The Dynamic Role of Big Data Analytics in Learning and Development and Its Impact on Risk Analysis in Stock Market

Mary Auxilia P.A.; Alvarado-Tolentino J.; Gonzales-Yanac T.; Huaman-Osorio A.; Durga S.; Hasan M.F. · Smart Innovation, Systems and Technologies (2023) · DOI: 10.1007/978-981-19-0108-9_17

Resumen

Big data analytics is making a paradigm shift in all industries, including banking, financial institutions and stock broking companies. The financial big data analytics (FBDA) is considered as one of the key areas of enhancing the management, governance, performing critical analysis and support the management, regulators and managers to make profound decisions. It is noted that the big data is transforming the finance sector mainly stock market domain in assisting the risk managers and investors to measure the risk in an effective manner so that they can invest in better assets like stocks, bonds, mutual funds, exchange traded funds (ETF) etc. for enhancing the return on investments. Every day there are millions of financial transactions which occur in the financial community around the world, the financial practitioners and risk management analyst need to upgrade their knowledge through continuous learning and focus in analysing the risk efficiently so as to enhance their investment plan and realise the financial goals. The risk management is considered as the systemic modelling which enables in the estimation of the interrelationship amongst the financial institutions, big data applies the major characteristic which is comprised of 4 Vs—Volume, Velocity, Variety and Veracity this enables in analysing the large volume of data available in stock prices, forecast the volatility and manage the risk in an appropriate manner. This paper enables in presenting a conceptual understanding on the dynamic role of big data analytics in learning and development and its impact of risk analysis in stock market, this paper enables in presenting sophisticated methods for risk control based on big data analytics in creating new finance aspects by analysing the overall feelings based on massive textual information from the social networks, apply various technologies in creating ways of estimating risk and enhance their return on investments (ROI).

Instituciones: Universidad Nacional Santiago Antúnez de Mayolo