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Investment decisions in pharmaceutical manufacturing companies listed on the Indonesia Stock Exchange (IDX) are influenced by fundamental analysis and stock price fluctuations. Stock prices reflect market perceptions shaped by profitability, liquidity, and capital structure. This study examines the effects of Return on Assets (ROA), Current Ratio (CR), and Debt-to-Equity Ratio (DER) on stock prices, both partially and simultaneously. Using a quantitative approach, the study analyzes secondary data from audited financial statements and stock prices of 12 pharmaceutical companies during 2022–2024, totaling 36 observations. Panel data regression with EViews 12 is applied. Results show that ROA and DER have positive and significant effects on stock prices, while CR has a negative but insignificant effect. Simultaneously, all three variables significantly influence stock prices, with an adjusted R² of 73%, indicating strong explanatory power. Profitability (ROA) is the most influential factor, followed by capital structure (DER), while liquidity (CR) shows no significant impact.

The Indonesian capital market has become a vital pillar of the national economy, providing opportunities for companies to obtain funding while simultaneously providing an investment vehicle for the wider community. In this context, stocks are the most sought-after instrument due to the potential returns they offer. However, stock investment is constantly faced with uncertainty, with fluctuating stock prices often presenting challenges for investors, especially those without a thorough understanding of the company's fundamental performance. An interesting phenomenon, the starting point of this research, is the quite extreme price movements of BIPI shares over the past decade. From 2015 to 2021, BIPI's share price remained stagnant at Rp 50 per share, a condition often referred to by market participants as "gocap" (goat capit). This condition reflects low investor interest in the company's shares, possibly due to high risk perceptions or unconvincing fundamental performance.

Stock market volatility represents a key indicator of financial market uncertainty, particularly in emerging economies where market structures are still evolving and are highly sensitive to global shocks. This study aims to analyze and compare the volatility dynamics of stock markets in four Asian emerging economies: Indonesia, India, Malaysia, and Thailand. The research employs a quantitative approach using daily stock index data from January 2011 to January 2026 obtained from Yahoo Finance. Stock returns are calculated using logarithmic transformation and analyzed using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH(1,1)) model. Prior to model estimation, stationarity and ARCH effect tests are conducted to ensure the validity of volatility modeling. The empirical findings indicate that all return series exhibit non-normal distribution, strong volatility clustering, and significant ARCH effects. The estimation results show that both ARCH and GARCH parameters are statistically significant, with persistence levels close to unity across all markets, implying that volatility shocks tend to persist over a long period. These findings suggest that emerging stock markets in Asia are highly sensitive to external shocks and exhibit long-memory volatility behavior. The results provide important implications for investors and policymakers in designing effective risk management and market stabilization strategies.

This study aims to analyze the reaction of the Indonesian capital market to the announcement of Donald Trump’s import tariff policy using an event study approach. Market reactions are measured through abnormal return and trading volume activity of exporting companies listed on the Indonesia Stock Exchange (IDX), with an event window of three trading days before and three trading days after the initial tariff announcement on April 2, 2025 and the revised tariff announcement on July 15, 2025. This study employs secondary data in the form of daily stock prices and trading volumes, analyzed using descriptive statistics, normality tests, and the Wilcoxon Signed Rank Test. The results indicate that the Indonesian capital market reacts to the announcement of Donald Trump’s import tariff policy, as reflected by differences in abnormal return and trading volume activity before and after the announcements, thereby supporting signaling theory and the semi-strong form of market efficiency.

Perkembangan kecerdasan buatan (AI) mendorong inovasi dalam analisis keuangan, termasuk prediksi harga saham yang fluktuatif. Penelitian ini bertujuan memprediksi harga saham PT Garudafood Putra Putri Jaya Tbk menggunakan model ARIMA dengan penanganan Outlier sebagai pendekatan awal menuju sistem prediksi yang lebih adaptif. Data harga penutupan harian dari Yahoo Finance dianalisis melalui uji stasioneritas, identifikasi model ARIMA, deteksi Outlier berbasis log-return, serta evaluasi performa menggunakan RMSE, MAE, dan MAPE. Hasil penelitian menunjukkan bahwa ARIMA Outlier memberikan performa lebih baik dibandingkan ARIMA dasar. ARIMA standar menghasilkan MAPE 1.32% dan AIC –899.46, sedangkan ARIMA dengan tiga dummy Outlier mencapai MAPE 1.16% dan AIC –900.37. Peramalan 14 hari ke depan menunjukkan pola yang stabil pada kisaran Rp 370–371. Pada data uji, ARIMA dasar memberikan akurasi terbaik pada pertengahan Agustus, sedangkan ARIMA Outlier mencapai akurasi tertinggi pada akhir Agustus dengan prediksi Rp 370.2 yang sangat dekat dengan harga aktual Rp 370.4. Hasil ini menunjukkan bahwa penanganan Outlier meningkatkan ketepatan model, sehingga ARIMA Outlier dapat digunakan sebagai fondasi awal menuju pengembangan sistem prediksi keuangan berbasis AI.