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Dividend announcement effect analysis before and during the COVID-19 pandemic in the Indonesia Stock Exchange

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  • Robiyanto Robiyanto

    (Satya Wacana Christian University)

  • Fanny Yunitaria

    (Satya Wacana Christian University)

Abstract

The emergence of the SARS-CoV-2 or COVID-19 pandemic has become a challenge for the global society, including the investors in the capital market, due to the uncertainty it has caused. In relation to the phenomenon, this research aimed to examine the impact of COVID-19 pandemic on the dividend announcement effect in Indonesia Stock Exchange by comparing the market volatility around the dividend announcement date of the selected stocks in 2019 and 2020. Implication of dividend increase and decrease as well as stock–risk profiling is also added for further learning. This research used event study methodology as a tool to analyze the data of the 23 sample companies taken from the LQ45 index. The period of analysis is ranged from 10 days before the dividend announcement to 10 days after the dividend announcement date. The study discovered that in 2019, the capital market presented a weak response toward the event, indicated by the inexistence of abnormal return. Moreover, in 2020, the dividend announcement effect caused negative insignificant abnormal returns and the number of companies with low volatility increased, which implies that the stock market is more pessimistic during the pandemic period. Even when the dividend amount increased from the previous period, the market still shows a negative reaction to it in 2020.

Suggested Citation

  • Robiyanto Robiyanto & Fanny Yunitaria, 2022. "Dividend announcement effect analysis before and during the COVID-19 pandemic in the Indonesia Stock Exchange," SN Business & Economics, Springer, vol. 2(2), pages 1-20, February.
    • Handle: RePEc:spr:snbeco:v:2:y:2022:i:2:d:10.1007_s43546-021-00198-8
    DOI: 10.1007/s43546-021-00198-8
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    References listed on IDEAS

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    1. Budi Frensidy & Irene Josephine & Ignatius Roni Setyawan, 2019. "Price Formation around Dividend Announcement Date: Empirical Evidence in Indonesian Stock Exchange," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 106-118.
    2. Jiangxia Liu & Sourish Sarkar & Sanjay Kumar & Zhenhu Jin, 2018. "An analysis of stock market impact from supply chain disruptions in Japan," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 67(1), pages 192-206, January.
    3. Schell, Daniel & Wang, Mei & Huynh, Toan Luu Duc, 2020. "This time is indeed different: A study on global market reactions to public health crisis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    4. Khanal, Aditya R. & Mishra, Ashok K., 2017. "Stock price reactions to stock dividend announcements: A case from a sluggish economic period," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 338-345.
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    Cited by:

    1. Georgina Maria Tinungki & Powell Gian Hartono & Robiyanto Robiyanto & Agus Budi Hartono & Jakaria Jakaria & Lydia Rosintan Simanjuntak, 2022. "The COVID-19 Pandemic Impact on Corporate Dividend Policy of Sustainable and Responsible Investment in Indonesia: Static and Dynamic Panel Data Model Comparison," Sustainability, MDPI, vol. 14(10), pages 1-23, May.

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    More about this item

    Keywords

    Event study methodology; Dividend announcement; Abnormal return; Market reaction; COVID-19 pandemic; Indonesia stock exchange;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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