Algorithmic Approaches to Financial Technology: Forecasting, Trading, and Forecasting

Algorithmic Approaches to Financial Technology: Forecasting, Trading, and Forecasting

Copyright: © 2024 |Pages: 32
DOI: 10.4018/979-8-3693-3264-1.ch003
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Abstract

The purpose of this study is to investigate and analyze the role of algorithmic approaches in financial technology, specifically focusing on their impact on forecasting, trading, and overall decision-making within the financial sector. It seeks to assess how these algorithms enhance efficiency, mitigate risks, and contribute to innovation in financial practices. Additionally, the study aims to provide practical insights and recommendations for professionals while addressing ethical considerations in algorithmic finance.
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Role Of Fintech In Revolutionizing Financial Markets

A disruptive force in the financial sector, financial technology, or FinTech, is altering established financial markets and business models (Gai, Qiu, and Sun, 2018). The impact of fintech is extensive, touching many facets of financial markets and services. FinTech has played a number of important roles in this change, such as:

  • Enhanced Customer Experience: According to Huang and Wang (2018), FinTech companies have made it simpler for users to obtain and administer financial services by introducing user-friendly digital interfaces. The preferred channels for banking, investing, and payment transactions are now mobile apps and internet platforms (Arner et al., 2016).

  • Enhanced Efficiency and Cost Savings: Operational costs have been greatly lowered as a result of automation and digitization of financial procedures (Yermack, 2017). In order to reduce intermediaries and simplify settlement and clearance procedures, blockchain technology, a type of FinTech, has the potential (Gomber et al., 2018).

  • Financial Inclusion: FinTech innovations have increased financial inclusion by extending financial services to underserved people (Demirgüç-Kunt et al., 2018). For people living in areas with a dearth of traditional banking infrastructure, mobile banking, and digital wallets offer access to financial products (Makridakis and Nikolopoulos, 2018).

  • Alternative Lending Models: According to Morgan et al. (2018), peer-to-peer lending platforms and algorithm-based credit assessments have upended traditional lending. These platforms offer more accessible and frequently less expensive financing options by putting borrowers and investors in direct contact (Yin et al., 2018).

  • Algorithmic Trading and Investment: According to Chaboud et al. (2014), robo-advisors and algorithmic trading powered by FinTech both use automated investment strategies. For retail investors, these technologies enhance investment choices and offer cost-effective investment solutions (Avery et al., 2017).

  • Blockchain and cryptocurrencies: According to Catalini and Gans (2018), cryptocurrencies have posed a threat to established financial systems and created new asset classes. Financial transactions could become more secure and transparent thanks to blockchain technology (Mougayar, 2016).

  • Regulatory Compliance and Reporting: To assist institutions in complying with complicated regulations, regulatory technology (RegTech) solutions have arisen (Böhme et al., 2015). By automating regulatory procedures, these technologies lower the cost of compliance (BIS, 2017).

  • Data Analytics and Risk Assessment: To understand customer behavior and evaluate risk, FinTech uses big data and sophisticated analytics (Lo, 2018). According to Bhattacharya and Khandelwal (2016), data-driven decision-making improves risk management and product development.

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