Robo-Sukuk pricing for Chinese equities

Katterbauer, Klemens; Syed, Hassan; Cleenewerck, Laurent; Genç, Sema Yılmaz

doi:10.1016/j.bir.2022.06.002

Cited by 7 publications

(4 citation statements)

References 14 publications

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“…The use of machine learning techniques can be costly, involving large expenditures on staff, technology, and software. The application of machine learning in asset pricing raises ethical questions due to the possibility of prejudice and discrimination in the model's predictions (Katterbauer K. , Syed, Cleenewerck, & Genc, 2022).…”

Section: Methodsmentioning

confidence: 99%

Ai-Driven Capital Asset Pricing Model for Enhancing Shariah-Compliant Investment Decisions – A Chinese Stock Market Analysis

2023

ijibm

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The CAPM makes it possible to estimate prices for specific instruments, like stocks, to project investment returns. As a key element of corporate finance and investment banking, the CAPM investigates the relationship between the level of risk associated with the investment and the inherent risks of the market as a whole. Several assumptions must be used to create the AI-driven mathematical model for Islamic financial assets to achieve the model. The first is that the expected values and standard deviations of the asset's returns are the only factors that influence investors' choices. Additionally, since the zakat and purification are deducted from the anticipated returns, there are no transaction fees. The assets may be marketable and are infinitely divisible in addition. Finally, there is no cap on the amount that may be lent or borrowed at the Sukuk profit rate or other Islamic benchmark rates because all expectations are homogenous. We presented a new AI-driven Islamic CAPM for the estimation of returns for Shariah-compliant A-Shares enterprises. The methodology represents a new AI-driven estimation framework integrated into the Islamic CAPM methodology for the estimation of returns and selection. The methodology was evaluated on an Islamic A-share portfolio, with the stocks being listed on both the Shenzhen and Shanghai stock exchanges. The analysis demonstrates the ability of the methodology to provide Shariah-compliant optimal returns for the stocks and ensure Shariah compliance of the portfolio allocations.

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Section: Methodsmentioning

confidence: 99%

Ai-Driven Capital Asset Pricing Model for Enhancing Shariah-Compliant Investment Decisions – A Chinese Stock Market Analysis

2023

ijibm

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“…Theories from economics, epidemiology, and meteorology can help build these linkages. Multivariate forecasting could also refer to forecasting many variables simultaneously (e.g., econometric models) (Chang et al, 2009;Katterbauer et al, 2022;Sun, 2020).…”

Section: Forecastingmentioning

confidence: 99%

Predicting Shariah Stock Market Indices with Machine Learning: A Cross-Country Case Study

Khairunnisa,

Rodoni,

Rama

2024

JESTT

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Stock prices are influenced by numerous factors, including policy adjustments, economic conditions, and international developments. Consequently, forecasting stock price trends accurately has posed a significant challenge for economists to study. The Islamic financial industry experiences fewer shocks compared to the traditional financial sector, allowing investors to anticipate the performance of Islamic indices. This study aims to predict the Islamic stock market indices in six countries, including Indonesia, Thailand, Malaysia, Pakistan, the United Arab Emirates, and Qatar, using the Autoregressive Integrated Moving Average (ARIMA) model. Monthly data from 2013 to 2023 sourced from investing.com and Yahoo Finance are analyzed using R machine learning. The objective of this study is to provide accurate predictions for the next 25 months and offer insights into potential price movements. Overall, this research also sheds light on the dynamics of the Islamic market in Indonesia, Thailand, Malaysia, Pakistan, the United Arab Emirates, and Qatar, which adhere to the Efficient Market Hypothesis (EMH) due to the predictability of index prices by historical data. Keywords: forecating, R-Studio, ARIMA, Islamic Stock Market, Machine Learning, R-Programming ABSTRAK Harga saham dipengaruhi oleh banyak faktor, termasuk penyesuaian kebijakan, kondisi ekonomi, dan perkembangan internasional. Oleh karena itu, memprediksi tren harga saham dengan akurat telah menjadi tantangan signifikan bagi para ekonom untuk mempelajarinya. Industri keuangan Islam mengalami lebih sedikit goncangan dibandingkan dengan sektor keuangan tradisional, yang memungkinkan investor untuk memperkirakan kinerja indeks Islam. Studi ini bertujuan untuk memprediksi indeks pasar saham Islam di enam negara, termasuk Indonesia, Thailand, Malaysia, Pakistan, Uni Emirat Arab, dan Qatar, menggunakan model Autoregressive Integrated Moving Average (ARIMA). Data bulanan dari tahun 2013 hingga 2023 yang berasal dari investing.com dan Yahoo Finance dianalisis menggunakan pembelajaran mesin R. Tujuan dari studi ini adalah untuk memberikan prediksi yang akurat untuk 25 bulan mendatang dan menawarkan wawasan tentang pergerakan harga yang potensial. Secara keseluruhan, penelitian ini juga memberikan cahaya tentang dinamika pasar Islam di Indonesia, Thailand, Malaysia, Pakistan, Uni Emirat Arab, dan Qatar, yang mengikuti Hipotesis Pasar Efisien (EMH) karena dapat diprediksi oleh data historis.. Kata Kunci: Prediksi, R-Studio, ARIMA, Indeks Pasar Modal Syariah, Machine Learning, R-Programming

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“…Sukuk wakalah is in demand because it provides greater flexibility in its structuring process and as an alternative to address the issue of lack of suitable assets to be used as underlying assets (Katterbauer et al, 2022).…”

Section: Problem Statementmentioning

confidence: 99%

An Overview of Sukuk Liquidity Market Issues in the Shariah Perspective

Sharif,

Redzuan,

Meerangani

et al. 2023

European Proceedings of Finance and Economics

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A sukuk can generally be understood as an investment document or certificate that proves the existence of right for certificate holder to an underlying profit, project or asset. However, there are some obstacles in structuring 'asset-backed' sukuk from a shariah aspect such as the difficulty of changing the name in the underlying asset grant from obligor to sukuk holder, tax issues and implications to 'negative pledge'. This study uses a qualitative approach in which the analysis of the original book of fiqh and a review of past studies by applying the method of content analysis. Content analysis has been defined as a systematic, replicable technique for compressing many words of text into fewer content categories based on explicit rules of coding. The most common notion about the content analysis is simply means doing a wordfrequency count. The assumption made is that the words that are mentioned most often are the words that reflect the greatest concerns. Thus, this study will use the words counting codes from the past literatures to examine the shariah issues that are hurdles to the industry in determining the nature of underlying asset for the sukuk marketability so that the liquidity problems may be resolved.

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Robo-Sukuk pricing for Chinese equities

Cited by 7 publications

References 14 publications

Ai-Driven Capital Asset Pricing Model for Enhancing Shariah-Compliant Investment Decisions – A Chinese Stock Market Analysis

Ai-Driven Capital Asset Pricing Model for Enhancing Shariah-Compliant Investment Decisions – A Chinese Stock Market Analysis

Predicting Shariah Stock Market Indices with Machine Learning: A Cross-Country Case Study

An Overview of Sukuk Liquidity Market Issues in the Shariah Perspective

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