Utilizing Large-Scale Data Analysis in Finance Management

Utilizing Large-Scale Data Analysis in Finance Management

Kola Anjana Devi, Ayush Khairnar, Prasad Prashant Kulkarni, Mridul Nawale, Muhammed Aflah, Bhavin Motwani, Sumedh Vilas Savalapurkar,  M Vedansh Reddy

Abstract

We investigate the application of machine learning (ML) methods in finance research. We begin by emphasizing a key differentiation: supervised and unsupervised learning, the main ML categories, confront unique challenges compared to conventional econometric techniques. Next, we explore the current landscape of ML usage in finance, identifying three primary areas: (i) the development of more sophisticated and original metrics, (ii) the reduction of predictive inaccuracies, and (iii) the augmentation of the established econometric toolkit. By categorizing these applications in this manner, we offer insights into potential future directions for both researchers and practitioners. Our discoveries underscore the numerous benefits of ML methodologies compared to traditional methods, highlighting the significant potential of ML in shaping the trajectory of financial research.