finance

<p>A dataset containing the daily closing price of 50 NYSE stocks
from 2015-01-02 to 2016-12-30. The first 50 columns are the daily closing
price for each of the 50 stocks, and the last column is the date.</p>

datasets

Fit Gaussian hidden Markov (or semi-Markov) models with / without autoregressive coefficients and with / without regularization. The fitting algorithm for the hidden Markov model is illustrated by Rabiner (1989) <doi:10.1109/5.18626>. The shrinkage estimation on the covariance matrices is based on the method by Ledoit et al. (2004) <doi:10.1016/S0047-259X(03)00096-4>. The shrinkage estimation on the autoregressive coefficients uses the elastic net shrinkage detailed in Zou et al. (2005) <doi:10.1111/j.1467-9868.2005.00503.x>.

Zekun Xu

rarhsmm

Regularized Autoregressive Hidden Semi Markov Model

finance function

<p>A data frame with 504 rows and 51 variables:</p>

finance: NYSE stock closing price data

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