International Journal on Science and Technology

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OptiVest: An Artificial Intelligence Based PortfolioOptimization and Intelligent Investment DecisionSupport System

Author(s) Mr. Mohit Chandar Shadija, Ms. Maniya Pradeep Motiramani, Mr. Harshit girdhari Sharma, Ms. Harshita Jay Dudani
Country India
Abstract Financial markets are known for their constantfluctuations and uncertainty, which makes the process of makinginvestment decisions quite difficult. Investors often have to dealwith unpredictable market movements, changing economic con-ditions, and various external factors that influence stock prices.Traditional portfolio management methods usually depend onhistorical averages and fixed statistical assumptions. Althoughthese techniques have been widely used for many years, theydo not always reflect the real-time behavior of modern financial markets. Because of these limitations, investors may experience problems such as inadequate diversification, higher exposure tovolatility, and decisions influenced by emotions rather than data.In this research, we introduce OptiVest, an Artificial Intelli-gence (AI) based portfolio optimization and investment decision support system. The proposed system combines deep learningtechniques, particularly Long Short-Term Memory (LSTM) net-works, with the principles of Modern Portfolio Theory (MPT)to generate more effective asset allocation strategies. OptiVestperforms several important tasks including collecting financial data, preparing and preprocessing the data, predicting futuretrends, optimizing portfolio weights, and presenting the resultsthrough visual analytics. The experimental evaluation showsthat the proposed system can achieve improved risk-adjustedreturns when compared with traditional portfolio construction approaches. The overall objective of this framework is to provideinvestors, especially retail investors, with a more transparent,practical, and data-driven way to make informed investmentdecisions.
Field Engineering
Published In Volume 17, Issue 2, April-June 2026
Published On 2026-04-29
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