Complex Event Analysis - Report

Key Focus

  • The answer is no, but examining the differences is critical in forming realistic expectations of AI in capital markets.
    With the car, there really is a code to be cracked. The problem largely involves geometry, immutable laws of motion and known roadways
  • Given the success of machine learning in domains involving vision and language, we should not be surprised at exuberant claims or expectations in capital markets as well.
    Having operated systemic machine-learning-based investing programs for two decades, I don't believe there is a code to crack

    • No momentum supporting factor found

    Challenge supporting factors

  • (learning, markets)
  • (capital, markets)
  • (markets, roadways)
  • (laws, markets)

    • Work-in-progress supporting factors

  • (markets, one-minute)
  • (machine-learning-based, markets)
  • (capital, markets)
  • (markets, trading)
  • (intelligence, markets)

    • Complex Event Time Series Summary - REPORT


    Time PeriodChallengeMomentumWIP
    Report43.75 0.00 56.25

    High Level Abstraction (HLA) combined

    High Level Abstraction (HLA)Report
    (1) (capital,markets)100.00
    (2) (markets,one-minute)81.82
    (3) (machine-learning-based,markets)72.73
    (4) (learning,markets)63.64
    (5) (markets,trading)36.36
    (6) (markets,roadways)27.27
    (7) (laws,markets)18.18
    (8) (intelligence,markets)9.09

    Complex Event Analysis - REPORT

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    Supporting narratives:

    • challenge (Read more)
      • ET
        By Vasant Dhar
        Ask these 5 questions before you invest with a machine-learning-based program
        Recent reports suggest that artificial intelligence will "crack the code" of financial markets by using big data and machine learning. Given the success of machine learning in domains involving vision and language, we should not be surprised at exuberant claims or expectations in capital markets as well.
        Having operated systemic machine-learning-based investing programs for two decades, I don't believe there is a code to crack
      • High Level Abstractions:
        • (learning,markets)

    • challenge (Read more)
      • The answer is no, but examining the differences is critical in forming realistic expectations of AI in capital markets.
        With the car, there really is a code to be cracked. The problem largely involves geometry, immutable laws of motion and known roadways
      • High Level Abstractions:
        • (capital,markets)

    • challenge (Read more)
      • The answer is no, but examining the differences is critical in forming realistic expectations of AI in capital markets.
        With the car, there really is a code to be cracked. The problem largely involves geometry, immutable laws of motion and known roadways.
      • High Level Abstractions:
        • (markets,roadways)
        • (laws,markets)

    • WIP (Read more)
      • As described eloquently in the book "Flash Boys," machines are able to learn predictable intraday patterns in the financial markets that arise from the actions of humans and machines. Such data are very dense in the sense that over an eight-hour trading day, the machine has 480 one-minute samples from which to learn to make one-minute predictions.
      • High Level Abstractions:
        • (markets,one-minute)

    • WIP (Read more)
      • ET
        By Vasant Dhar
        Ask these 5 questions before you invest with a machine-learning-based program
        Recent reports suggest that artificial intelligence will "crack the code" of financial markets by using big data and machine learning
      • High Level Abstractions:
        • (machine-learning-based,markets)
        • (intelligence,markets)

    • WIP (Read more)
      • Given the success of machine learning in domains involving vision and language, we should not be surprised at exuberant claims or expectations in capital markets as well.
        Having operated systemic machine-learning-based investing programs for two decades, I don't believe there is a code to crack
      • High Level Abstractions:
        • (capital,markets)

    • WIP (Read more)
      • As described eloquently in the book "Flash Boys," machines are able to learn predictable intraday patterns in the financial markets that arise from the actions of humans and machines. Such data are very dense in the sense that over an eight-hour trading day, the machine has 480 one-minute samples from which to learn to make one-minute predictions
      • High Level Abstractions:
        • (markets,trading)

    Target rule match count: 8.0 Challenge: 0.22 Momentum: 0.00 WIP: 0.28