AGENTIC ARTIFICIAL INTELLIGENCE FOR STOCK MARKET DIRECTION PREDICTION: A MACHINE LEARNING FRAMEWORK USING TECHNICAL INDICATORS AND FINANCIAL TIME-SERIES ANALYSIS

Abstract

This paper proposes an agentic AI System to predict stock market direction via machine learning and technicalindicators on financial time-series data. It incorporates a model adaptive selection technique for enhancing themodel performance in forecasting. Prompt: AI-backed stock prediction and forecasting systems rely on sophisticated algorithms and machine learning to analyze market trends and make informed investment decisions.