A Hybrid LMD–ARIMA–Machine Learning Framework for Enhanced Forecasting of Financial Time Series: Evidence from the NASDAQ Composite Index

A Hybrid LMD–ARIMA–Machine Learning Framework for Enhanced Forecasting of Financial Time Series: Evidence from the NASDAQ Composite Index

This study proposes a novel hybrid forecasting approach designed explicitly for long-horizon financial time series. It incorporates LMD (Local Mean Decomposition), SD (Signal Decomposition), and sophisticated machine learning methods. The framework for the NASDAQ Composite Index begins by decomposin...

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Bibliographic Details
Main Authors: Jawaria Nasir, Hasnain Iftikhar, Muhammad Aamir, Paulo Canas Rodrigues, Mohd Ziaur Rehman
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Mathematics
Subjects:
hybrid forecasting models
Local Mean Decomposition
financial time series
Signal Decomposition
XGBoost
forecast accuracy
Online Access:https://www.mdpi.com/2227-7390/13/15/2389
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