Foreign investor portfolio flow and monetary policy response in the Indonesian stock market considering the COVID-19 pandemic

  • 199 Views
  • 52 Downloads

Creative Commons License
This work is licensed under a 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.

view full abstract hide full abstract
    • Figure 1. Research model
    • 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
    • Conceptualization
      Herry Subagyo, Hersugondo Hersugondo
    • Investigation
      Herry Subagyo, Wijaya Marcellino Candra
    • Methodology
      Herry Subagyo, Hersugondo Hersugondo
    • Supervision
      Herry Subagyo
    • Writing – original draft
      Herry Subagyo, Hersugondo Hersugondo, Wijaya Marcellino Candra, Kardison Lumban Batu, Dwi Eko Waluyo
    • Writing – review & editing
      Herry Subagyo
    • Formal Analysis
      Hersugondo Hersugondo, Dwi Eko Waluyo
    • Resources
      Hersugondo Hersugondo, Wijaya Marcellino Candra, Dwi Eko Waluyo
    • Validation
      Hersugondo Hersugondo
    • Data curation
      Wijaya Marcellino Candra, Kardison Lumban Batu
    • Visualization
      Wijaya Marcellino Candra, Kardison Lumban Batu, Dwi Eko Waluyo
    • Project administration
      Kardison Lumban Batu, Dwi Eko Waluyo
    • Software
      Kardison Lumban Batu