2016 Agenda 

09:00 Big data and machine learning in investment management

  • Opportunities and challenges for applying news, satellite image, social media and other unstructured data sources into the investment process
  • Comparing the pros and cons of machine learning techniques in global stock selection models 
  • How to capitalize on the diversification benefits created by big data and machine learning
Panel discussion

09:30  FinTech and InvestTech – navigating Canada’s opportunity for global leadership

  • With the FinTech movement almost exclusively targeting consumer-level products, what disruptive opportunities are on the horizon for institutions? 
  • What tools and technologies could drive efficiencies in capital allocation?  
  • Artificial intelligence and machine learning – as autonomous machines take on a larger role in the investment process, how can the industry address potential issues surrounding trust, accountability and fiduciary responsibility? 
  • Democratization, dissemination and disintermediation of data – how can innovation in the way information is controlled, accessed and analyzed empower institutional investors? 
  • Is Canada’s growing but undeveloped private sector venture capital market equipped to propel the country into a global hub for FinTech innovation?
  • How can Canada’s vast network of global banking resources help stimulate productivity and competition? 
  • How can government lobbying efforts help startups in Canada’s innovation sector achieve global scale and commercialization?
John MacKinlay,   Special Advisor,  OMERS Platform Investments
Panel discussion

11:10  Investing in IT – how are innovative Canadian firms using their technology dollars to drive efficiency and performance?

  • How can you develop a framework for measuring ROI on tech spend, and how does human capital factor into this equation?
  • Build vs. buy vs. XaaS – what are you outsourcing and what are you building in-house? What is your comfort level in outsourcing?
  • How is your firm handling discretionary spending across data storage, cloud infrastructure, connectivity and other IT initiatives?
  • Separating hype from hope in disruptive tech – distributed ledger, cryptocurrencies, Hadoop, Spark and data and analytics platforms, parallel computing, artificial intelligence and machine learning
  • Cybersecurity and network protection – how much can you solve with a purchase order?
Moderator:   Madaliso Mulaisho,   VP, Quanititave Trader/Researcher,  Algorithmic Trading Firm
Paul Neo,   Director, Enterprise Architecture,  Scotiabank
11:50  Finding alpha in the real estate sector – what works?
  • With the recent separation of REITs (real estate investment trust) from the financial sector, what are the most effective metrics for evaluating REIT investments?
  • Are traditional means of asset valuation, such as dividend yield and book-to-price ratio, less reliable indicators of REIT value than other, less-conventional valuation metrics?
  • What impact does the level and direction of analyst consensus price target have on REITs?
  • During a rising rate environment, do NAVP and Analyst Upside prove to be key indicators?
Panel discussion

12:10  Market structure, liquidity and regulation – what’s on the minds of Canadian traders and investors heading into 2017?

  • What do the trends of decreasing capital commitment and increased electronic trading mean for the future of Canadian markets? 
  • Dark pools, block trading and the Canadian regulatory landscape – are key stakeholders making progress in achieving effective oversight of unlit venues? 
  • Brexit and other geopolitical events – what are the implications for Canadian capital markets?
  • 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?

14:00  A new framework to evaluate the performance of your portfolio of hedge fund managers

  • Introduction: what was the original idea behind the paper?
  • How do hedge fund investors assess the performance of their portfolios?
  • The MMB framework
  • Application to evaluate portfolio construction methodologies for a portfolio of managed futures managers
  • Application to evaluate the value add of managed futures to the traditional 60/40 portfolio
Panel discussion

14:30  Shifting tides in asset allocation – should Canadian investors ride it out with reeling hedge funds?

  • Exiting U.S. pensions  – with recent high-profile hedge fund divestitures by CALPERS and NYCERS, will Canadian allocators follow suit? 
  • Rise of ETFs –  do smart beta funds, robo-advisors and other low-cost actively managed vehicles present more attractive options for institutional investors in Canada’s rapidly growing ETF marketplace?
  • Compensation structure  – is it time to re-think the long-held 2 & 20 fee structure? What alternative models could realistically replace it? How does the performance of Canadian hedge funds compare with U.S. counterparts?
  • Next move for hedge funds  – how will savvy hedge funds adapt and respond to unprecedented adversity? Has the explosive growth of smart beta and enhanced indexing made lower fees imminent, or can hedge funds still offer superior, non-replicable performance commensurate of high fees?
Panel discussion

15:10  How can funds leverage non-traditional data sources to drive investment returns?

  • Nascent data – how will data from nanosatellites, drone imagery, Internet of Things and other emerging data sources be applied to capture alpha?
  • How do you go about making the decision whether to invest in “rare” data sources?
  • Is the novelty of a data set the most important factor when determining its usefulness?
  • What do recent innovations in computing mean for achieving an information edge in the big data ecosystem?
  • Data access vs. human capital vs. compute – striking the right balance
15:50  Asset pricing research - a driving force for automated platform development
  • How our growing understanding of "alpha" and goal-based management are transforming the financial industry 
  • The implications for product development tools
  • The implications for institutional robo-advisors


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.
  • Blockchain – a crash course on distributed ledger technology and the potential use cases for Canadian capital markets

Virgile Rostand, PhD, Founder & Managing Director, CoinSquare

  • Cybersecurity – what should quants and traders know about protecting their digital assets?

Arsen Shirokov, Director, Information Security Strategy, CIBC

  • Non-traditional data – how to leverage emerging unstructured data sources for alpha generation

Dr Ernest Chan, Principal,  QTS Capital Management

  • Rise of the robo-advisors – threat or opportunity for traditional asset management?

Randy Cass, Founder,  Nest Wealth

  • Socially responsible investing – how can you incorporate ESG (environmental, social, governance) without sacrificing returns?

Branimir Kralj, CFA, Financial Technologist, Independent

  • Unconventional data and machine learning – applications for global stock selection models

Yin Luo, Vice Chairman,  Wolfe Research, LLC

17:20  Perspectives from an original disruptor – why unconventional times call for unconventional leadership

Peter Aceto, President & CEO,  Tangerine Bank
17:50 Chairperson Closing Remarks & Networking Cocktail Party