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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 楊鈞澔 | zh_TW |
| dc.contributor.advisor | Chun-Hao Yang | en |
| dc.contributor.author | 王柏崴 | zh_TW |
| dc.contributor.author | Po-Wei Wang | en |
| dc.date.accessioned | 2024-08-09T16:26:00Z | - |
| dc.date.available | 2024-08-10 | - |
| dc.date.copyright | 2024-08-09 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-08-01 | - |
| dc.identifier.citation | Amari, S. i. (2016), Information geometry and its applications, Vol. 194, Springer.
Bańbura, M., Giannone, D. and Reichlin, L. (2010), ‘Large bayesian vector auto regres sions’, Journal of applied Econometrics 25(1), 71–92. Bollerslev, T. (1986), ‘Generalized autoregressive conditional heteroskedasticity’, Journal of econometrics 31(3), 307–327. Carriero, A., Clark, T. E. and Marcellino, M. (2019), ‘Large bayesian vector autore gressions with stochastic volatility and non-conjugate priors’, Journal of Econometrics 212(1), 137–154. Carriero, A., Kapetanios, G. and Marcellino, M. (2012), ‘Forecasting government bond yields with large bayesian vector autoregressions’, Journal of Banking & Finance 36(7), 2026–2047. Carvalho, C. M., Polson, N. G. and Scott, J. G. (2009), Handling sparsity via the horseshoe, in ‘Artificial intelligence and statistics’, PMLR, pp. 73–80. Carvalho, C. M., Polson, N. G. and Scott, J. G. (2010), ‘The horseshoe estimator for sparse signals’, Biometrika 97(2), 465–480. Chan, J. C. and Yu, X. (2022), ‘Fast and accurate variational inference for large bayesian vars with stochastic volatility’, Journal of Economic Dynamics and Control 143, 104505. Choi, K., Yi, J., Park, C. and Yoon, S. (2021), ‘Deep learning for anomaly detection in time-series data: Review, analysis, and guidelines’, IEEE access 9, 120043–120065. Cuaresma, J. C., Feldkircher, M. and Huber, F. (2016), ‘Forecasting with global vec tor autoregressive models: A bayesian approach’, Journal of Applied Econometrics 31(7), 1371–1391. Gefang, D. (2014), ‘Bayesian doubly adaptive elastic-net lasso for var shrinkage’, Inter national Journal of Forecasting 30(1), 1–11. Gefang, D., Koop, G. and Poon, A. (2023), ‘Forecasting using variational bayesian infer ence in large vector autoregressions with hierarchical shrinkage’, International Journal of Forecasting 39(1), 346–363. Kalli, M. and Griffin, J. E. (2018), ‘Bayesian nonparametric vector autoregressive mod els’, Journal of econometrics 203(2), 267–282. Kullback, S. and Leibler, R. A. (1951), ‘On information and sufficiency’, The annals of mathematical statistics 22(1), 79–86. Makalic, E. and Schmidt, D. F. (2015), ‘A simple sampler for the horseshoe estimator’, IEEE Signal Processing Letters 23(1), 179–182. Miranda-Agrippino, S. and Ricco, G. (2021), ‘The transmission of monetary policy shocks’, American Economic Journal: Macroeconomics 13(3), 74–107. Ormerod, J. T. and Wand, M. P. (2010), ‘Explaining variational approximations’, The American Statistician 64(2), 140–153. Prüser, J. (2021), ‘The horseshoe prior for time-varying parameter vars and monetary pol icy’, Journal of Economic Dynamics and Control 129, 104188. Sharma, D. (2016), ‘Nexus between financial inclusion and economic growth: Evidence from the emerging indian economy’, Journal of financial economic policy 8(1), 13–36. Sims, C. A. (1980), ‘Macroeconomics and reality’, Econometrica: journal of the Econo metric Society pp. 1–48. Stock, J. H. and Watson, M. W. (2001), ‘Vector autoregressions’, Journal of Economic perspectives 15(4), 101–115. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/93920 | - |
| dc.description.abstract | 在這篇研究中，我們會給出一個包含向量自迴歸模型、自迴歸隨機波動、馬蹄鐵先驗分佈的模型，再使用變分貝氏方法估計模型中的變數服從的分佈，像是常態分佈或是逆伽瑪分佈這些比較常見以及期望值容易計算的分佈，最後再使用迭代的方式找到每個變數的估計值。 | zh_TW |
| dc.description.abstract | In this thesis, we propose an approach to find an estimate of the variables in a model that combines vector autoregression (VAR), log-normal autoregressive stochastic volatility (ARSV) and the horseshoe prior. Using variational Bayes (VB) method, we can show an approximated distribution to each variable such as normal or inverse gamma distribution which are well-known and the expectation is easy to be obtained, which allows us to use iteration to estimate each variable. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-08-09T16:26:00Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-08-09T16:26:00Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 致謝 i
摘要 iii Abstract v Contents vii Chapter 1 Introduction 1 1.1 Large Bayesian VAR Model 1 1.2 GARCH Versus SV 2 1.3 Goal 3 Chapter 2 Theoretical Preliminary 5 2.1 Horseshoe prior 5 2.2 VAR with Stochastic Volatility and Horseshoe prior 8 2.3 Variational Bayesian: KL and ELBO 12 Chapter 3 Main Results 15 3.1 The Optimal Density for Parameters in VAR and SV 18 3.2 The Optimal Density for Horseshoe Prior Parameters 24 3.3 Iterative Algorithm 26 Chapter 4 Conclusion and Outlooks 31 4.1 Conclusion 31 4.2 Outlooks 31 References 33 | - |
| dc.language.iso | en | - |
| dc.subject | 向量自迴歸模型 | zh_TW |
| dc.subject | 牛頓-拉弗森方法 | zh_TW |
| dc.subject | 變分貝氏方法 | zh_TW |
| dc.subject | 馬蹄鐵先驗分佈 | zh_TW |
| dc.subject | 隨機波動 | zh_TW |
| dc.subject | horseshoe prior | en |
| dc.subject | variational Bayesian | en |
| dc.subject | Newton-Raphson | en |
| dc.subject | stochastic volatility | en |
| dc.subject | vector autoregression | en |
| dc.title | 自迴歸隨機波動的向量自迴歸模型之馬蹄鐵估計 | zh_TW |
| dc.title | Horseshoe Estimates for Vector Autoregression Model with Log Normal Stochastic Volatility | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 崔茂培;陳裕庭;李志煌 | zh_TW |
| dc.contributor.oralexamcommittee | Mao-Pei Tsui;Yu-Ting Chen;Jhih-Huang Li | en |
| dc.subject.keyword | 向量自迴歸模型,隨機波動,馬蹄鐵先驗分佈,變分貝氏方法,牛頓-拉弗森方法, | zh_TW |
| dc.subject.keyword | vector autoregression,stochastic volatility,horseshoe prior,variational Bayesian,Newton-Raphson, | en |
| dc.relation.page | 34 | - |
| dc.identifier.doi | 10.6342/NTU202402563 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2024-08-05 | - |
| dc.contributor.author-college | 理學院 | - |
| dc.contributor.author-dept | 數學系 | - |
| 顯示於系所單位： | 數學系 | |
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