1 Fan, J., "Variable selection via nonconcave penalized likelihood and its oracle properties" 96 (96): 1348-1360, 2001
2 Chen, S. L., "Using multivariate stochastic volatility models to investigate the interactions among NASDAQ and major Asian stock indices" 14 (14): 127-133, 2007
3 Zou, H., "The adaptive lasso and its oracle properties" 101 (101): 1418-1429, 2006
4 Lee, T., "Tests for volatility shifts in GARCH against long-range dependence" 36 (36): 127-153, 2015
5 Davis, R. A., "Sparse vector autoregressive modeling" 25 (25): 1077-1096, 2016
6 Changryong Baek, "Sparse seasonal and periodic vector autoregressive modeling" Elsevier BV 106 : 103-126, 2017
7 Basu, S., "Regularized estimation in sparse high-dimensional time series models" 43 (43): 1535-1567, 2015
8 Baek, C., "Periodic dynamic factor models : Estimation approaches and applications" 12 (12): 4377-4411, 2018
9 Baek, C., "On distinguishing multiple changes in mean and long-range dependence using local Whittle estimation" 8 : 931-964, 2014
10 Lütkepohl, H., "New Introduction to Multiple Time Series Analysis" Springer 2005
1 Fan, J., "Variable selection via nonconcave penalized likelihood and its oracle properties" 96 (96): 1348-1360, 2001
2 Chen, S. L., "Using multivariate stochastic volatility models to investigate the interactions among NASDAQ and major Asian stock indices" 14 (14): 127-133, 2007
3 Zou, H., "The adaptive lasso and its oracle properties" 101 (101): 1418-1429, 2006
4 Lee, T., "Tests for volatility shifts in GARCH against long-range dependence" 36 (36): 127-153, 2015
5 Davis, R. A., "Sparse vector autoregressive modeling" 25 (25): 1077-1096, 2016
6 Changryong Baek, "Sparse seasonal and periodic vector autoregressive modeling" Elsevier BV 106 : 103-126, 2017
7 Basu, S., "Regularized estimation in sparse high-dimensional time series models" 43 (43): 1535-1567, 2015
8 Baek, C., "Periodic dynamic factor models : Estimation approaches and applications" 12 (12): 4377-4411, 2018
9 Baek, C., "On distinguishing multiple changes in mean and long-range dependence using local Whittle estimation" 8 : 931-964, 2014
10 Lütkepohl, H., "New Introduction to Multiple Time Series Analysis" Springer 2005
11 Torben G. Andersen, "Modeling and Forecasting Realized Volatility" The Econometric Society 71 (71): 579-625, 2003
12 Song, S., "Large vector auto regressions"
13 Lee, B. S., "Information transmission between the NASDAQ and Asian second board markets" 28 (28): 1637-1670, 2004
14 Dongwoo Kim, "Factor-augmented HAR model improves realized volatility forecasting" Informa UK Limited 27 (27): 1002-1009, 2020
15 Chen, J., "Extended Bayesian information criteria for model selection with large model spaces" 95 (95): 759-771, 2008
16 Barndorff-Nielsen, O. E., "Econometric analysis of realized volatility and its use in estimating stochastic volatility models" 64 (64): 253-280, 2002
17 Song, J., "Detecting structural breaks in realized volatility" 134 : 58-75, 2019
18 Kim, Y., "Consistent model selection criteria on high dimensions" 13 : 1037-1057, 2012
19 Hyndman, R. J, "Another look at forecast-accuracy metrics for intermittent demand" 4 (4): 43-46, 2006
20 Cubadda, C., "A vector heterogeneous autoregressive index model for realized volatility measures" 33 (33): 337-344, 2017
21 Corsi, F., "A simple approximate long-memory model of realized volatility" 7 (7): 174-196, 2009