The effect of the US Dollar Index and foreign stock indexes on Jakarta Composite Index (JKSE)
DOI:
https://doi.org/10.53402/ajebm.v2i1.272Keywords:
US Dollar Index, DJIA, NASDAQ, SSEC, Nikkei 225, AORD, FTSEAbstract
Many theories explain that the Jakarta Composite Index (JKSE) can be influenced by stock indices or currencies of other countries. With the recent events of the war between Russia and Ukraine, this might be the perfect opportunity to prove that statement. The purpose of this study is to see whether the United States Dollar Index, Dow Jones Industrial Average (DJIA), NASDAQ 100 Index, Shanghai Composite Index (SSEC), Nikkei 225 Index (N225), Australian All Ordinaries Index (AORD), FTSE Index 100, against the Jakarta Composite Index (JKSE). This study uses the documentation method with secondary data in the form of daily closing prices for foreign stock indices and USD indices spread from 4 January 2022 to 25 February 2022. The hypothesis is tested with a partial significant test (t-test), simultaneous significant test (F test), and coefficient of determination. The test results show that the USD, DJIA, NASDAQ, SSEC, N225, AORD, and FTSE indices do not affect the JKSE. But simultaneously the USD Index, DJIA, NASDAQ, SSEC, N225, AORD, and FTSE affect JKSE. This may be because, during the study period, there were no foreign companies listed on the Indonesian Stock Exchange. Companies listed on the Indonesia Stock Exchange are domestic companies denominated in Rupiah, so the investment that occurs is purely local investment using Rupiah. At this time the world is also in a period of economic recovery after previously declining due to the COVID-19 pandemic. This causes investors from other countries to prefer investing in their own country. So, investment from abroad to Indonesia also decreased. This research is limited to using independent and dependent variables used and the research is limited to only 2 months. For further research, it is recommended to add more varied independent variables and extend the observation period so that it can increase better data distribution.
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Copyright (c) 2023 Hendro Fangsawinata, Ratna Septiyanti, Agus Zahron Idris
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