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Testing for Parameter Instability and Structural Change in Persistent Predictive Regressions

Andersen, Torben - 2020

This paper develops parameter instability and structural change tests within predictive regressions for economic systems governed by persistent vector autoregressive dynamics. Specifically, in a setting where all – or a subset – of the variables may be fractionally integrated and the...

Persistent link: https://www.econbiz.de/10012831312

A penalized two-pass regression to predict stock returns with time-varying risk premia

Bakalli, Gaetan; Guerrier, Stéphane; Scaillet, Olivier - 2021

We develop a penalized two-pass regression with time-varying factor loadings. The penalization in the first pass enforces sparsity for the time-variation drivers while also maintaining compatibility with the no arbitrage restrictions by regularizing appropriate groups of coefficients. The second...

Persistent link: https://www.econbiz.de/10012487589

Directed graphs and variable selection in large vector autoregressive models

Bertsche, Dominik; Brüggemann, Ralf; Kascha, Christian - 2019 - First draft: July 17, 2017, this version: December 10, 2018

We represent the dynamic relation among variables in vector autoregressive (VAR) models as directed graphs. Based on … need to be included in a VAR if interest is in forecasting or impulse response analysis of a given set of variables. We …-step causal for the variables of interest by relating the paths in the graph to the coefficients of the "direct" VAR …

Persistent link: https://www.econbiz.de/10012317407

Technical Appendix to Consistent Estimation, Variable Selection, and Forecasting in FAVAR Models

Chao, John C.; Swanson, Norman R. - 2022

-Augmented VAR Models by Chao and Swanson (2022) are gathered in this paper …

Persistent link: https://www.econbiz.de/10013306503

Consistent Estimation, Variable Selection, and Forecasting in FAVAR Models

Chao, John C.; Swanson, Norman R. - 2022

. We study this problem within a factor-augmented VAR (FAVAR) framework, and show that by using variables selected via our …

Persistent link: https://www.econbiz.de/10013306504

Forecasting Oil Prices With Penalized Regressions, Variance Risk Premia and Google Data

Lycheva, Maria; Mironenkov, Alexey; Kurbatskii, Alexey; … - 2023

variables, a Hierarchical Vector Auto-Regression model estimated with the LASSO, and a set of forecasting models using a …

Persistent link: https://www.econbiz.de/10014349277

Factor GARCH-ITO Models for High-Frequency Data with Application to Large Volatility Matrix Prediction

Kim, Donggyu - 2017

Several novel large volatility matrix estimation methods have been developed based on the high-frequency financial data. They often employ the approximate factor model that leads to a low-rank plus sparse structure for the integrated volatility matrix and facilitates estimation of large...

Persistent link: https://www.econbiz.de/10012941598

Uniform Predictive Inference for Factor Models with Instrumental and Idiosyncratic Betas

Cheng, Mingmian; Liao, Yuan; Yang, Xiye - 2021

This paper investigates the effect of characteristic-based time-varying factor beta on the diffusion-index type forecast. Specifically, the factor beta includes two distinct components: the "instrumental beta'' is a function of some observed stable variables, while the "idiosyncratic beta''...

Persistent link: https://www.econbiz.de/10013240929

Multivariate Overnight GARCH-Ito Model with Applications in Large Volatility Matrix Estimation and Prediction

Kim, Donggyu; Oh, Minseog; Song, Xinyu; Wang, Yazhen - 2022

This paper introduces a unified multivariate overnight GARCH-Ito model for volatility matrix estimation and prediction both in the low- and high-dimensional set-up. To account for whole-day market dynamics in the financial market, the proposed model has two different instantaneous volatility...

Persistent link: https://www.econbiz.de/10013290653

Forecasting half-hourly electricity prices using a mixed-frequency structural VAR framework

Kapoor, Gaurav; Wichitaksorn, Nuttanan; Li, Mengheng; … - In: Econometrics : open access journal 13 (2025) 1, pp. 1-26

impact on electricity price and volatility. In this paper, we employ a mixed-frequency vector autoregression (MF-VAR …) framework where we propose a VAR specification to the reverse unrestricted mixed-data sampling (RU-MIDAS) model, called RU-MIDAS-VAR … regressors can replicate some key characteristics of electricity prices. We also find the MF-VAR and RU-MIDAS-VAR models achieve …

Persistent link: https://www.econbiz.de/10015408219