An EM/MCMC Markov-Switching GARCH Behavioral Algorithm for Random-Length Lumber Futures Trading

An EM/MCMC Markov-Switching GARCH Behavioral Algorithm for Random-Length Lumber Futures Trading

This paper tests using two-regime Markov-switching models with asymmetric, time-varying exponential generalized autoregressive conditional heteroskedasticity (MS-EGARCH) variances in random-length lumber futures trading. By assuming a two-regime context (a low <inline-formula><math xmlns=&q...

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Bibliographic Details
Main Authors: Oscar V. De la Torre-Torres, José Álvarez-García, María de la Cruz del Río-Rama
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Mathematics
Subjects:
Markov-switching GARCH
active portfolio management
algorithmic trading
lumber futures
behavioral finance
news sentiment
Online Access:https://www.mdpi.com/2227-7390/12/3/485

Internet

https://www.mdpi.com/2227-7390/12/3/485

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