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Stock Prices Analysis of State-Owned Enterprise and Non-State-Owned Enterprise in Response to Negative Information Period 2017-2019

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  • Raka Daniel Lihardo Sumbayak
  • Tony Irawan
  • Trias Andati

Abstract

There were bad news affected stock prices, i.e. Fraud and bad financial performance. Fraud on State Owned Enterprises (SOE) listed companies was suspected to have a stronger impact on stock prices compared to Non-SOE issuers. The effect of bad financial performance on Non-SOE issuers was thought to have a stronger impact on stock prices when compared to SOE issuers. This research was conducted on SOE and non-SOE that experienced fraud and bad financial performance from 2017 to 2019. Data analysis was performed with the Google Search Volume Index, Difference Test, and Multiple Linear Regression Analysis. The data from Google Search Volume Index showed that SOE issuers were more searched by the public when compared to Non-SOE issuers in responding to Fraud and bad financial performance. Linear Regression Analysis found that the decline in stock prices of SOE issuers was lower than the Non-SOE issuers in response to Fraud. The decline in stock prices of SOE issuers in response to the bad financial performance in the Property and Finance sectors was lower than the decline in stock prices of Non-SOE issuers. However, the decline in the stock prices of Non-SOE companies in response to the bad financial performance in the Basic Industry sector was lower than the SOE issuers. This could be influenced by SOE stock ownership dominated by the Indonesian government and the existence of a Conservatism Bias.

Suggested Citation

  • Raka Daniel Lihardo Sumbayak & Tony Irawan & Trias Andati, 2021. "Stock Prices Analysis of State-Owned Enterprise and Non-State-Owned Enterprise in Response to Negative Information Period 2017-2019," International Journal of Business and Management, Canadian Center of Science and Education, vol. 15(6), pages 204-204, July.
    • Handle: RePEc:ibn:ijbmjn:v:15:y:2021:i:6:p:204
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    References listed on IDEAS

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    1. Takeda, Fumiko & Wakao, Takumi, 2014. "Google search intensity and its relationship with returns and trading volume of Japanese stocks," Pacific-Basin Finance Journal, Elsevier, vol. 27(C), pages 1-18.
    2. Wu, Chen-Hui & Wu, Chin-Shun & Liu, Victor W., 2009. "The conservatism bias in an emerging stock market: Evidence from Taiwan," Pacific-Basin Finance Journal, Elsevier, vol. 17(4), pages 494-505, September.
    3. Nazrul Hisyam Ab Razak & Rubi Ahmad & Huson Aliahmed Joher, 2011. "Does Government Linked Companies (GLCs) perform better than non-GLCs? Evidence from Malaysian listed companies," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 1(1), pages 1-10.
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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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