Hedge Funds Draw on Big Data Advantage

Published on
April 17th, 2017
Topic
Technology, Business Strategy, Trading
Duration
41 minutes
Asset class
Equities

Hedge Funds Draw on Big Data Advantage

The Interview ·
Featuring Tammer Kamel

Published on: April 17th, 2017 • Duration: 41 minutes • Asset Class: Equities • Topic: Technology, Business Strategy, Trading

Tammer Kamel provides the information advantage to quants by mining Big Data for hedge funds, in a world starved of alpha. As industries across the spectrum amass vast data banks, from non traditional sources like satellites, actionable insights and signals on all aspects of the global economy can be obtained, while the alternative data opportunity combined with artificial intelligence is producing an entirely new breed of data driven hedge funds. Filmed on March 28, 2017, in Toronto.

Comments

  • MM
    Michael M.
    17 April 2017 @ 17:19
    I would love to know how they go about backing out their estimates of how much capital can be put behind a particular proprietary data set before the advantage gets arbed out.
  • AT
    Anthony T.
    17 April 2017 @ 19:47
    How does limiting distribution of these data sets such that the advantage does not become arbed away not qualify the information as MNPI?
    • MC
      Michael C.
      18 April 2017 @ 10:05
      I agree. I am not sure how this is different from sitting outside a factory and counting trucks. I always thought that was real research but it does seem to have been deemed MNPI in some jurisdictions (USA I am looking at you).
  • SR
    Steve R.
    18 April 2017 @ 05:17
    Sounded rather like a 45min commercial to me. We've had interviews along these same lines before - didn't really add anything that hasn't already been talked about (IMHO).
    • W
      Łukasz W.
      18 April 2017 @ 10:05
      Same reception. Here. I think it is the interviewer's fault rather than interviewee's. There is a ton of questions which could have been asked. What is the client structure - who pays, who uses just the freebies. What are the most utilized data sources and types. How does Quandl plan to coexist with Bloomberg terminal... Just top of my head. Also - the idea that he plans to offer his product to narrow alpha generating group was left not commented.
  • SF
    Simon F.
    18 April 2017 @ 07:32
    Possibly the most important "signal" was rhe admission by the interviewer at the beginning that he was an early investor. My one problem with RV is the tendancy to not have interviewers that really c
  • SF
    Simon F.
    18 April 2017 @ 07:33
    ...challenge the interviewees.
  • RM
    Robert M.
    23 April 2017 @ 00:29
    Love quandl. A wonderful resource. This was a great backgrounder interview for a fan like me. I use many free tickers to easily update my excel models. They allow 50000 free data calls a day. Will very possibly pay for premium data at some stage. What a great range of data, and always growing. Bravo Tammer and RV.
  • RW
    Raymond W.
    23 April 2017 @ 22:24
    Very interesting.
  • GC
    Grant C.
    29 April 2017 @ 12:42
    I can certainly understand someone spending 50 - 80% of their time wrangling data after studying Udacity's Data Analyst program. Great interview, and yes more and more companies are hiring data scientists. I have noticed mining companies building data science teams.
  • SA
    Scott A.
    23 May 2017 @ 13:32
    As an IT guy with a kid finishing up his PhD in stats I may be biased but I thought it was a great interview. The discussion of the upstream sources, how the data gets priced, and how the landscape would need to change to grow the company were all interesting topics. I did not get the "commercial" feel others did. I'd think whenever you leave the analyst arena and talk to actual company owners you will get some company focus, but I thought it was done well.
  • SA
    Scott A.
    23 May 2017 @ 13:32
    As an IT guy with a kid finishing up his PhD in stats I may be biased but I thought it was a great interview. The discussion of the upstream sources, how the data gets priced, and how the landscape would need to change to grow the company were all interesting topics. I did not get the "commercial" feel others did. I'd think whenever you leave the analyst arena and talk to actual company owners you will get some company focus, but I thought it was done well.
  • MR
    Maximilian R.
    12 December 2017 @ 15:01

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