Comparison of statistical and machine learning methods for prediction LME metal prices
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Abstract (EN)
It is intended to provide a comprehensive analysis of the daily zinc prices around the world in the wake of the Covid-19 pandemic and the impact it has had on global financial zinc markets. Through the implementation of ARIMA modelling on the original zinc prices, we have gained valuable insights into the complex dynamics. According to the results, ARIMA works efficiently when attempting to fit the stationary data than the other models. This study has provided an important contribution to the existing body of knowledge regarding pandemic-related factors in financial markets assessment and strongly highlights the need to integrate such factors into the assessment of these markets as a result of the results of this study. We also apply chaotic time series analysis to the LME zinc data to demonstrate the interaction with chaos theory.
Author
İbrahim Tüfekci
Institution
Piri Reis University
Hesaplamalı Bilim ve Mühendislik Bilim Dalı
How to Cite
İbrahim Tüfekci (Doctorate thesis). Comparison of statistical and machine learning methods for prediction LME metal prices, 2024, Piri Reis University.
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