Are CDS spreads predictable during the Covid-19 pandemic? Forecasting based on SVM, GMDH, LSTM and Markov switching autoregression

This paper investigates the forecasting performance for credit default swap (CDS) spreads by Support Vector Machines (SVM), Group Method of Data Handling (GMDH), Long Short-Term Memory (LSTM) and Markov switching autoregression (MSA) for daily CDS spreads of the 513 leading US companies, in the peri...

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Detalles Bibliográficos
Autores principales: Vukovic, Darko B., Romanyuk, Kirill, Ivashchenko, Sergey, Grigorieva, Elena M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782769/
https://www.ncbi.nlm.nih.gov/pubmed/35095216
http://dx.doi.org/10.1016/j.eswa.2022.116553

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782769/
https://www.ncbi.nlm.nih.gov/pubmed/35095216
http://dx.doi.org/10.1016/j.eswa.2022.116553

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