Return Performance of Indonesian Technology Stocks: A Descriptive Analysis of Post-Pandemic Market Dynamics (2023–2025)
DOI:
https://doi.org/10.71305/ijemr.v3i2.1681Keywords:
Descriptive Quantitative, IDX Technology, Indonesia Stock Exchange, Stock Return, Technology StocksAbstract
This study aims to describe and compare the return performance of technology-related stocks listed on the Indonesia Stock Exchange during the period January 2023–December 2025. This research applies a descriptive quantitative approach using secondary data in the form of monthly stock returns calculated from monthly closing stock prices. The research sample consists of eight technology-related companies, namely GoTo Gojek Tokopedia Tbk. (GOTO), Bukalapak.com Tbk. (BUKA), DCI Indonesia Tbk. (DCII), Elang Mahkota Teknologi Tbk. (EMTK), M Cash Integrasi Tbk. (MCAS), Distribusi Voucher Nusantara Tbk. (DIVA), Kioson Komersial Indonesia Tbk. (KIOS), and Solusi Sinergi Digital Tbk. (WIFI). The data were analyzed using descriptive statistics consisting of mean, minimum, maximum, and standard deviation. The results show heterogeneous return characteristics among Indonesian technology stocks. WIFI recorded the highest average monthly return, followed by DCII and KIOS. Meanwhile, MCAS recorded the lowest average monthly return. In terms of volatility, KIOS showed the highest standard deviation, while BUKA had the lowest standard deviation. These findings indicate that Indonesian technology stocks have diverse risk-return profiles across companies. This study provides an empirical descriptive overview of technology stock performance in Indonesia after the pandemic and after major digital company IPOs. This study contributes to the literature by providing an updated descriptive mapping of risk-return characteristics among Indonesian technology stocks during the post-pandemic digital economy expansion period. The findings offer practical insights for investors, portfolio managers, and market analysts in understanding heterogeneous performance patterns within the Indonesian technology sector before conducting causal or predictive analyses.
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