UNDERSTANDING INVESTORS’ BEHAVIOR DURING STOCK PRICE MANIPULATION: A CASE OF INDONESIA’S STOCK MARKET

• Main Author: Riznaldi Akbar
• Format: Article
• Language: English
• Published: Universitas Tarumanagara 2017-03-01
• Series: Jurnal Manajemen
• Subjects: Text mining, stock price manipulation, fraud, early warning system
• Online Access: http://www.ecojoin.org/index.php/EJM/article/view/70
• ISSN: 1410-3583; 2549-8797

Penelitian ini mencoba untuk mencari pola tekstual yang berkaitan dengan perilaku investor dan sentimen selama manipulasi harga saham di Bursa Efek Indonesia. Kami mengusulkan analisis text mining untuk menunjukkan proses penggalian informasi dari berita dan media rilis Tweeter selama periode 2000 sampai 2014. Kami mengambil tiga sampel perusahaan dari PT AGIS Tbk (TMPI), PT Garda Tujuh Buana Tbk (GTBO) dan PT Bumi Resources Tbk (BUMI) yang telah ditunjukkan mengalami manipulasi harga saham. Perusahaan-perusahaan ini mengalami harga saham apresiasi abnormal dan diikuti dengan penurunan tajam dari sekitar 90 persen dalam waktu singkat. Informasi yang diekstrak dari Tweeter dan analisis sentimen memberikan bukti bahwa berita dan media rilis cenderung menghasilkan umum istilah kunci negatif seperti "terjun", "drop", dan "jatuh"; serta istilah yang terkait dengan laporan laba rugi seperti "kehilangan", "keuntungan", "bersih", "penjualan" dan "pendapatan" .Ini menunjukkan bahwa sebagian besar investor akan memiliki bias negatif dan menderita lebih ketika harga saham mengalami signifikan menurun. Hal ini juga mengungkapkan bahwa investor lebih cupet pada laporan laba rugi daripada menganalisis gambaran besar dari penilaian dasar perusahaan secara keseluruhan. Dengan demikian kita berpendapat bahwa basis pengetahuan ini dan istilah kunci dapat digunakan untuk mencerminkan karakteristik umum dari perilaku investor selama manipulasi harga saham di pasar saham Indonesia. This study attempts to search textual patterns that are associated with investor behavior and sentiment during stock price manipulation in Indonesia’s Stock Market. We propose text mining analysis to demonstrate the process of extracting information from news and media release of Tweeter over the period of 2000 to 2014. We took three sample firms of PT AGIS Tbk (TMPI), PT Garda Tujuh Buana Tbk (GTBO) and PT Bumi Resources Tbk (BUMI) that have been indicated experiencing stock price manipulation. These firms experienced an abnormal stock price appreciation and followed with a sharp decline of about 90 per cent within short period of time. The extracted information from Tweeter and sentiment analysis provide evidence that news and media releases tend to yield common negative key terms such as “plunge”, “drop”, and “fall”; as well as terms related to income statements such as “loss”, “profit”, “net”, “sales” and “revenue”.It shows us that most investors would have negative bias and suffer more when the stock price experienced a significant decline. It also reveals that investors are more short-sighted on the profit and loss statements rather than analyzing the big picture of corporate fundamental valuation as a whole. We thus argue that these knowledge bases and key terms could be used to reflect common characteristics of investor behavior during stock price manipulation in the Indonesia’s stock market.