Machine Learning is considered as a subfield of Artificial Intelligence and it is concerned with the development of techniques and methods which enable the computer to learn. In this paper introduce SVM. It is techniques and methodologies developed for machine learning tasks Support vector machines (SVMs) are a set of related supervised learning methods used for classification and regression. S...

We investigate several statistical properties of the order book of three liquid stocks of the Paris Bourse. The results are to a large degree independent of the stock studied. The most interesting features concern (i) the statistics of incoming limit order prices, which follows a power-law around the current price with a diverging mean; and (ii) the humped shape of the average order book, which...

The study aims to conduct a comparative analysis of the legal regulation use artificial intelligence in financial services market. research was carried out based on empirical methods comparison, description, interpretation, and theoretical formal dialectical logic. Particular scientific were used: legal-dogmatic method interpreting norms. market is currently expanding access finance. At same ti...

The output of innovation achievements artificial intelligence enterprises cannot be achieved without the support capital, and financial leasing is playing a positive role in meeting capital needs solving financing difficulties. Based on data AI A-share listed China from 2007 to 2020, this thesis constructs A fixed effects model make an empirical analysis relationship between enterprises' achiev...

Abstract This article analyzes the implications of financial sector’s recent adoption artificial intelligence (AI) and machine learning (ML). It identifies advantages these technologies in terms fraud protection, cost savings, efficiency, while also highlighting worries about conventional institutions’, such as banks, insurance reinsurance institutions, inability to compete with Fintech firms. ...

The purpose of the study was to systematically map Artificial Intelligence (AI) in financial sector VUCA era. research design employed a quantitative approach with descriptive method. utilized systematic literature review bibliometric analysis techniques. Researchers collected data from Google Scholar database, technique using VOSviewer, and statistics as results indicated following: (RQ1) 539 ...

This thesis focuses on applications of Computational Intelligence techniques to Finance and Economics. First of all, we build upon a Genetic Programming (GP)-based financial forecasting tool called Evolutionary Dynamic Data Investment Evaluator (EDDIE), which was developed, and reported on in the past, by researchers at the University of Essex. The novelty of the new version we present, which w...

Machine learning is the core of artificial intelligence. It is a fundamental way to the computer intelligence. Support vector machine is one of the important methods in the field of machine learning. It has the advantages of global optimization and strong generalization ability. It has been successfully applied to face recognition, fault diagnosis, financial forecasting and other fields. In thi...