compindPCA - Computation of Relative Weights of Variables and Composite Index Values Based on PCA

It helps in development of a principal component analysis based composite index by assigning weights to variables and combining the weighted variables. For method details see Sendhil, R., Jha, A., Kumar, A. and Singh, S. (2018). <doi:10.1016/j.ecolind.2018.02.053>, and Wu, T. (2021). <doi:10.1016/j.ecolind.2021.108006>.

Last updated 2 years ago

1.00 score 1 scripts 173 downloads

eemdARIMA - EEMD Based Auto Regressive Integrated Moving Average Model

Forecasting time series with different decomposition based ARIMA models. For method details see Yu L, Wang S, Lai KK (2008). <doi:10.1016/j.eneco.2008.05.003>.

Last updated 3 years ago

1.00 score 206 downloads

SBAGM - Search Best ARIMA, GARCH, and MS-GARCH Model

Get the most appropriate autoregressive integrated moving average, generalized auto-regressive conditional heteroscedasticity and Markov switching GARCH model. For method details see Haas M, Mittnik S, Paolella MS (2004). <doi:10.1093/jjfinec/nbh020>, Bollerslev T (1986). <doi:10.1016/0304-4076(86)90063-1>.

Last updated 4 years ago

1.00 score 2 scripts 135 downloads

MSGARCHelm - Hybridization of MS-GARCH and ELM Model

Implements the three parallel forecast combinations of Markov Switching GARCH and extreme learning machine model along with the selection of appropriate model for volatility forecasting. For method details see Hsiao C, Wan SK (2014). <doi:10.1016/j.jeconom.2013.11.003>, Hansen BE (2007). <doi:10.1111/j.1468-0262.2007.00785.x>, Elliott G, Gargano A, Timmermann A (2013). <doi:10.1016/j.jeconom.2013.04.017>.

Last updated 4 years ago

1.00 score 1 stars 5 scripts 159 downloads