Cargando…
Application of Supervised Machine Learning Techniques to Forecast the COVID-19 U.S. Recession and Stock Market Crash
Machine learning (ML), a transformational technology, has been successfully applied to forecasting events down the road. This paper demonstrates that supervised ML techniques can be used in recession and stock market crash (more than 20% drawdown) forecasting. After learning from strictly past month...
Autor principal: | Malladi, Rama K. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9607774/ https://www.ncbi.nlm.nih.gov/pubmed/36321065 http://dx.doi.org/10.1007/s10614-022-10333-8 |
Ejemplares similares
-
Hybrid Machine Learning Technique for Forecasting Dhaka Stock Market Timing Decisions
por: Banik, Shipra, et al.
Publicado: (2014) -
Brand equity and the Covid-19 stock market crash: Evidence from U.S. listed firms
por: Huang, Yuxuan, et al.
Publicado: (2021) -
Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets
por: Pyo, Sujin, et al.
Publicado: (2017) -
Why stock markets crash : critical events in complex financial systems /
por: Sornette, D.
Publicado: (2003) -
Stock Market Forecasting Based on Spatiotemporal Deep Learning
por: Li, Yung-Chen, et al.
Publicado: (2023)