Foreign investor portfolio flow and monetary policy response in the Indonesian stock market considering the COVID-19 pandemic
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DOIhttp://dx.doi.org/10.21511/imfi.21(1).2024.08
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Article InfoVolume 21 2024, Issue #1, pp. 88-97
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Creative Commons Attribution 4.0 International License
Foreign portfolio investment in developing countries, including Indonesia, plays a crucial role in the economy, where this fund flow can influence exchange rates and stimulate price increases in the stock market. During the COVID-19 pandemic, the volatility of foreign portfolio flows by investors has significantly increased. To anticipate these conditions, the monetary authorities in Indonesia have implemented various monetary policies to address the possibility of more adverse situations. This study examines the impact of the inflow or outflow of foreign portfolio investments and the monetary policies reflected in the 7-day repo rate of Bank Indonesia on the Indonesian stock market. The data were collected from April 4, 2016, to March 18, 2022. The research methodology involves the Non-Linear Autoregressive Distributed Lag and the Markov Switching Regression (MSR) model. The findings indicate that foreign investor portfolio flows influence the Jakarta Composite Index. There is a tendency for domestic investors to analyze the habits of foreign investors. The study also found that monetary policy is not proven to affect the Jakarta Composite Index, while the USD/IDR exchange rate has an impact on the Indonesian stock market. This indicates many companies listed on the Indonesia Stock Exchange have debt in dollars or are paid in US dollars, making them vulnerable to exchange rate fluctuations.
- Keywords
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JEL Classification (Paper profile tab)C22, E44, E58
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References49
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Tables6
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Figures1
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- Figure 1. Research model
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- Table 1. Descriptive statistics
- Table 2. Characteristics of research subjects
- Table 3. Non-linear autoregressive distributed lag (1; 0; 0; 0), long-run parameter estimation model and ECM coefficients
- Table 4. Error correction coefficient of non-linear autoregressive distributed lag model (1,0,0,0,0)
- Table 5. Diagnostic examination
- Table 6. Markov switching regression
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