Day 1


Breakfast & Registration


Chairman’s Opening Remarks

Bob Litterman

Pricing carbon – a pragmatic approach to address mankind’s greatest risk management problem

  • The difficulties of pricing high-cost, low-probability events – is there a viable economic argument for implementing a costly carbon tax whose benefit may or may not be realized at an unknown point in the future?
  • Today’s bill & tomorrow’s dilemma – how much should society spend today to insure the future against climate risk?
  • Investor & shareholder response – are we approaching a tipping point in public opinion and policy on climate risk?
Attilio Meucci

FinTech Education - leveraging technology to understand finance, analytics and data in theory and practice

  • Say it (Ying & Yang) – hardcore math made easy
  • See it (Visualization) – voiced-over simulations as opposed to lecture recording
  • Do it (Interactive computing) – live data, cloud-based computing, hosted editing for on-the-fly replication
  • Share it (Community) – slide neutralization, feedback looping
  • Frame it (Cross-linking) – multi-media interconnectivity, spoke-to-hub architecture
Panel discussion

Regulation AT – how would the CFTC’s landmark proposal affect proprietary traders, market fairness and systemic risk?

  • How would the CFTC and other government agencies use proprietary source code obtained from automated traders to reduce the likelihood of “flash crashes” and other harmful market disruptions?
  • Do the potential benefits justify significantly lowering the bar for government access to intellectual property? 
  • How will regulators protect source code from hackers and cyber-breaches? 
  • How would market participants, particularly smaller ones, handle the higher compliance costs created by Reg AT’s increased risk controls, reporting demands and recordkeeping requirements?
  • How should exchanges and trading venues be involved in the oversight process?

SPEED Networking

Panel discussion

Latency management tools, technologies and platforms for high-performance trading systems

  • Deploying low-latency messaging tools
  • Increasing real-time visibility into infrastructure
  • Techniques and architecture for achieving maximum system performance
  • Measuring latency – how fast do you need to be?
  • Ultra-low latency – ticker plants and order execution gateways
  • Key differentiators for high-performance servers – what features can provide latency-sensitive trading firms with superior performance in connectivity, data access and computation?
Stéphane Tyĉ

Microwave lines – a review of the latest developments

Panel discussion

FPGAs, acceleration technologies, GPUs and high-performance hardware

  • Budget balancing – speed vs. capacity and latency vs. performance
  • Parlaying speed into intelligence – how are new classes of server technology enabling deterministic performance in addition to cutting latency?
  • Measuring the value of FPGA enhanced functionality – how can they optimize trade workflow and be applied beyond the traditional domains of market data acquisition and distribution?

Networking Lunch

round tables


These small group discussions don’t require any presentation or preparation, and are simply designed to serve as platforms for networking, collaboration and information exchange between like-minded professionals.

Since roundtable sessions run concurrently, you can choose 1 session that is most interesting.

Click on above text to expand list of roundtable topics and the respective discussion leaders.
  • Backtesting & financial modeling in the cloud – security, agility and strategy
  • Greg Ulepic

    Greg Ulepic, Director, Avere Systems

  • Big data architecture, infrastructure & analytics - tools & technologies for achieving peak enterprise performance (Hosted by HPE Veritca)
  • David vs. Goliath – how are savvy smaller exchanges adapting in the consolidation era?
  • Haroon Askari

    Haroon Askari, Deputy Managing Director, Karachi Stock Exchange

  • Non-traditional data & AI – how to leverage unstructured data sourced for alpha generation
  • Perception arbitrage - why wait for information to arrive if you can create it?
  • Efrem Hoffman

    Efrem Hoffman, CEO, Running Alpha Investments

  • Real-time market data – best practices for assessing and responding to data quality in latency-critical trading systems
  • David Taylor

    David Taylor, Chief Technology Officer, Exegy

  • Tick to trade & high-performance options trading – why? how? how much?
  • Kevin Darby

    Kevin Darby, Managing Partner, Blue Trading Systems LLC

  • Trading technology scorecard - what are the factors driving change in our ecosystem?
  • Brian Cassin

    Brian Cassin, Head of Product & Strategy, North America, Vela Trading Technologies

  • Ultra-low latency trading on CME with FPGAs
  • John Lockwood

    John Lockwood, CEO, Algo-Logic Systems


    5-minute walk from roundtables

    Automated Trading & HPC

    Chairman’s Opening Remarks

    Quant World & Big Data in Finance

    Chairman’s Opening Remarks

    Automated Trading & HPC

    Ultra-low latency connectivity – how is the game of speed changing in today’s automated trading environment?

    • Cloud & carrier neutral co-location – selecting the right connectivity for your firm 
    • Fiber vs. microwave vs. millimeter wavelength – comparing and contrasting new developments in network connectivity
    • Benefits beyond latency – how can you parlay low latency into high trading intelligence?
    • Network monitoring – solutions, methods and technologies for identifying trends, detecting outliers and correcting excessive latency and jitter in real time
    • How can you accurately measure latency and jitter in a microsecond-sensitive ultra-low latency networking environment?
    • Next-generation data centers – open infrastructure, software-defined technologies and automation
    • LEO (low-earth orbit) satellites – a connectivity revolution?
    Quant World & Big Data in Finance

    Next-generation data – what tools, technologies and applications will be most critical for enabling alpha discovery?

    • Is it sustainable to sell a packaged alpha product? If so, how are vendors offering packaged alpha products accounting for crowding and the resultant decay of the value with time?
    • Will the ability to manage emerging unstructured data sources (i.e. nanosatellites, drone imagery, Internet of Things) ultimately become the most critical ingredient for alpha discovery?
    • How are vendors helping firms de-silo and integrate enterprise data into a unified environment?
    • Underlying infrastructure – how will firms maintain the necessary computational resources to uncover alpha-generating signals from expanding and diversifying data sources? Will in-memory applications become a critical component in all data management and analytics platforms?
    Automated Trading & HPC

    Enterprise data management – how are you applying innovative technologies to streamline and modernize the information lifecycle?

    • Warehousing & integration – best practices for building an enterprise data warehouse and unifying data management across different IT teams and departments
    • Standardization – what are the benefits of a common industry language, or financial Rosetta Stone, on operational efficiency and regulatory reporting?
    • Storage – deploying cloud servers and software-defined data centers to maximize storage efficiency and scalability; maintaining storage requirements to accommodate new data sources and exponentially growing data volumes 
    • Governance – how to design an effective data governance strategy for managing regulatory risk and meeting compliance demands 
    • Roadblocks – data quality issues; integrating big data technologies with legacy IT infrastructure
    Quant World & Big Data in Finance

    Risky business – how are savvy funds blending analytics, cloud computing and quantitative methodology to supercharge risk management? 

    • How are portfolio managers accurately assessing risk as modern markets become increasingly complex and volatile?
    • Leveraging next-generation data management and analytics tools to achieve an integrated view of portfolio risk exposure across time horizons and asset classes
    • Risk modelling – how can new validation tools be applied to ensure accuracy? 
    • Predictive analytics – how are you using predictive tools to measure risk?
    • Compute-intensive risk – how are quants and risk managers using the cloud to scale up modeling capacity without breaking the bank on building new data centers?

    Afternoon Networking Break

    Automated Trading & HPC

    Re-thinking IT infrastructure for trading – compute, storage and networking 

    • Design and engineering developments – how are new technologies driving trading firms from proprietary software and hardware to open source, automated, software-defined models?
    • Hyperconverged vs. converged vs. traditional infrastructure – assessing the benefits of combining compute, storage and networking into a single, software-driven appliance
    • Outsourcing your data center – sourcing, integrating and managing third-party DCaaS (data center as-a-service), IaaS (infrastructure as-a-service), PaaS (platform as-a-service) solutions
    • Containerization vs. virtualization – how can you leverage container technology to increase operational efficiency, boost scalability, facilitate application development and lower costs?
    • Docker – a panacea for achieving innovation and removing the albatross of obsolete, over-complex enterprise software?
    Dr Arun Verma

    Extracting embedded alpha in social & news data - a quantamental approach

    • Extracting actionable information in the high volume, time-sensitive environment of news and social media stories 
    • Using machine learning to address the unstructured nature of textual information
    • Techniques for identifying relevant news stories and tweets for individual stock tickers and assigning them sentiment scores
    • Does using these sentiment scores in your trading strategy ultimately help in achieving higher risk-adjusted returns? 
    Bill Chen, PhD

    The Mathematics of Poker – quantitative methodology for the Hold’em table and trading desk

    • What lessons can be applied from poker to quantitative trading, and vice versa?
    • Online vs. live poker and pit trading vs. screen trading 
    • Exploitative play vs. optimal play 
    • Poker finance – portfolio theory, risk of ruin and the Kelly Criterion
    • Psychological components of trading and poker
    • Will quantitative skills and knowledge ultimately become a necessity for poker players?

    Networking Cocktail Party

    last published: 21/Apr/17 20:35 GMT