An LSTM-Driven Decision-Support Framework for Small and Medium-Sized Investors

As economic integration accelerates, small and medium-sized investors, previously regarded as marginal entities, have emerged as central figures in the capital market. Their rise, however, is marred by considerable challenges. The increasing intricacy of the capital market, compounded by their limited investment expertise, often culminates in precarious investment decisions. In response to these challenges, this study introduces an advanced framework designed to augment the investment decision- making capabilities of this demographic. This framework accentuates the enhancement of its effectiveness through the integration of a composite indicator, informed by the LSTM (Long Short-Term Memory) model-an avant-garde machine learning methodology specializing in time-series forecasting. Further, by aligning with the consistent investment methodology encapsulated by the SIP (Systematic Investment Plan) strategy, users can derive bespoke, lucid, and streamlined investment guidance with minimal data input, equipping them to robustly reinforce their financial portfolios amidst a dynamic market.