Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Data detailed on artificial intelligence have bee n presented. According to news reporting originating from Birmingham, United Kin gdom, by NewsRx correspondents, research stated, “The volatile and nonlinear na ture of stock market data, particularly in the post-pandemic era, poses signific ant challenges for accurate financial forecasting.” Funders for this research include Vc Research; Leverhulme Trust. Our news correspondents obtained a quote from the research from Aston University : “To address these challenges, this research develops advanced deep learning an d machine learning algorithms to predict financial trends, quantify risks, and f orecast stock prices, focusing on the technology sector. Our study seeks to answ er the following question: “Which deep learning and supervised machine learning algorithms are the most accurate and efficient in predicting economic trends and stock market prices, and under what conditions do they perform best?” We focus on two advanced recurrent neural network (RNN) models, long short-term memory (L STM) and Gated Recurrent Unit (GRU), to evaluate their efficiency in predicting technology industry stock prices. Additionally, we integrate statistical methods such as autoregressive integrated moving average (ARIMA) and Facebook Prophet a nd machine learning algorithms like Extreme Gradient Boosting (XGBoost) to enhan ce the robustness of our predictions. Unlike classical statistical algorithms, L STM and GRU models can identify and retain important data sequences, enabling mo re accurate predictions.”
NETL
NSTL