2026-09-22T14:45:07Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/124632 2026-01-14 col_2142_5131 col_2142_14830 com_2142_5130 com_2142_14829 com_2142_8903

Amir-Ahmadi, Pooyan Amir-Ahmadi, Pooyan Bernhardt, Dan Xie, Shihan Chen, Yuguo 2024-05 application/pdf en text Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-05-01 The student, Zhendong Sun, accepted the attached license on 2024-03-19 at 09:03. The student, Zhendong Sun, submitted this Dissertation for approval on 2024-03-19 at 09:10. This Dissertation was approved for publication on 2024-03-29 at 16:14. DSpace SAF Submission Ingestion Package generated from Vireo submission #20257 on 2024-09-16 at 00:48:52 Estimation and forecasting with time-varying parameters models and sequential method Sun, Zhendong 2024-03-29 Economic Forecasting Time-varying Parameters Model Sequential Monte Carlo In this research, we examine the use of time-varying parameters (TVP) models for out-of-sample forecasting within the realms of macroeconomics and finance. From a methodological perspective, the efficacy of the Sequential Monte Carlo (SMC) method in estimating TVP models is emphasized. Notably, SMC provides a distinct computational edge, requiring substantially less processing time relative to the traditional Markov Chain Monte Carlo (MCMC) method, all the while preserving predictive accuracy. Furthermore, we augment a generic SMC approach by incorporating the variational Bayes method, thereby enabling it to estimate large TVP models with an integrated variable selection prior. Empirically, we embark on a detailed exploration of three out-of-sample predictive applications in the fields of macroeconomics and finance: 1) the estimation of US GDP and inflation via a trivariate VAR model; 2) the forecasting of monthly returns of the S$\&$P500 index, which integrates a comprehensive set of 143 predictors; and 3) the nowcasting of US GDP using a TVP VAR model enriched with mixed-frequency variables. Consistently, across these analytical domains, findings suggest that TVP models bolster predictive capabilities, surpassing both their fixed-parameter counterparts and other advanced methodologies. Text eng https://hdl.handle.net/2142/124632 Copyright 2024 Zhendong Sun Ph.D. Dissertation Economics University of Illinois at Urbana-Champaign Economics