Published: Jan. 1, 2023
This research paper introduces an innovative methodology for predicting mutual fund prices in the Indian financial market by utilizing a hybrid ensemble learning technique based on Stacking Regressor algorithm. Conventional forecasting techniques frequently face difficulties capturing intricate non-linear connections and interdependencies found within data. To tackle this problem, suggested solution is introduction of framework that harnesses collective capabilities multiple base learners to enhance prediction accuracy. The approach consists two main components: meta-learner. Experimental evaluations are conducted using comprehensive dataset market. proposed compares well with traditional single-model other methods. Ridge used as meta-regressor stacking-regressor model. results demonstrate stacking regression-based achieves superior predictive performance relation precision, resilience, consistency. successfully varied viewpoints learners, enhancing overall precision predictions compared standalone models. outcomes study make valuable contribution domain price forecasting, emphasizing potential advantages employing methods presents promising opportunity investors institutions improve their decision-making processes, optimize portfolio management strategies, mitigate risks associated investments.This
Language: Английский
