Our artificial intelligence applications are linked to the analysis of the behavior of the main investors in the financial market through numerical data and through statistical and time series. Unfortunately, artificial intelligence cannot provide predictive capabilities regarding insider trading. The latter are that category of investors who know all the sensitive information that drives all financial instruments. They are those who always make money and who illegally steal a huge part of the profits from the financial markets.

We apply machine learning as a branch of artificial intelligence to create data and information management systems and therefore the set of rules and criteria that guide decisions to buy and sell financial instruments in strategies.

Trading strategies using machine learning can fully exploit the ability of algorithms to analyze large amounts of data, identify trends as set in programming, predict future scenarios, and adapt to market changes based on the parameters set in the strategy.

Consequently, machine learning offers technical advantages for improved operational efficiency but is not a guarantee for the reliability and effectiveness of the algorithms. The latter must be inspired by logical ideas that consider the nature of financial instruments.

Quantal is a professional organization that offers institutional, para-institutional, and professional investors in general IT, technological and artificial intelligence support for the study, analysis and programming of quantitative and algorithmic trading and the structuring of complex financial products. It does not carry out and is not authorized to carry out any asset management or other similar activity, for which specific authorizations from the financial authorities are required. N.B.: when we talk about programming and related coding of orders on trading platforms, it is understood and specified as referring to an IT activity on behalf of third parties and nothing else.