Conference Program

Inside Market Data Chicago, 27th September 2012

8.10 Registration and breakfast

8.30 Welcome remarks

8.40 Keynote

9.10 End-user panel Market data management in the battle zone of Chicago's competition, cost pressures and changing regulations

• Procuring profitable data: assessing the real value of data and are current prices justified?
• Time to market: best practices for the implementation of new products
• Developing synergy between practitioners and vendors: establishing effective lines of communication
• Adapting to the implications of data licensing and compliance for an increasingly mobile workforce and client base

10.00 Morning break

Managing Chicago's market data: perspectives, challenges and current dynamics

Eliminating technological challenges: scalable solutions in storage and trading architecture

10.30 Opening Remarks

10.30 Opening Remarks

10.35 Panel Clarifying the methods of pricing, valuations and ratings

• Rating Newsfeeds, Ratings, Research and Tweets: identifying competitive value from additional datasets and tools
• The buck swaps here: the impact of SEFs and new venues on trading activity, data volumes and quality, and the data businesses of existing marketplaces
• Information Arbitrage: using OTC pricing methodologies to identify inefficiencies in exchange-traded instruments
• Valuing VAR: understanding risk for better trading through accurate evaluations and effective challenges

10.35 Panel Re-architecting enterprise infrastructure for the "age of big data"

• Putting the "data" in "Big Data": the benefits and challenges of applying new techniques to processing market data
• Building the foundations to raise the roof: breaking down data silos to improve enterprise communication and data quality, and reduce architectural complexity
• Storm or silver lining: expanding the use cases for how and where to harness the power of cloud computing
• From handlers to Hadoop: finding the right technologies to future-proof your firm for massive throughput and storage requirements

11.20 Panel Show me the money: measuring, monitoring, managing and monetizing data quality and compliance

• Quantifying quality and the costs and benefits of good data management policies and practices, from accuracy in the front office to timely back office reporting
• The costs of compliance vs. non-compliance: ensuring adherence to exchange and vendor licences, and implementing and enforcing rules around usage
• Mining what's mine: establishing data ownership and stewardship to capture, keep and make the most of in-house data assets
• Rise of the machines: is a fully-automated data factory feasible for quality control, or is human intervention still needed to put the "man" in Data Management?
  

11.20 Panel High Noon for Low Latency: is being fastest on the draw still enough?

• Assessing how the value, importance and cost of achieving low latency is changing for different market participants?
• Breaking the speed limit: how fast is fast enough, what new approaches and technologies can firms leverage to optimize latency across their entire trading architecture?
• The "haves" vs. the "have-nots": where firms dropping out of the latency race can focus efforts to remain competitive
• A new sheriff in town: leveraging low-latency technologies to satisfy risk management and regulatory requirements
• The future beyond futures: applying latency lessons to low-frequency asset classes

12.05 Lunch break

13.05 Case study

13.30 Panel Thinking Outside the Loop: infrastructure and connectivity for joined-up trading strategies

• Too close ain't close enough: combining co-location and proximity hosting to achieve optimal trading for multi-venue strategies
• Reducing distance, raising cost: overcoming space, power and hardware limitations of co-locating across multiple locations, and the impact of exchange consolidation and new venues
• Datacenters as the new exchange floors: identifying the most valuable locations to co-locate
• Beam me up, Data: from neutrinos to quantum teleportation, which new developments offer potential for competitive advantage, and which are just science fiction?

14.15 Afternoon Break

14.45 Case study

15.10 Panel How to avoid the pitfalls of hidden complexities in data analytics

• What data should you analyse?
• Know your data: leveraging knowledge to maximise value in decision making
• Social Trading: evaluating sentiment data to predict trading opportunities and the future of the markets
• Displaying data analytics visually

15.55 Closing remarks

16.00 Cocktail reception