Analyzing and Forecasting Financial Services using Packet Transform through Wavelet Transitions

Financial analysis plays a pivotal role in understanding market trends and making informed investment decisions. This research leverages the power of Wavelet Packet Transform (WPT) to extract valuable insights from financial time series data. By applying WPT to financial data, complex patterns and trends can be uncovered, enabling more accurate forecasting and analysis. The study utilizes Plotly’s interactive line charts to visualize these insights effectively. The proposed approach has demonstrated exceptional performance, achieving an accuracy rate of ${9 9 . 5 \%}$. This high level of accuracy empowers stakeholders and financial advisors to navigate the dynamic financial landscape with greater confidence. By providing deeper insights into market behavior, this research contributes to improved decision-making and risk management in the financial industry.