Applications of Machine Learning in Predictive Analysis and Risk Management in Trading

Authors

  • Karthik V Kavin B.Tech Scholar, School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology, Chennai, Tamil Nadu, India Author

Keywords:

Algorithmic Trading, Risk Management, Equity Markets, Portfolio Management, Predictive Analysis, Fundamental Analysis, Value at Risk

Abstract

The stock market is considered the  primary domain of importance in the financial sector where Artificial Intelligence combined with various  algorithmic practices empowers investors with data driven insights, enhancing decision-making, predicting  trends, and optimizing risk management for more  informed and strategic financial outcomes. This research  paper delves into the real-world applications of machine  learning and algorithmic trading, observing their  historical evolution together and how both of these can go  hand in hand to control risk and forecast the movement of  a stock or an index and its future. The research is  structured to provide comprehensive insights into two major subdomains in the application of AI in algorithmic  trading: risk management in equity markets and  predictive analysis of stock trends through the application  of machine learning models and training the current  existing data which is feasible and training them with  respect to historical scenarios of various market trends  along with various fundamental and technical analysis  techniques with the help of various deep learning  algorithms. For risk management of a portfolio in finance,  various machine learning models can be employed,  depending on the specific needs and goals of the portfolio  manager or risk analyst and implementing various value at-risk algorithms along with deep learning techniques in  order to assess risk at particular trade position and to  manage volatile trades at unprecedented situations. The  significance of this research paper lies in its practical  applicability, offering real-world solutions to enhance  trading strategies and decision-making processes with a  focus on mitigating risk and capitalizing on market  opportunities and also giving clear insights with respect  to the current practical limitations of application of the  provided solution and future scope to overcome the same. 

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Published

2023-11-30

Issue

Vol. 11 No. 6 (2023): International Journal of Innovative Research in Computer Science and Technology (Nov) 2023

Section

Articles

How to Cite

Applications of Machine Learning in Predictive Analysis and Risk Management in Trading . (2023). International Journal of Innovative Research in Computer Science & Technology, 11(6), 18–25. Retrieved from https://www.acspublisher.com/journals/index.php/ijircst/article/view/12120