Neural Networks for Financial Risk Assessment in Investment Strategies

Abstract

Financial risk assessment plays a critical role in investment strategies, as it helps investors make informed decisions by identifying and mitigating potential risks. Neural networks have emerged as powerful tools in financial risk assessment, leveraging complex data patterns to predict market trends, identify risks, and optimize investment portfolios. This article explores the applications of neural networks in financial risk assessment, focusing on their use in market prediction, credit scoring, and portfolio optimization. It also discusses the challenges, limitations, and future directions for using neural networks in financial decision-making.