Efrem Hoffman | CEO
Running Alpha Investments

Efrem Hoffman, CEO, Running Alpha Investments

Founded by Efrem Hoffman, Running Alpha is a Toronto based decision-support platform and prediction analytics think-tank that was born out of the need for: finding smart cuts to optimization and forecasting problems that are currently intractable using classical computing models.

To look ahead whole chunks of the decision optimization space at once, instead of incrementally searching for the next best steps, we built a new class of artificial war-gaming intelligence that harnesses the way nature uses quantum computing principles and gauge symmetries for preserving the survival of the fittest.

Recasting financial market prediction as a quantum computing problem is our first application in this multi-trillion-dollar marketplace. By leveraging this new platform of decision-making, our mission is clear; we are: unlocking value and extending the shelf-life of conventional and alternative data sets; accelerating knowledge discovery under conditions of extreme uncertainty and limited history; and rendering visibility and sensibility into the sentiment perceptions and networking feedback effects of the billions of complex interacting market agents, powering business and economic decisions in world capital markets; thereby, helping investors and corporate decision-makers better allocate their human, machine, and capital resources to the corners of the marketplace that matters for: maximizing alpha creation; profiting from disruptive change; and defending portfolio positions against known and unknown market threats.


Day 1 @ 16:10

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?
  • Choosing the right data – how do you go about making the decision whether to invest in “rare” data sources?
  • Exclusivity, novelty & data processing capability – is one more important than the other when mining for alpha?
  • Package alpha products – are they sustainable? If so, how are vendors offering products accounting for crowding and the resultant decay of the value with time?
  • Compute component – 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 

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