Abstract
Sukuks have assumed increasing importance in the global financial industry, with both institutional and retail investors realizing the benefits of Sukuk, both in terms of their adherence to Islamic principles, as well as being more stable and robust. The growing importance of the Sukuk markets has happened simultaneously with the significant development of China. With the financial crisis and other recent events reducing the trust and confidence of investors in the existing financial system structures, Islamic financial products have received great attention due to their connection to real assets and risk-sharing. While Sukuk financial instruments differ significantly from their conventional bond counterparts, pricing has mostly followed conventional bond pricing methodologies. This represents a significant challenge as the characteristics of Sukuk are not considered, misrepresenting the value and associated performance of the Sukuk. An innovative data-driven methodology for the pricing of Sukuk in the Chinese equity market is presented. It overcomes the challenges with conventional bond pricing methodologies applied to Sukuk pricing. The methodology integrates a deep learning framework for the estimation and forecasting of Sukuk prices, considering factors, such as cashflows, net income, and stock price performance, in addition to textual information. Illustrated on thirty major Chinese corporations listed on the Hong Kong Stock Exchange, the framework provides a more market and value-based approach to pricing Sukuk considering the partnership nature of the Islamic financial product.
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