A Deep Learning Robo-Advisor Framework for Shariah-Compliant Investment into Chinese A-Shares

Abstract

The economic growth of China has led to a growth of investment opportunities in China that has strengthened its collaboration with many Muslim countries. The One-Belt-One-Road initiative has led to growth in bilateral investment with many Muslim countries, requiring the investing Chinese companies to adopt more and more Islamic finance principles. Until recently, Muslim investors had relatively little information and options to invest into the Chinese markets, making the investment potentially impermissible according to Shariah Law. With the growing access provided by Islamic banks to Muslim investors, exchange traded funds incorporating Shariah compliant Chinese A-Share stocks have been set up. For individual investors, determining efficiently which stocks are Shariah compliant remains a considerable challenge and requires extensive manual analysis. Overcoming this challenge, the paper represents a deep learning Robo-advisor prescriptive framework for Shariah compliant investment advice in the Chinese stock market. The performance of the framework was evaluated on recent stock and company financial information, outlining the strong estimation and advisory functionality of the framework. The framework represents an important step towards making high quality Shariah-compliant investment advisory available to a wider audience.