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on Islamic Finance |
| By: | , Arys |
| Abstract: | The capital market is a financial market for long-term funds. The Islamic Capital Market is all activities in the capital market that do not conflict with Islamic principles. The Indonesian Islamic capital market is part of the Islamic financial industry which is regulated by the Financial Services Authority (OJK), particularly the Islamic capital market directorate. This article describes the history of the capital market, risks and investment strategies in the capital market. |
| Date: | 2022–12–19 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:4bmp9&r=isf |
| By: | Nanaeva, Zhamal; Aysan, Ahmet Faruk; Shirazi, Nasim Shah |
| Abstract: | Rapid developments and the adoption of financial technologies (Fintech) lead to radical changes in the delivery of financial services, including enabling fast payment systems. The recent Covid-19 pandemic catalyzed these processes, while Open Banking supports their further advancement. The concept of Open Banking is gaining global recognition for integrating innovative financial service providers into the sustainable financial ecosystem. This paper discusses Open Banking, including its core building blocks, prospects, and challenges. Given the European Union's pioneering role in adopting Open Banking regulations, the paper also reviews the revised Payment Services Directive (PSD2) and its role in advancing the European fast payment systems. Furthermore, the paper analyzes the practical implications of the PSD2 in Germany by reviewing the examples of the banking-as-a-service platform and the Islamic digital bank, Solarisbank and Insha, respectively. Finally, the paper sheds light on the benefits of Open Banking for ecosystem stakeholders, including fast payment system providers, and what they can derive from the introduction of Open Banking regulations. |
| Keywords: | Open Banking, PSD2, Fintechs, Payment Services, Insha, Solarisbank |
| JEL: | E49 G19 O35 P16 Q01 |
| Date: | 2021–10–31 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:110763&r=isf |
| By: | Hoang, Daniel; Wiegratz, Kevin |
| Abstract: | We study how researchers can apply machine learning (ML) methods in finance. We first establish that the two major categories of ML (supervised and unsupervised learning) address fundamentally different problems than traditional econometric approaches. Then, we review the current state of research on ML in finance and identify three archetypes of applications: i) the construction of superior and novel measures, ii) the reduction of prediction error, and iii) the extension of the standard econometric toolset. With this taxonomy, we give an outlook on potential future directions for both researchers and practitioners. Our results suggest large benefits of ML methods compared to traditional approaches and indicate that ML holds great potential for future research in finance. |
| Keywords: | Machine Learning, Artificial Intelligence, Big Data |
| JEL: | C45 G00 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:kitwps:158&r=isf |