjan and Jin Hoon Bang: papers.ssrn.com/abstract_id=2756331.

Speaker biographies:

Blair Hull began his career in the investment industry as a member of a skilled team of blackjack players in Las Vegas in the 1970’s.  In 1985, Blair founded Hull Trading Company, which became a global leader in the application of computer technology to listed derivatives trading.   Hull Trading leveraged technological innovation and quantitative models to become one of the world’s premier market-making firms, trading on 28 exchanges in nine countries.  At its peak, Hull Trading Company moved nearly a quarter of the entire daily market volume on some markets, executed over 7% of the index options traded in the United States, 3% of the equity options, and 1% of all shares traded daily on the New York Stock Exchange.  In 1999, Hull sold his company to Goldman Sachs for $531 million.  Currently, Blair oversees Ketchum Trading, a privately held, proprietary trading firm located in Chicago.  Driven by algorithms and technology, this high frequency trading firm makes markets and trades in options, futures and stocks.  Blair Hull recently launched an actively managed ETF, listed on the New York Stock Exchange, utilizing predicative analytics.

Matthew Dixon is an Assistant Professor of Finance at the Illinois Institute of Technology and the founder of Quiota LLC, a consulting firm providing machine learning expertise to trading firms. Matthew began his career in structured credit trading at Lehman Brothers in London before pursuing academics and consulting for financial institutions in quantitative trading and risk modeling. He holds a Ph.D. in Applied Mathematics from Imperial College (2007), a Master of Science in Parallel and Scientific Computation with distinction from the University of Reading (2002) and has held postdoctoral and visiting professor appointments at Stanford University and UC Davis respectively. He has published several academic papers, serves on the program committee of multiple computational finance workshops and chairs the workshop on high performance computational finance at SC.

Admission is $15 in advance (or $20 at the door) with light food and drinks provided. Students and unemployed $10.

Purchase tickets or reserve a seat (space available) via TicketLeap (at chicagoqwafafew.ticketleap.com/market-timing-big-data-and-machine-learning.)

QWAFAFEW is an informal organization for discussions of quantitative investment topics. QWAFAFEW has active chapters in Chicago, Boston, Hartford, New York, Denver, Princeton, and San Francisco.

Trading Technologies has been a Chicago-based global leader in trading platform innovation since 1994. The firm’s next-generation TT® platform is the fastest commercially available futures trading platform. Create your free trial account at www.tryTTnow.com.

Details

Date:
September 22, 2016
Time:
5:00 pm - 7:00 pm
Cost:
$15.00
Website:
https://chicagoqwafafew.ticketleap.com/market-timing-big-data-and-machine-learning/

Venue

Trading Technologies
222 South Riverside Plaza
Chicago, IL 60606 United States
+ Google Map
Website:
www.tradingtechnologies.com