Krakovsky, A. (2018). Master Equation for Coarse-Time Microscopic Dynamics. AIP Advances, 8, Article ID: 085301.
https://doi.org/10.1063/1.5041379

has been cited by the following article:

• TITLE: Conditionalism as a Methodology of Forecasting, Decision-Making and Machine Learning

  AUTHORS: Andrey Krakovsky

  KEYWORDS: Decision-Making, Machine Learning, Forecasting, Financial Markets

  JOURNAL NAME: Voice of the Publisher, Vol.8 No.1, February 11, 2022

  ABSTRACT: We examine how conditionality inherent to the real-life training data sets influences forecasting and decision-making by analyzing examples that range from behavioral logic to machine learning. For machine learning or other systematic methods, we outline a process-driven approach to better navigate and improve decisions in situations with obscure or difficult to capture conditionality. We outline implementation of these techniques in a portfolio management engine.