ABSTRACT

This book presents a collection of high-quality contributions on the state-of-the-art in Artificial Intelligence and Big Data analysis as it relates to financial risk management applications. It brings together, in one place, the latest thinking on an emerging topic and includes principles, reviews, examples, and research directions. The book presents numerous specific use-cases throughout, showing practical applications of the concepts discussed. It looks at technologies such as eye movement analysis, data mining or mobile apps and examines how these technologies are applied by financial institutions, and how this affects both the institutions and the market. This work introduces students and aspiring practitioners to the subject of risk management in a structured manner. It is primarily aimed at researchers and students in finance and intelligent big data applications, such as intelligent information systems, smart economics and finance applications, and the internet of things in a marketing environment.

chapter 1|16 pages

Grey model as a tool in dynamic portfolio selection

Simple applications

chapter 4|22 pages

Deep Learning in Detecting Financial Statement Fraud

An Application of Deep Neural Network (DNN)

chapter 5|16 pages

Predicting Stock Return Risk and Volatility Using Neural Network

The Case of the Egyptian Stock Exchange

chapter 7|31 pages

Optimization algorithms for multiple-asset portfolios with machine learning techniques

Theoretical foundations of optimum and coherent economic capital structures

chapter 9|20 pages

The role of blockchain in financial applications

Architecture, benefit, and challenges

chapter 12|35 pages

Optimization algorithms for multiple-asset portfolios with machine learning techniques

Practical applications with forecasting of optimum and coherent economic capital structures