| dc.contributor.advisor | Rizki, Akbar | |
| dc.contributor.advisor | Sadik, Kusman | |
| dc.contributor.author | Dandi, Yusuf | |
| dc.date.accessioned | 2022-08-24T13:14:17Z | |
| dc.date.available | 2022-08-24T13:14:17Z | |
| dc.date.issued | 2022 | |
| dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/113996 | |
| dc.description.abstract | Pasar modal menjadi salah satu bidang yang terkena dampak COVID-19. Hal ini terlihat dari menurunnya indeks saham di berbagai sektor di Indonesia. Penelitian ini bertujuan menguraikan pengaruh COVID-19 terhadap indeks saham sektoral. Data yang digunakan merupakan data harian periode 15 Maret 2020 hingga 16 Maret 2021 yang terdiri atas data indeks saham sektoral dan data kasus harian COVID-19. Interpolasi linier digunakan pada data indeks saham sektoral untuk menduga data hilang. Uji kausalitas Granger digunakan untuk mengetahui hubungan sebab-akibat antara COVID-19 dan indeks saham sektoral. Selanjutnya vector autoregressive digunakan untuk memodelkan pengaruh COVID-19 terhadap indeks saham sektoral. Hasil penelitian menunjukkan bahwa pengaruh guncangan sebesar satu simpangan baku perubahan kasus harian COVID-19 akan direspon perubahan relatif indeks saham sektoral selama 3 sampai dengan 4 hari ke depan. Besarnya kontribusi perubahan kasus harian COVID-19 dalam memengaruhi perubahan relatif indeks saham sektoral relatif kecil dengan persentase kurang dari 5%. Selain itu, perubahan kasus harian COVID-19 memengaruhi perubahan relatif indeks saham sektor infrastruktur, utilitas, dan transportasi pada taraf nyata 5%. | id |
| dc.description.abstract | The capital market is one of the sectors affected by COVID-19. This can be seen from the decline of stock index in various sectors in Indonesia. This study aims to describe the effect of COVID-19 on sectoral indices. The data used is daily data for the period March 15, 2020 until March 16, 2021, which consists of sectoral indices data and daily COVID-19 case data. Linear imputation is used to estimate missing observations on the sectoral indices data. Granger causality test is used to determine the causal relationship between COVID-19 and sectoral indices. The effect of COVID-19 on sectoral indices is then modelled using the vector autoregressive model. The results show that one standard deviation shock in changes in daily COVID-19 cases will be responded by relative changes in sectoral indices over the next 3 to 4 days. Changes in daily COVID-19 cases contribute to a relatively small influence in the relative changes of sectoral indices, with percentage of less than 5%. Furthermore, changes in the daily COVID-19 cases affect the relative changes in the stock index of the infrastructure, utilities, and transportation sectors at a significant level of 5%. | id |
| dc.language.iso | id | id |
| dc.publisher | IPB University | id |
| dc.title | Penggunaan Vector Autoregressive untuk Mengetahui Pengaruh COVID-19 terhadap Indeks Saham Sektoral | id |
| dc.title.alternative | The Use of Vector Autoregressive to See the Impact of COVID-19 on Sectoral Indices | id |
| dc.type | Undergraduate Thesis | id |
| dc.subject.keyword | COVID-19 | id |
| dc.subject.keyword | sectoral indices | id |
| dc.subject.keyword | vector autoregressive (VAR) | id |
