2017 Agenda

Day 1


Breakfast & Registration


Chairman's Opening Remarks

Panel discussion

The D’s of disruption – how will democratization, disintermediation and decentralization shape the future of capital markets?

  • Democratization of investment research – does crowdsourcing earnings estimates from anonymous contributors, professionals and non-professionals from the buy-side, sell-side and academia lead to more accurate forecasting than traditional sell-side research?
  • Real-time information – how are social networks, blogs and other digital mediums offering instantaneous access to news and information filling a void left by traditional investment research?
  • Decentralization, disintermediation & distributed ledger – how will blockchain-based technologies redefine regulation, oversight and the provision of trust in financial transactions?
  • The dark side of decentralization – what are the hidden risks in a blockchain revolution? 
  • Data democracy – is the trend toward equal access to information eroding alpha? If so, how can active managers pivot to regain a competitive edge? 
  • Cryptocurrency market cap, growth, competition & composition – with the total market cap nearing $90 billion in mid-2017, what are the growth expectations for cryptocurrencies heading into 2018? 
Moderator: Mark Beeston, Founder & Managing Partner, Illuminate Financial Management
Daniel Diaz, Head of Business Development, Dash

SPEED Networking

Automated Trading & HPC

HPC & infrastructure strategy – aligning compute, storage and networking for real-time data consumption and analysis

  • Design & engineering developments – how are new technologies driving trading firms from proprietary software and hardware to open source, automated, software-defined models?
  • 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?
  • ‘Big data’ architecture – how are you integrating Hadoop and deploying big data technologies into the enterprise?
  • Real-time insights – how can traders use visualization technology to aid in real-time pattern discovery and outlier detection?
  • High performance storage – achieving performance, density and scale; assessing performance upside for large-scale big data and analytics applications in the growing flash storage market ‘
  • Customizing trading applications in the cloud – how to deliver maximum performance, ultra-low latency and advanced functionality
Quant World & Big Data in Finance

Re-thinking risk – how are savvy funds using new technologies to supercharge risk management?

  • Complexity & volatility – how are portfolio managers accurately assessing risk in unpredictable modern market conditions?
  • Next-generation data management & analytics – leveraging new 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?
  • Alternative data for risk management – how can “alt” data be leveraged as an indicator for measuring risk, anticipating volatility and extracting unique market insights?
Quant World & Big Data in Finance

Evaluating time-series momentum in non-liquid markets – risk-adjusted performance vs. diversification

  • Trend strategy performance – how does time-series momentum perform across markets and asset classes?
  • Trader behavior – how are traders, especially smaller ones, evaluating the merits of trend strategies across markets?
  • More than meets the eye – why trend strategies can offer significant portfolio diversification benefits despite seemingly unattractive risk-adjusted performance 
Automated Trading & HPC

Fixed income revolution – how can the buy-side make a seamless transition to an electronic marketplace?

  • Drivers of change – regulation, higher capital requirements for banks, illiquidity, technological innovation, increasing institutional investor appetite for data-driven insights
  • New electronic platforms – are all-to-all trading platforms a panacea for bond market illiquidity? 
  • HFT & fixed income – are HFTs valuable liquidity providers?
  • Analytics, TCA & best execution – capitalizing on newly available order book and market data to enhance operational efficiency and lower costs
  • Deregulation – how, if at all, will any efforts by the Trump administration to undo many of the restrictions mandated via Dodd-Frank, impact the evolution of fixed income market structure?
  • Learning from history – what lessons from other asset classes, particularly equities, should be heeded during this crucial transformational period for the fixed income market?
round tables


  • Alternative data – using non-traditional sources to harvest trading signals
  • Howard Getson

    Howard Getson, CEO, Capitalogix Trading

  • Anomaly detection – how to detect outliers in financial datasets
  • Beyond Bitcoin – evaluating trading opportunities in the growing cryptocurrency market
  • Complex data sets – new mining approaches and efficient strategies for improving data discovery, utility & sustainability
  • Jacob Lee

    Jacob Lee, Director, Kinetica

  • Emerging managers – how are allocators evaluating hedge fund investments in the age of the algorithm?
  • Michael Oliver Weinberg, CFA

    Michael Oliver Weinberg, CFA, Partner & Chief Investment Strategist, Protégé Partners

  • Enterprise data management – new tools and technologies for managing the information cycle
  • Fear gauge flatline - how to overcome low volatility in the post-election era
  • Derek Wang

    Derek Wang, CEO, Bell Curve Capital

  • Fixed income leaders – making a seamless transition to an electronic, data-driven marketplace
  • Michael Koegler

    Michael Koegler, Principal, Viable Mkts

  • 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

  • The art & science of backtesting – war stories and best practices
  • Bert Mouler

    Bert Mouler, President & CEO, Profluent Capital


    Networking Lunch

    Quant World & Big Data in Finance

    Correlated volatility shocks

    • Why commonality in idiosyncratic volatility cannot be completely explained by time-varying volatility
    • How the Dynamic Factor Correlation (DFC) model captures the cross-sectional correlations in idiosyncratic volatility innovations via decomposing the common factor in idiosyncratic volatility (CIV) into the volatility innovation factor (VIN) and time-varying volatility factor (TVV)
    • How a strategy that takes a long position in the portfolio with the lowest VIN and TVV betas, and short position in the portfolio with the highest VIN and TVV betas, earns an average of 8.0% annual returns
    Automated Trading & HPC

    High-performance hardware – how should trading firms approach FPGAs, acceleration technologies and latency management tools?

    • 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
    Quant World & Big Data in Finance

    Fact & fiction in quantitative trading, big data and machine learning

    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 non-traditional 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

    Spotlighting ‘RegTech’ – how can cutting-edge technology transform GRC (governance, risk and compliance) from a back-office burden into an enterprise opportunity?

    • Real-time risk – how much hidden value exists in real-time risk data, and how can you unlock it to maximize operational efficiency?
    • Automating the back office – leveraging the power of data analytics, cloud computing and machine learning to cut costs and enhance regulatory compliance 
    • Regulatory change management – how are trading firms, banks and funds maximizing GRC technology to keep up with the flood of regulatory changes and revisions? How are firms conquering the challenge of integrating RegTech solutions across legacy systems and infrastructure? 
    • Innovation through collaboration – how can market regulators, financial institutions, technology vendors and other key stakeholders in the RegTech ecosystem work together to promote industry standards, seamless systems integration and innovation? 

    Afternoon Networking Break

    Quant World & Big Data in Finance

    AI in trading & investing –  debating the risks, rewards and reality of robo-advisors and artificial intelligence in capital markets

    • AI & your investment strategy – the advantages and disadvantages of trading on probability and using AI to enhance your investment strategy
    • Markets for machines – how will increased usage of machine learning & AI alter market dynamics? 
    • Fiduciary rule fallout – how the new financial investment rules for advisors to act in their clients’ best interest impact robo-advisors?
    • AI-associated risks – what risks should financial firms be aware of as smart machines become more fundamental in modern markets? Do the biggest risks lie in man’s misuse of technology or machine learning techniques themselves?  
    Automated Trading & HPC

    The alpha of trade performance – how to harness the power of real-time TCA to lower execution costs, optimize trading algorithms and predict market behavior 

    • How must quant funds, trading firms, asset managers and banks adjust to decaying alpha, tighter spreads, thinner margins and increased risk aversion when implementing a market data strategy?
    • Performance measurement solutions for post-trade, intra-day and real-time cost analysis 
    • Capturing, cleansing, storing & analyzing cross-asset & cross-geography data for alpha discovery in turbulent market conditions
    • Vendor relationships – the build vs. buy puzzle and working with your provider to improve performance, capacity and cost efficiency
    • Real-time insights – how can traders use visualization technology to aid in real-time pattern discovery and outlier detection?
    • Real-time pattern detection – how to use low-latency, complex event processing (CEP) technology to interpret live data streams
    Quant World & Big Data in Finance

    Passive aggressive – what’s next for active management amidst the seismic investor shift into ETFs & index funds? 

    • Cost factor – should the timeless passive vs. active debate be recast as high vs. low-cost investing?
    • Compensation structure – is the 2 & 20 fee structure officially extinct?  What other viable compensation structures could replace it? 
    • Regulation & consolidation – should we expect margin compression and increasing regulatory burdens to bring more consolidation to the asset management industry?
    • Passive investing bubble? Are falling correlations between assets an early indicator of an imminent passive investing bubble bursting? Will such a bubble ultimately create a fertile environment for an active management comeback? 
    • Dead, dying or evolving? Have robo-advisors, smart beta funds and other FinTech/InvestTech innovations already sounded the death knell for traditional forms of active management? If so, how will active management be defined in the future? Will the systematic methods employed by quants evolve to replace the elements of human intuition? 
    Automated Trading & HPC

    The quest for ‘best ex’ – how are buy-side firms enhancing execution quality amidst changing market dynamics? 

    • Buy-side control – what is driving buy-side firms to seek more power in the execution process? 
    • Cross-asset market microstructure – how are Reg NMS and MiFID changing firms’ approach to sourcing liquidity? Has regulation ultimately improved or hindered execution?
    • Execution strategy – how are firms deploying algorithms in both dark and lit venues to locate the best price with minimal price leakage? 
    • Broker innovation – how can savvy brokers evolve strategies and differentiate algorithms to meet buy-side demands?
    • Clearing & settlement – settlement services for securities lending transactions? what is the importance of central counterparty clearing and 
    • Institutional vs. technical – how do execution needs differ?  
    • TCA & analytics – real-time analytics solutions to improve order routing and enhance execution quality
    Panel discussion

    HFT paradigm shift – evaluating the evolution and survival of high-speed trading 

    • HFT phase 3 – as higher technology costs and diminishing returns continue to make pure market structure and latency arbitrage untenable, how is the high-frequency trading (HFT) industry pivoting to more of an “alpha” focus?
    • Permanent mark – how has HFT permanently changed the nuts and bolts of the capital markets ecosystem?  
    • Perceptions & misconceptions – how do definitions and perceptions of HFT differ between institutional investors, exchanges, latency-sensitive trading firms, regulators and the lay public? 
    • Education & collaboration – how can trading firms, institutional investors, exchanges and regulators come together to educate stakeholders on the role of HFT in the larger trading ecosystem and foster trust in the integrity of modern markets?
    • Opening the black box – can proprietary trading firms afford to remain cloaked in secrecy at the expense of public education? 

    Chairman's Closing Remarks & Networking Cocktail Party

    last published: 20/Jun/17 14:25 GMT