The Conceptual Framework of Applying ML and AI Models to Analyze and Forecast Financial Assets

This article was written by:

Sergey Okun  Sergey Okun – Financial Analyst at I Know First, Ph.D. in Economics.


Eugen KalaidinEugene Kalaidin – Professor, Dept. of Mathematics and Computer science, The Financial University under the Government of the Russian Federation, Ph.D., D. Sci. (Habilitation) in Physics and Mathematics.

Highlights:

  • Knowledge significantly decreases the speculative risk of investment
  • ML and AI technologies allow us to get relevant knowledge about the financial market
  • Information asymmetry is a key factor in getting the arbitrage return
  • Models of nonlinear dynamic systems allow correctly to evaluate financial assets by determining the backbone behavior of assets

premiumRead The Full Premium Article

Subscribe to receive exclusive PREMIUM content here

Trade Smartly in the Fractal Stock Market with Machine Learning Power

motek 1This algorithmic article was written by Yutong Li – Analyst at I Know First, Master's candidate at Brandeis University.

Highlights:

  • Although Efficient Market Hypothesis has been a dominated financial theory for years, it fails to give a sensible reason and interpretation of the financial crashes and crises that occurred
  • A more comprehensive financial theory - Fractal Market Hypothesis is capable to explain these crises and provide a clear-cut description of the financial markets
  • Fractal Market Hypothesis puts forward the idea of self-similarity and stability in the market when it consists of investors from a wide range of investment horizons
  • FMH verifies the root of technical analysis under the idea that history can repeat, and this process of pattern-finding can be efficiently attained by machine learning

premiumRead The Full Premium Article
Subscribe to receive exclusive PREMIUM content here