A portfolio recommendation system based on machine learning and big data analytics

Abstract

<abstract><p>This research paper introduces a portfolio recommendation system that utilizes machine learning and big data analytics to offer a profitable stock portfolio and stock analytics via a web application. The system's effectiveness was evaluated through backtesting and user evaluation studies, which consisted of two parts: user evaluation and performance evaluation. The findings indicate that the development of a machine learning-based portfolio recommendation system and big data analytics can effectively meet the expectations of the majority of users and enhance users' financial knowledge. This study contributes to the growing body of research on utilizing advanced technologies for portfolio recommendation and highlights the potential of machine learning and big data analytics in the financial industry.</p></abstract>

Big data applications in portfolio management: A review of techniques and strategies

“…The impact of big data on portfolio performance is multifaceted, encompassing enhanced predictive analytics, improved risk management, and personalized investment solutions. Leung et al (2023) developed a machine learning-based portfolio recommendation system that leverages big data analytics to provide stock analytics and portfolio recommendations through a web application. Their findings, derived from backtesting and user evaluation studies, indicate that such systems can significantly user expectations and enhance financial knowledge.…”

“…The emergence of machine learning and big data analytics has further propelled the development of portfolio recommendation systems. Leung et al (2023) demonstrate how these technologies can be employed to deliver profitable stock portfolios and enhance financial knowledge among users. Their findings suggest that the integration of advanced analytical tools can significantly improve the effectiveness of portfolio management strategies.…”