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.


  • 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

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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.


  • 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

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