Time Series Modelling With Semiparametric Factor Dynamics
By Byeong U. Park, Enno Mammen, Wolfgang Karl Härdle, Szymon Borak. 2009
106 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/17f398e5087cc9186bf2c00462ac0de4f9ec1d68
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Liangjun Su
- Markus Pelger
- Xia Wang
- Jianqing Fan
- Yuan Liao
- Ruoxuan Xiong
- Dominik Liebl
- Byeong U. Park
In Finance
- Liangjun Su
- Markus Pelger
- Dominik Liebl
- Ruoxuan Xiong
- Yuan Liao
- Xia Wang
- Byeong U. Park
- Jianqing Fan
Citations in the corpus
- State-Varying Factor Models of Large Dimensions (2018, methodology): “This problem can be overcome by using high-frequency data as in Pelger (2019, 2020), Ait-Sahalia and Xiu (2019, 2017), Kong (2017, 2018), and Kong and Liu (2018), that allows to make general statements about time-variation in large-dimensional latent factor models.”
- On Time-Varying Factor Models: Estimation and Testing ∗ (2017, methodology): “For more discussion, see Robinson (1989, 1991). Since we model the factor loadings as a function of scaled time, our factor model can be regarded as a semiparametric factor model. In a similar spirit to ours, Park et al. (2009) study a semiparametric factor model = () 0 + where is”
- Flexible generalized varying coefficient regression models (2012, background): “Some time series models related to the functional coefficient model, with Xj being unobserved common factors that depend on time, have been proposed and studied by, for example, Fengler, Härdle and Mammen (2007) and Park et al. (2009).”
- PROJECTED PRINCIPAL COMPONENT ANALYSIS IN FACTOR MODELS (2014, methodology): “The specific case (1.2) (with γ ik = 0) was used extensively in the financial studies by Connor and Linton (2007), Connor et al. (2012) and Park et al. (2009), with X i ’s being the observed “market characteristic variables”.”
- Modeling and forecasting electricity spot prices: A functional data perspective (2013, methodology): “The two FDA models are the above-discussed DSFM model of Park et al. (2009) and the semi-functional partial linear (SFPL) model of Vilar, Cao and Aneiros (2012).”