RCML: A Novel Algorithm for Regressing Price Movement during Commodity Futures Stress Testing Based on Machine Learning is a research paper published by MDPI indicating a major advancement in using machine learning algorithms for the purpose of predicting future price movement in commodity futures stress testing. The algorithm is based on a combination of linear regression techniques, deep learning models, various statistical analysis, as well as market data and risk assessment. Researchers from MDPI have developed this algorithm and present its detailed implementation, validation and results in this paper.
MDPI (Multidisciplinary Digital Publishing Institute) is an open access publisher of peer-reviewed journals that are dedicated to providing free access to scientific research. Established in 1996, MDPI believes in knowledge-sharing and encourages its authors to publish in open access journals. Their portfolio currently consists of over 200 journals that cover a broad range of scientific disciplines including life, physical, and social sciences, technology, and medicine.
The algorithm was developed by Professor Heiko Pawletta who is an experienced researcher in the field of machine learning. Heiko is currently a Research Professor at the Machine Learning Group of the University of Mannheim in Germany. His research focuses on artificial intelligence (AI), data mining, robotics, natural language processing, and deep learning.
