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Stock price crash risk has become a critical concern in investment decision making and risk management, drawing the attention of investors and regulators amid a dynamic global business environment and repeated financial crises. However, empirical evidence on this issue remains limited in developing countries, particularly in the Iraqi context. Therefore, this study examines the relationship between board characteristics—board gender diversity, board size, and board independence—and stock price crash risk, as well as the mediating role of audit committee effectiveness. The study uses secondary data from ten banks listed on the Iraq Stock Exchange (ISX) during the 2017–2023 period. The findings show that board gender diversity and board size significantly reduce stock price crash risk. Higher female representation on boards is associated with more conservative decision making and stronger monitoring, which improves financial reporting transparency. An appropriately sized board also enhances oversight and lowers the likelihood of extreme negative stock price movements. In addition, the results indicate that the frequency of audit committee meetings mediates the relationship between board independence and stock price crash risk, suggesting that board independence is more effective when supported by an active audit committee. This study recommends that investors and financial analysts consider board characteristics and audit committee effectiveness when assessing firm value and risk. Furthermore, regulators and policymakers are encouraged to promote gender diversity on corporate boards to strengthen governance quality and reduce the probability of stock price crashes.

Stocks represent a capital market instrument with the potential to generate high returns. When making investment decisions, investors typically assess various internal aspects of a company, including its financial performance. The objective of this study is to examine the influence of profitability, liquidity, and leverage ratios on stock prices in the Indonesian banking sector, with a particular focus on state-owned banks, in both partial and simultaneous regression models. The methodology employed is quantitative analysis, with a secondary data set being utilized. The sample was determined using a purposive sampling technique, covering four state-owned banks (BRI, BNI, Mandiri, and BTN) for the 2010-2024 period. The findings of the analysis demonstrate that profitability and leverage exert a substantial negative influence on the stock prices of these banking institutions, while the liquidity ratio does not demonstrate a significant effect. Concurrently, all three variables exert an influence on stock prices, with an R-squared value of 58%.

The dynamic fluctuations in stock prices present a major challenge for investors in making informed decisions. To anticipate such uncertainties, forecasting methods that can provide accurate predictions are required. This study compares two time series forecasting methods Autoregressive Integrated Moving Average (ARIMA) and Double Exponential Smoothing (Holt) in predicting the stock prices of PT Telkom Indonesia (TLKM). The dataset consists of monthly closing prices from January 2018 to December 2023. The performance of each model is evaluated using three error metrics: Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE). The results show that the ARIMA(1,1,1) model yields higher predictive accuracy than the Holt method, with MAE of 787.71, MSE of 771,844.2, and RMSE of 878.55. In contrast, the Holt method records a MAE of 837.19, MSE of 878,393.4, and RMSE of 937.23. These findings confirm that ARIMA is superior in capturing the complex patterns of stock price movements and is more effective in volatile market conditions such as the stock exchange.

This study aims to analyze the development strategy of the Jeanete business, located in Maumere City, Jl.  Kesehatan No.  3, Lorong Masuk SDK Yos Sudarso, using the Strengths, Weaknesses, Opportunities, and Threats (SWOT) approach.  The research employs a descriptive qualitative method with data collected through observation, interviews, and documentation of the Jeanete business operations.  The results indicate that the main strengths of the business include affordable product prices, unique item variations, and increasing consumer interest in preloved products.  However, Jeanete also faces several weaknesses, such as dependence on supplies from outside the region, limited stock availability, and fluctuating bale prices.  On the other hand, opportunities include the growing trend of thrifting among young consumers and rising demand for environmentally friendly products.  The threats faced by the business involve increasing competition, shifting consumer preferences, and the risk of products not passing quality control.  Based on these findings, the development strategy for Jeanete should focus on improving product quality, strengthening digital promotion, and maintaining more stable supply management.

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.

The management of material and labor costs at Gregors Barbershop is still manual and not formally structured, resulting in wastage of consumable materials, suboptimal labor utilization, and difficulties in determining service prices that align with the expected profit margins. Material costs, such as hair gel, tissues, disposable razors, and alcohol/disinfectants, are not recorded systematically, leading to frequent mismatches between stock and actual needs, while labor costs are calculated improvisationally without considering productivity and service targets. This activity aims to improve the ability of owners and employees to plan, control, and evaluate operational costs systematically, ensuring efficiency, resource optimization, and business profitability. The method uses an applied, hands-on approach, including the identification of partner needs, preparation of relevant training modules, direct operational mentoring, and evaluation with follow-up. The object of the activity is Gregors Barbershop in Batu Aji District, Batam City, which offers services such as modern men’s haircuts, classic shaves, shaving, hair treatments, and the sale of grooming products like pomade and hair oil. The results show increased efficiency in the use of consumable materials, more productive labor management, more systematic cost planning, and the ability to set service prices in line with costs and profit margins. It is recommended to implement a digital recording system and productivity-based incentives to ensure more accurate cost control, more efficient operations, and sustainable business profitability.

This study aims to examine the relationship between Corporate Social Responsibility (CSR) disclosure and profitability with firm value. The research was conducted on companies in the oil, gas, and coal sub-sector listed on the Indonesia Stock Exchange (IDX) during the 2021–2024 period. The independent variables in this study are corporate social responsibility disclosure and profitability, while firm size is employed as a control variable. Firm value is proxied by Price to Book Value (PBV), whereas profitability is measured using Return on Equity (ROE). This study is grounded in Stakeholder Theory and Signaling Theory to explain the relationships among the variables. The sample was determined using purposive sampling, resulting in 29 companies. The data analysis techniques applied include Pearson correlation analysis and multiple linear regression to examine both the simple relationships and the effects of corporate social responsibility disclosure and profitability on firm value. The results indicate that corporate social responsibility disclosure has a negative relationship with firm value, while profitability shows a positive and significant relationship with firm value.

This study applies the Mean Variance model, which aims to form an optimal portfolio composition in the health, property, and cyclical consumer sectors and combine the three sectors into one portfolio, then visualize its efficient frontier. This study analyzes the return profiles and compares the risks of each portfolio using alternative risk measures such as the Coefficient of Variation (CV), Value at Risk (VaR), and Conditional Value at Risk (CVaR). Daily closing price data for the three sectors listed on the Indonesia Stock Exchange (IDX) from March 2, 2020, to March 3, 2025, were used in this study. Stock selection was conducted using purposive sampling, followed by selecting seven stocks for optimization based on the lowest Coefficient of Variation (CV) value. Portfolio optimization analysis was conducted using the Python programming language with Visual Studio Code software. The findings of this study indicate that the combined portfolio incorporating the three sectors is the most efficient, with an expected return of 0.104%, standard deviation of 0.007, and alternative risk measures such as Coefficient of Variation (CV) 6.9328, Value at Risk (VaR) of -0.99%, and Conditional Value at Risk (CVaR) of -1.44%, which are lower than those of single-sector portfolios. Visualization of the efficient frontier curve confirms that the combined portfolio offers better results in terms of risk and return. The results of this study indicate that cross-sector diversification can significantly reduce risk and prevent significant losses.

This research investigates the effect of fundamental factors, namely the current ratio, debt to equity ratio, and return on equity on stock returns of mining firms listed on the Indonesia Stock Exchange (IDX) during 2021–2023. The research highlights the utility of understanding a firm’s financial performance in guiding investment selection within the capital market. Although the mining industry contributes significantly to Indonesia’s economy, stock movements in this sector are often subject to uncertainty due to market fluctuations and commodity price volatility. This research utilizes secondary data from annual financial statements and stock price records of 51 IDX-listed mining companies over the study period. Panel data regression, combined with descriptive and quantitative statistical techniques, was employed using E-Views 12 software. The findings reveal that stock returns are significantly influenced by the current ratio, debt to equity ratio, and return on equity. These results provide useful insights for investors, financial analysts, and corporate management by emphasizing the function of fundamental indicators in assessing stock performance, particularly within the mining sector.

This study aims to analyze the effect of the Current Ratio (CR), Debt-to-Equity Ratio (DER), and Return on Equity (ROE) on the stock prices of healthcare companies classified as sharia-compliant on the Indonesia Stock Exchange (IDX) for the 2020–2024 period. The background of the study is motivated by notable stock price fluctuations among sharia healthcare issuers, such as the sharp decline in PT Kimia Farma Tbk and price dynamics of other issuers including KLBF, MIKA, PEHA, and SIDO. The analysis uses a quantitative approach applying Partial Least Squares – Structural Equation Modeling (PLS-SEM) implemented in WarpPLS 8.0. The results indicate that CR does not have a significant effect on stock price (p = 0.174), while DER has a negative but not statistically significant effect (p = 0.484). In contrast, ROE has a positive and significant effect on stock price (p < 0.001), making ROE the dominant factor influencing investor interest. Simultaneously, the three independent variables explain only 20.2% of stock price variation, while the remaining 79.8% is influenced by factors outside the research model. The Tenenhaus goodness of fit (GOF) value of 0.450 suggests the research model has good overall quality despite the limited explanatory power of the tested financial variables.

The COVID-19 pandemic has increased public interest in investing, especially in the banking sector, which is known for its stability. However, many investors still lack an understanding of fundamental analysis. This study aims to examine the effect of Return on Asset (ROA), Return on Equity (ROE), and Net Profit Margin (NPM) on stock prices of banking companies listed on the Indonesia Stock Exchange during the 2011–2023 period. The research used a quantitative approach with purposive sampling and multiple linear regression analysis using SPSS. The results show that ROA has no significant effect on stock prices. In contrast, ROE has a significant negative effect, while NPM has a significant positive effect on stock prices. These findings indicate that investors tend to consider net profit margins more than asset efficiency, and that high ROE may be perceived as a signal of high leverage risk. This research is expected to provide insights for investors in assessing banking performance before making investment decisions.

This study examines the impact of Market Value Added (MVA), Economic Value Added (EVA), and Financial Value Added (FVA) on stock returns in energy-sector mining companies listed on the Indonesia Stock Exchange (IDX) during 2018–2023. A quantitative approach with multiple linear regression was applied to 23 purposively selected firms based on data availability. Secondary data were obtained from annual reports and stock prices published on the IDX website. The findings show that EVA has a significant effect on stock returns (p = 0.048 < 0.05), while MVA (0.075) and FVA (0.080) are not significant individually. However, the three variables collectively influence stock returns (p = 0.031 < 0.05). The adjusted R² of 0.396 indicates that 39.6% of return variability is explained by the model, with the rest influenced by other factors. Overall, EVA emerges as the key indicator for investors in evaluating return potential, while market-based measures such as MVA are less decisive, and historical value indicators (FVA) are less statistically relevant as predictors of stock returns. From a managerial perspective, firms are encouraged to focus on capital efficiency and sustainable economic value creation to enhance their investment appeal.

The goal of this research is to explore the relationship between stock prices, liquidity, profitability, and leverage. This study focuses on transportation and logistics companies that were registered in the Indonesia Stock Exchange from 2021 to 2023. A quantitative approach was taken, utilizing secondary data derived from the annual financial statements of companies that were active during this time frame. The sample comprised 45 data points, selected using a purposive sampling technique. The independent variables include leverage, measured with the Debt to Equity Ratio (DER), profitability, assessed through Return on Assets (ROA), and liquidity, evaluated via the Current Ratio (CR). The dependent variable for this research is the stock price. The findings from this partial analysis reveal that liquidity significantly and negatively impacts stock price, with a t-count of -2.264 and a significance level of 0.029. However, the correlation between stock price and profitability was found to be insignificant, indicated by a significance value of 0.071 and a t-count of -1.853. Similarly, leverage does not significantly affect stock price, as evidenced by a t-count of -0.657 and a significance level of 0.515. Nonetheless, when considered collectively, the three factors of leverage, profitability, and liquidity do influence stock prices. According to the coefficient of determination (R2) test, these three variables account for 13.9% of the volatility in stock prices, leaving the remaining 86.1% to be attributed to external factors not examined in this study.

This study aims to analyze the influence of macroeconomic variables in the form of the dollar exchange rate, inflation, and Gross Domestic Product (GDP) on the Composite Stock Price Index (JCI) in Indonesia for the period 2010–2024. The research method used is a quantitative approach with multiple linear regression analysis using time series data obtained from Bank Indonesia, the Central Statistics Agency (BPS), and the Indonesia Stock Exchange (IDX). The data analysis technique was carried out through classical assumption tests and hypothesis testing to determine the relationship between variables. The results of the study show that partially GDP has a significant effect on the JCI, while inflation and the dollar exchange rate tend not to have a significant effect. However, simultaneously these three variables have a significant influence on the JCI. These findings show that macroeconomic stability is very important in maintaining the performance of the capital market in Indonesia and can be a reference for investors in making investment decisions. In addition, the results of the study confirm that national economic growth is the main indicator that market participants pay attention to in assessing investment prospects. Therefore, the government needs to maintain economic stability through effective and sustainable fiscal and monetary policies.

This study aims to analyze the effect of profitability, leverage, and liquidity on firm value in food and beverage sub-sector companies listed on the Indonesia Stock Exchange (IDX) for the 2020–2024 period. Profitability is measured by Return On Assets (ROA), leverage by Debt to Equity Ratio (DER), and liquidity by Current Ratio (CR), while firm value is proxied by Price to Book Value (PBV). The study employs a quantitative approach using multiple linear regression analysis. The sample consists of 25 companies selected through purposive sampling, with a total of 125 secondary data observations obtained from annual financial statements. The results indicate that, partially, profitability, financial risk, and liquidity have a positive and significant effect on firm value. Simultaneously, the three independent variables also significantly affect firm value, with an adjusted R² of 43.4%, meaning that 56.6% of the variation in firm value is explained by other factors outside the model. These findings support agency theory and signaling theory, which suggest that strong financial performance, optimal debt management, and adequate liquidity provide positive signals to investors, thereby enhancing firm value.

This research examines the analysis of Return on Equity (ROE), Quick Ratio (QR), and Debt to Equity Ratio (DER) on corporate valuation, as assessed by Price-to-Book Value (PBV), within technology firms listed on the Indonesia Stock Exchange (IDX) during the period from 2022 to 2024. The primary aim of this investigation is to ascertain the effects of profitability, liquidity, and leverage both in isolation and in conjunction on market valuation in an industry characterized by innovation and intangible assets. This research employs panel data regression analysis utilizing EViews 13 as the quantitative methodology. The findings reveal that ROE significantly enhances PBV, indicating that investors place considerable importance on firms that are capable of generating substantial returns on equity for shareholders. Conversely, QR and DER appear to have no discernible impact on PBV. This observation can be attributed to the unique nature of technology companies, wherein investors prioritize factors other than short-term liquidity and leverage. Nonetheless, when assessed collectively, the three metrics illuminate the variations in corporate value. These results suggest that while financial stability indices exert a positive yet comparatively subdued effect on investor sentiment within the technology sector, profitability remains a paramount determinant. The study elucidates the financial determinants that influence corporate value in innovation-driven industries, providing valuable insights for managers and investors alike.

This study aims to examine the effect of profitability ratios, namely Earnings per Share (EPS), Net Profit Margin (NPM), Return on Assets (ROA), and Return on Equity (ROE), on the stock price of PT Ciputra Development Tbk during the 2016–2023 period. The research employs a quantitative approach with a causal research design using secondary data derived from quarterly financial statements and stock closing prices published by the Indonesia Stock Exchange. The data were analyzed using multiple linear regression, supported by classical assumption tests, partial hypothesis testing (t-test), simultaneous testing (F-test), and the coefficient of determination (R²). The results show that EPS, NPM, and ROA do not have a significant effect on stock prices, while ROE has a positive and significant effect. Simultaneously, all profitability variables do not significantly influence stock prices. The coefficient of determination indicates that profitability ratios explain a relatively small proportion of stock price variation, suggesting that stock prices in the property sector are influenced more by external and market-related factors than by short-term profitability indicators. These findings imply that ROE is the most relevant profitability indicator for investors in assessing property sector stocks, while other profitability ratios play a limited role.

This study analyzes the effect of Bitcoin prices, the LQ45 Index, mutual fund net asset value (NAV), and the net profit margin (NPM) of gold mining companies on the price of gold as a safe haven asset within the context of the Indonesian financial market. Gold is often seen as a safe haven asset that is the primary choice of investors when economic uncertainty increases, but the relationship between gold and various other investment instruments still requires further study. This study uses a multiple linear regression method with a robust standard errors approach to analyze 420 monthly and quarterly data observations during the 2018-2022 period. The results of the study found that the price of Bitcoin and the NPM of gold mining companies had a significant positive influence on the price of gold, while the LQ45 Index had a significant influence effect. Meanwhile, the NAV of mutual funds showed a significant positive influence that was not in line with the initial hypothesis. These findings indicate that gold does not always function absolutely as a safe haven asset, as its role is contextual and still influenced by the dynamics of other investment instruments such as digital assets, stock markets, and mutual funds. The study's results make an important contribution to financial literature by proving that the safe haven characteristics of gold are complex and dynamic, so investors need to consider various factors and market conditions before allocating investments to gold as a hedging strategy in their portfolios.

This study aims to estimate changes in the Indonesian Sharia Stock Index (ISSI) from 2020 to 2025 using the Autoregressive Integrated Moving Average (ARIMA) model. The growth of the Islamic stock market in Indonesia has increased rapidly, driven by public awareness of investments that follow sharia principles, as well as changes in macro and microeconomic conditions, especially during the COVID-19 pandemic which has had a significant impact on the financial market. This study relies on monthly ISSI data taken from official sources and analyzed with a quantitative approach using the time series method using EViews version 13 software. Statistical analysis and stationarity tests indicate that the ISSI data exhibits an increasing trend pattern and quite high volatility, so that a differentiation process is necessary to achieve stationarity. Based on the results of model testing and the selection of optimal information criteria, the ARIMA (1,1,1) model was selected as the most appropriate to capture the autocorrelation pattern and produce accurate short-term predictions. Projections indicate a stable growth trend until the end of 2025, with an estimated index of more than 8.3 million. The findings of this study indicate that the ARIMA model is an effective tool for forecasting ISSI movements and can be a strategic consideration for investors, financial institutions, and policymakers in developing sustainable investment strategies in the Indonesian Islamic stock market.

This study aims to see the effect of Debt to Equity Ratio (DER) and Return on Assets (ROA) on Stock Price in PT. Wilmar Cahaya Indonesia, Tbk which is listed on the IDX during the period 2015–2022. The data used in this study is in the form of the company's annual financial statements obtained through secondary sources. This study uses a quantitative approach with multiple linear regression analysis methods, while data processing is carried out using the SPSS application. The results of the study show that partially the Debt to Equity Ratio (DER) variable has a negative effect on the Share Price, while the Return on Assets (ROA) does not have a positive effect on the company's Share Price. However, the results of the simultaneous test show that DER and ROA together have a positive and significant influence on the Stock Price. These findings provide an idea that the combination of capital structure and profitability remains an important indicator in assessing the performance of a company's shares even though their partial relationships show different tendencies. In addition, this research can be a reference for investors in considering the company's fundamental condition before making investment decisions, as well as provide additional insights for management in managing the capital structure more optimally.