Simulation of emotional differences in the structured query language for databases of financial markets

Abstract

Subject. The article addresses a simulation in the structured query language (SQL) for the Bloomberg information base, the scientifically grounded tools for measuring emotions in markets in the face of financial and pandemic crisis and market imbalances, in addition to classic financial indicators, the creation of analytical tools based on state-of-the-art software tools that integrate the latest advances in behavioral finance and in financial and coefficient analysis, machine learning technologies, and open financial market data. Objectives. The aim is to create a usable toolkit for balanced evaluation of financial and economic situation of companies, based on the analysis of the main Russian and foreign modern means to measure emotions. Methods. The study employs methods of induction, deduction, and modeling. It demonstrates the link between methods and methodologies with new technical means of modern information systems. Results. The paper studies the effect of the heuristics of insufficient reaction and heuristics of excessive self-confidence, using the examples of market drawdown. I developed and implemented a model, using the behavioral finance tools as a factor in stabilizing financial decisions. Conclusions. New software and hardware tools enabled to identify and measure the actions of the heuristics of financial market participants. Financial analysts, when applying the new capabilities of modern information systems for programming and creating user models with required parameters and extensive database, will have new opportunities in the described models. The procedure for collecting and processing the original information required for valuation is simplified.