A survey of the application of graph-based approaches in stock market analysis and prediction

Abstract

AbstractGraph-based approaches are revolutionizing the analysis of different real-life systems, and the stock market is no exception. Individual stocks and stock market indices are connected, and interesting patterns appear when the stock market is considered as a graph. Researchers are analyzing the stock market using graph-based approaches in recent years, and there is a need to survey those works from multiple perspectives. We discuss the existing graph-based works from five perspectives: (i) stock market graph formulation, (ii) stock market graph filtering, (iii) stock market graph clustering, (iv) stock movement prediction, and (v) portfolio optimization. This study contains a concise description of major techniques and algorithms relevant to graph-based approaches for the stock market.