External Data Conference
External Data Conference
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External Data Conference 2019 Trailer
EXDC is the world’s first external data annual conference bringing together leading minds in finance, business, media and sustainability to discuss the real-world use cases for alternative data.
The first edition of EXDC took place at the Times Center NYC on Nov. 5th and featured 30 speakers from Goldman Sachs, UBS, 500startups, The Wall Street Journal, Business Insider, Bank of America, Greenpeace, Alliance Bernstein, Adweek, Cornell University, USAFacts, NYU, The Pudding and more. Learn more at
www.externaldataconference.com
Topics include machine learning, ESG, labor markets, product & retail trends, competitive intelligence, future of news and open data.
Want to join our next event? Stay tuned for EXDC 2020:
www.externaldataconference.com/2020
LinkedIn:
www.linkedin.com/company/externaldataconference/
www.linkedin.com/company/thinknum/
Facebook:
thinknum/
Twitter:
Thinknum
ThinknumMedia
Stay tuned for EXDC Annual 2020:
www.externaldataconference.com/2020
มุมมอง: 91

วีดีโอ

External Data Conference | Financial Transparency Act - Fireside Chat | New York 2019
มุมมอง 1235 ปีที่แล้ว
Richard Berner (NYU), Justin Zhen (Thinknum and Nick Hart (Data Coalition) joined our Government Panel to discuss the FTA and open data policies. EXDC is the world’s first annual conference bringing together leading minds in finance, business, media and sustainability to discuss the real-world use cases for alternative data. The first edition of EXDC took place at the Times Center NYC on Nov. 5...
External Data Conference | Media Panel - Why Your Data Sucks? | New York 2019
มุมมอง 3155 ปีที่แล้ว
Shoshana Wodinsky (AdWeek), Thornton McEnery (Dealbreaker), Ben Gilbert (Business Insider) and Ross Fadely (Wall Street Journal) joined us for our Media Panel at External Data Conference to discuss how they use data for reporting and what makes data “good”. EXDC is the world’s first annual conference bringing together leading minds in finance, business, media and sustainability to discuss the r...
External Data Conference | Interview with Poppy MacDonald from USAFacts | New York 2019
มุมมอง 3795 ปีที่แล้ว
Poppy MacDonald of USAFacts joined Thinknum Media finance editor Jon Marino on stage to share insights on how USAFacts brings government data within reach of US nation. Read more about EXDC at Thinknum Media: media.thinknum.com/articles/exdc-usafacts-poppy-macdonald-enhances-journalists-work-through-data/ EXDC is the world’s first annual conference bringing together leading minds in finance, bu...
External Data Conference | The End of Healthcare AI - Kevin Maney | New York 2019
มุมมอง 1495 ปีที่แล้ว
Kevin Maney delivers an inspiring keynote presentation on "The End of Healthcare: AI and the Creation of Health Assurance". Kevin Maney is the author of NY Times Best Sellers "Unscaled" and "Play Bigger" and founding partner of Category Design Advisors. He has been a contributor of notable publications such as Fortune, The Atlantic, Fast Company and ABC News, among other media outlets. For 22 y...
External Data Conference | ESG The Shift in Consumer, Business and Investor Behavior | New York 2019
มุมมอง 3835 ปีที่แล้ว
Investors are increasingly facing difficult choices and are being pressed with challenging questions from limited partners - how are the deals you're making, making the world a better place? Thinknum Chief Growth Officer Marta Lopata hosted our panel focused on ESG - environmental, social, and governance investing - bringing together some of the top minds overseeing a growing asset class on Wal...
External Data Conference | Shared Economy at Scale Panel | New York 2019
มุมมอง 1315 ปีที่แล้ว
At EXDC, Thinknum's first External Data Conference, Revel's Paul Suhey and LiquidSpace's Mark Gilbreath each offered their respective visions for the next ten years when it comes to how the shared economy will change the way humans think about ownership and access to everything from transportation, to living spaces, to workspaces. Read more here: media.thinknum.com/articles/exdc-our-future-depe...
External Data Conference | Ten Financial Applications of Machine Learning | Marcos Lopez de Prado
มุมมอง 19K5 ปีที่แล้ว
Marcos delivered an inspiring keynote presentation on "Ten Financial Applications of Machine Learning" at EXDC2019. Marcos López de Prado is the CIO of True Positive Technologies (TPT), and professor of practice at Cornell University's School of Engineering. He has over 20 years of experience developing investment strategies with the help of machine learning algorithms and supercomputers. EXDC ...
External Data Conference | How Venture Capital and Private Equity Firms Use External Data | NY, 2019
มุมมอง 3235 ปีที่แล้ว
Alessio Fanelli (645 Ventures), Amit Bhatti (500 Startups), Rebecca Yu (BelHealth Investment Partners) and John Biggs (former TechCrunch) shared their perspectives on the applications of external data for venture capital and private equity firms. EXDC is the world’s first annual conference bringing together leading minds in finance, business, media and sustainability to discuss the real-world u...
External Data Conference | Telling Stories with Data | Matt Daniels, The Pudding | New York, 2019
มุมมอง 4265 ปีที่แล้ว
Matt Daniels delivered a captivating keynote speech on "Telling Stories with Data" at the External Data Conference. Read more about the EXDC at Thinknum Media: media.thinknum.com/articles/video-from-exdc-telling-stories-with-data/ EXDC is the world’s first annual conference bringing together leading minds in finance, business, media and sustainability to discuss the real-world use cases for alt...

ความคิดเห็น

  • @emilyemily6246
    @emilyemily6246 ปีที่แล้ว

    Crystal clear presentation. Amazing

  • @Onnti
    @Onnti ปีที่แล้ว

    epic

    • @Onnti
      @Onnti ปีที่แล้ว

      epicx2

  • @tamashbeen6610
    @tamashbeen6610 2 ปีที่แล้ว

    Where is the presentation that Marco is discussing? Can we download it somewhere?

  • @marcogelsomini7655
    @marcogelsomini7655 2 ปีที่แล้ว

    i don't think that statistical approach cannot deal with outliers but yes maybe empirical alghoritms can do better

    • @max0x7ba
      @max0x7ba 2 ปีที่แล้ว

      The empirical results speak for themselves. Your opinion is anti-scientific.

  • @kevinshen3221
    @kevinshen3221 3 ปีที่แล้ว

    this is mind blowing

  • @anindadatta164
    @anindadatta164 3 ปีที่แล้ว

    The video could have divulged the returns and risks generated by leading ML based quant funds over the years and also returns generated by some major trading algos over the years, to bring out theshelf life of specific algos and ability to generate sustained higher sharp ratios.

  • @thuythu1304
    @thuythu1304 3 ปีที่แล้ว

    You try to give the video more brightness it will be great if you do

  • @alrey72
    @alrey72 3 ปีที่แล้ว

    I don't believe in hedging. Why not just lessen the position size if you're not that confident. On some occasions, both the original position and hedge can go against you.

    • @leimococ
      @leimococ 3 ปีที่แล้ว

      Not believing in hedging is like not believing in clouds. It's true that in some occasions position and hedge can go against you; that doesn't invalidate the fact that good hedging strategies will lower the probability of losing by diversifying exposure.

    • @max0x7ba
      @max0x7ba 2 ปีที่แล้ว

      Hedging is based on the scientific method. Your beliefs are irrelevant.

    • @juggernautuci8253
      @juggernautuci8253 ปีที่แล้ว

      Hedging is like the insurance. Your clients may dislike the risk

  • @albertosantangelo6872
    @albertosantangelo6872 3 ปีที่แล้ว

    De Prado's logic: since poor models fit badly I don't use any model. Unfortunately this approach is not going to work when data are not enough to tell you anything close to the truth, e.g. in finance where returns are fat tailed and most observations are just noise

    • @max0x7ba
      @max0x7ba 2 ปีที่แล้ว

      You failed to grasp Marcos' message and the fundamental idea of ensembling.

    • @albertosantangelo6872
      @albertosantangelo6872 2 ปีที่แล้ว

      @@max0x7ba you lack understanding of statistical properties of returns

    • @max0x7ba
      @max0x7ba 2 ปีที่แล้ว

      @@albertosantangelo6872 You said that you don't have enough data and some return distribution has fat tails. And you believe your data is noise. You failed to grasp Marcos' message to maximize recall instead of precision. Recall can be converted to precision by the ensemble model. That's machine learning fundamentals, you statistical genius.

    • @albertosantangelo6872
      @albertosantangelo6872 2 ปีที่แล้ว

      @@max0x7ba study before commenting, eg read Taleb’s book on applied statistics (freely available on arxiv)

    • @max0x7ba
      @max0x7ba 2 ปีที่แล้ว

      @@albertosantangelo6872 You should read his book beyond "fat tails" on the cover.

  • @daryoushmehrtash7601
    @daryoushmehrtash7601 3 ปีที่แล้ว

    The high frequency example of flash crash is classic fat tail. When many algorithm act the same way you get extreme events. Without the common models, their actions would cancel. But if many players come to same conclusion, you get the black swan. Machine learning is causing the extreme events, the black swans, as it correlates activities.

  • @Estrav.Krastvich
    @Estrav.Krastvich 3 ปีที่แล้ว

    Something that you find after tens of scrolls of your monitor after very specific query. Kind of bonus level, here it is ;).

  • @tratkotratkov126
    @tratkotratkov126 3 ปีที่แล้ว

    great presentation !

  • @yourswimpal
    @yourswimpal 3 ปีที่แล้ว

    this is eye opening , very fresh perspective on using ML to tackle one of the toughest challenge - finance .

  • @arkapravabandyopadhyay
    @arkapravabandyopadhyay 4 ปีที่แล้ว

    This is gold. Fantastic crystal clear presentation!!! (y)

  • @TheCheukhin
    @TheCheukhin 5 ปีที่แล้ว

    the problem is that we lack financial market data, especially bearish market data. If the company focuses on HFT, it surely has enough data to deal with regime change. However, for medium-term trading, ML cannot help us to predict regime change because of lacking data.

    • @omegasigma4500
      @omegasigma4500 4 ปีที่แล้ว

      not true due to the existence of alternative data and the opportunity to generate synthetical data

    • @TheCheukhin
      @TheCheukhin 4 ปีที่แล้ว

      @@omegasigma4500 yes, you can find more data. Also, it is easy to overfit a medium term trading strategy

    • @omegasigma4500
      @omegasigma4500 4 ปีที่แล้ว

      @@TheCheukhin did you even watch the video? it's also about avoiding backtest overfitting...

    • @bartenderbob8875
      @bartenderbob8875 4 ปีที่แล้ว

      Not sure what you mean by not enough data. We have nearly 15 years of decent T1 data for all asset classes - a lot of it is free too! Data Quality tends to increase with the year it was collected (aka more gaps, missing data from 2000’s than 2019) Besides, increasing your training set doesn’t necessarily reduce OOS variance.

    • @bartenderbob8875
      @bartenderbob8875 4 ปีที่แล้ว

      Omega Sigma is right. We can easily create synthetic data sets that is seeded from historical data to fill in gaps or simply create more similar data. Just read the scikit-learn documentation on it

  • @Sebastian-qq9tt
    @Sebastian-qq9tt 5 ปีที่แล้ว

    Keep up the good work. I really think that you deserve more views! Did you ever look into using smzeus . c o m?? You should use it, it will help you get the views that you deserve!!!

  • @AceHardy
    @AceHardy 5 ปีที่แล้ว

    🙏