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| Title: | 臺灣產業類股間因果關係之研究：以雙重變數選擇過程檢驗高維度 Granger 因果關係
Causal Relationship between Sector Indices in Taiwan Stock Market：Testing High-Dimensional Granger Causality with a Post-Double-Selection Procedure |
| Authors: | 劉芳均
Liou, Fang-Jun |
| Contributors: | 徐士勛
Hsu, Shih-Hsun
劉芳均
Liou, Fang-Jun |
| Keywords: | 產業類股報酬關係
高維度Granger因果關係
LASSO
雙重變數選擇過程
邊緣介數法
Sector Indices Relationship
HD-Granger Causality
LASSO
Post Double Selection Procedure
Edge Betweenness |
| Date: | 2023 |
| Issue Date: | 2023-08-02 13:41:26 (UTC+8) |
| Abstract: | 本研究採用 COVID-19 疫情期間的資料探討 27 個台股產業指數週報酬間的因果關係，並分別探討美國聯準會實施量化寬鬆和量化緊縮政策兩段期間資金面的變化對產業股價報酬關係的影響。本文主要根據 Hecq et al. (2019) 提出的分析架構，透過 LASSO 方法進行雙重變數選擇對原高維度 VAR 模型進行系統降維，以得到更為穩健的估計與推論，最後再利用網路圖呈現 Granger 因果關係和分群結果。
首先，在量化寬鬆期間的分析中，我們發現受惠於疫情的生技醫療、食品和資訊服務業類股的股價報酬領先於其他產業，且估計係數幾乎為正，顯示這三個產業在當時為潛在領漲的類股。而電器電纜、半導體、光電類股的股價報酬亦領先於其他產業，但估計係數幾乎為負，多數電子類股在此期間的負向領先關係顯示了在此期間為潛在領跌族群。相對地，在量化緊縮期間，我們發現建材營造和金融保險類股為相對領先者，並且皆對其他產業的估計係數正負相間，顯示了各類股表現不一，跟量化寬鬆期間相比，此期間可能受到通膨和升息等較雜亂的市場訊息影響。
綜合分析上述兩段期間的分群結果，在顯著水準為 1% 之下，均將網路分成多群大小相異的族群；在顯著水準為 5% 之下，均將較關聯的產業分成一個大族群，以及其餘的獨立族群，兩種類型的結果分別適合關注小群類股以及整體產業趨勢的研究者。
This research aims to analyze the causal relationship between the weekly returns of 27 stock sector indices in Taiwan stock market during the COVID-19 epidemic period by testing high-dimensional Granger causality with a post-double-selection procedure. The analysis framework is primarily based on the methodology proposed by Hecq et al. (2019), and the findings are presented through network graphs.
Our findings indicate that during the period of quantitative easing, the returns of biotechnology and medical, food and information services sectors primarily Granger caused the returns of other industries, suggesting that these sectors were potential leading stocks at that time. On the other hand, during the period of quantitative tightening, our findings indicate that the returns of construction and financial sectors primarily Granger caused the returns of other industries. However, the estimated coefficients showed positive or negative values, indicating varied performances across sectors.
Fianaly, the clustering results indicate under significance levels of 1% and 5%, respectively, the former consistently partitioned the network into multiple communities of varying sizes. In contrast, the latter resulted in a single large community and the remaining independent communities. |
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| Description: | 碩士
國立政治大學
經濟學系
110258004 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0110258004 |
| Data Type: | thesis |
| Appears in Collections: | [經濟學系] 學位論文
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