Influence Stock Prices Research Articles

Key Drivers of Stock Price Movements: Financial and Economic Indicators in Unilever Indonesia (2014–2023)

Multinational corporations are critical in ensuring financial market stability and boosting corporate performance, mainly through job creation and increased productivity. These contributions positively influence investor confidence and significantly impact stock market performance. As one of the leading multinational companies, PT Unilever contributes substantially to Indonesia's economic development. However, in recent years, PT Unilever has faced a notable decline in its stock prices. Such a decline can undermine investor trust, affecting the company’s investment strategies. For this reason, examining factors that influence stock price movements, including financial ratios and macroeconomic variables, becomes essential. This research investigates the influence of financial ratios and macroeconomic indicators on PT Unilever Indonesia Tbk's stock price fluctuations in 2014–2023. The variables analyzed include the Current Ratio (CR), Earnings Per Share (EPS), inflation, interest rates, and Gross Domestic Product (GDP). Using secondary data and a multiple linear regression approach, the study reveals that EPS and inflation positively and significantly impact stock prices. At the same time, interest rates and GDP exhibit a negative and significant effect. On the other hand, the CR variable does not significantly affect stock price movements

Pengaruh Struktur Modal, Profitabilitas, Dan Price To Book Value Terhadap Harga Saham

The purpose of this research is to analyze the correlation between capital structure, profitability, and stock market value, proxied by the price-to-book ratio. The capital structure variable is measured using DER, while profitability is measured using the ROA. In this study, the data used comes from the financial statements of property and real estate companies listed on the IDX during the period of 2020 to 2023. This study applies multiple linear regression analysis with the help of SPSS to process data obtained from 22 purposively selected companies over four years. The research concludes that capital structure and profitability are crucial factors that can influence stock prices. These results indicate that companies need to focus on improving profitability and maintaining healthy debt management to enhance their value in the eyes of investors. Additionally, investors should not rely solely on the PBV when evaluating investment prospects.

DO STOCK INVESTMENT STRATEGY AFFECT STOCK PRICES? A CASE STUDY OF SHARIAH-COMPLIANT COMPANIES IN MALAYSIA

This study aims to analyze how the stock market investment strategy using fundamental analysis affects stock prices. Fundamental analysis is an approach used to assess the intrinsic value of a stock based on the company's fundamental factors, including financial statements. This study utilizes historical stock data from 170 Shariah-compliant publicly listedcompanies on Bursa Malaysia and applies various financial ratios and stock valuation methods, such as net profit margin (NPM), price earnings ratio (PER), current ratio (CR), dividend payout ratio (DPR), earnings per share (EPS) and firm size (FS). The sample consists of 170 Shariah-compliant firms from all sectors except for the financial sector of Bursa Malaysia and 20 years maintained listed as status of Shariah-compliant Firms. This research employs panel data estimation techniques for regression analysis with robust panel data estimation technique for statistical inferences. The results indicate that PER, CR, EPS and FS have a positive effect on the stock price. This result confirms that higher in price earnings ratio, liquidity, earnings per share and firm size can increase stock price. The results also found that that NPM and DPR are negatively significant effect to the stock price of Shariah-compliant companies in Malaysia. This research contributes to the understanding of how fundamental analysis methods can be effectively applied in stock market strategies to influence stock prices. It aims to broaden investors' horizons by helping them identify the best strategies using fundamental analysis to generate profits from stock market investments and contribute to economic growth by strengthening economic conditions. This research is among the few studies examining the impact of stock investment decisions using a fundamental analysis approach on the stock prices of Shariah-compliant listed companies in Malaysia.

THE INFLUENCE OF RETURN ON ASSETS, RETURN ON EQUITY, AND EARNINGS PER SHARE ON STOCK PRICES IN TECHNOLOGY SECTOR COMPANIES LISTED ON THE INDONESIA STOCK EXCHANGE (IDX)

Stock price is one of the important indicators of a company's success. The purpose of this study is to determine the influence of Return on Assets (ROA), Return on Equity (ROE), and Earnings Per Share (EPS) on stock prices. The data analysis method used in this study is quantitative analysis, which involves analyzing numerical data and using statistical calculations to test hypotheses. The quantitative data analysis methods applied in this research include descriptive statistics tests, classical assumption tests, and multiple linear regression analysis. Out of a population of 22 companies, a sample of 15 companies was selected for this study, covering the period from 2021 to 2023. The data analysis results indicate that Return on Assets (ROA) does not have a significant effect on stock prices, as indicated by t-value < t-table (0.824 < 2.018) with a significance of 0.415 > 0.05. Similarly, the analysis shows that Return on Equity (ROE) also does not significantly influence stock prices, with a t-value < t-table (-0.919 < 2.018) and a significance of 0.364 > 0.05. It can be concluded that neither ROA nor ROE significantly impacts stock prices. However, Earnings Per Share (EPS) does have a significant influence on stock prices, with a significance of 0.020. Future researchers are encouraged to conduct studies using different variables, such as ROA, ROE, and EPS, and to expand the sample size to achieve more in-depth research.

Inhabiting influence of digital finance on stock price synchronicity

We examine how digital finance can influence stock price synchronicity in China for the period of 2011–2021. Results suggest that the digital finance index, coverage breadth, usage depth, and digitalization level can significantly reduce stock price synchronicity. The possible channels of this linkage are information opacity and stock price crash risk. We find that digital finance is effective in reducing stock price synchronicity only in state-owned enterprises and large firms. The results are robust and immune to reverse causality and endogeneity and have important implications for investors and policymakers.

Assessing the Effects of Cyber Attacks on Financial Markets

Cyber-attacks on financial markets have emerged as a significant threat to global economic stability, disrupting market operations, compromising sensitive data, and undermining investor confidence. This study explores the multifaceted impact of cyber-attacks on financial markets, examining both the immediate and long-term effects on market performance, regulatory response, and overall market resilience. By analyzing recent incidents, this research highlights how cyber-attacks influence stock prices, trading volumes, and market volatility, shedding light on the vulnerabilities within financial systems. Findings suggest that cyber threats not only impact individual institutions but also ripple through interconnected markets, amplifying financial risk on a broader scale. The study concludes with recommendations for strengthening cybersecurity measures in financial markets to enhance resilience and mitigate potential losses from future cyber incidents.

How does finance and accounting supervision affect stock price crash risk?

As an essential component of China's national supervision system, finance and accounting supervision plays an important role in regulating financial order, promoting economic development, and maintaining social stability. This study selects the special action of finance and accounting supervision as a quasi-natural experiment and conducts a difference-in-differences estimation to alleviates the problem of endogeneity. Using a sample of A-share listed firms from 2007 to 2013, this study examines the effect of finance and accounting supervision on stock price crash risk in the context of China. Our results indicate that firms subject to finance and accounting supervision are less likely to suffer a stock price crash. We explore the underlying mechanism and find that finance and accounting supervision mitigates firms' information asymmetry, thereby reducing future stock price crash risk. We also find that the negative effect of finance and accounting supervision on stock price crash risk is more pronounced for highly financialized firms, firms with larger management shareholding, and firms with poorer stockholder checks and balances. This study has significance for enriching research on the factors influencing stock price crash risk and assessing the effectiveness of finance and accounting supervision in the capital market.

The Relationship Between Dividend Announcements And Ex-Dividend Dates On Stock Prices Before And During The Pandemic In The Indonesian Stock Market

The ongoing discourse surrounding the ramifications of dividend announcements and ex-dividend dates on stock prices persists, particularly against the backdrop of the Covid-19 pandemic's significant upheaval on the Indonesian economy, including its stock market. Thus, this study endeavors to delve into the intricate dynamics of how dividend announcements and ex-dividend dates influence stock prices, coupled with an exploration of investor reactions amidst the pandemic. Focusing on companies listed on the IDX that dispensed dividends from 2018 to 2021, this research adopts a purposive sampling approach, yielding a robust dataset comprising 181 observations. Leveraging descriptive analysis and hypothesis testing via SPSS software, the study unravels compelling insights. Notably, it unveils a positive nexus between dividend announcements, the pandemic, and stock prices. Intriguingly, however, the ex-dividend date appears to exert negligible impact on stock prices, challenging conventional wisdom. By shedding light on these dynamics, this research contributes to a deeper understanding of market behavior amidst dividend-related events and the unprecedented disruptions posed by the Covid-19 pandemic, offering valuable insights for investors and policymakers.

Predicting Market Share Patterns using LSTM

Forecasting stock prices is a significant challenge in the financial sector, marked by its complexity and the impact of numerous variables. In this paper, we undertake a comprehensive investigation into how machine learning algorithms can be effectively applied to address this challenge. Our main goal is to clarify the methodologies and strategies that can enhance the accuracy of stock market predictions. We explore the complex process of predicting stock values and scrutinize the various machine learning algorithms that have been suggested and employed for this purpose. By critically evaluating these algorithms, we aim to provide insights into their individual strengths and weaknesses, ultimately helping the reader make an informed decision about the most appropriate algorithm for their specific forecasting requirements. Beyond algorithm selection and attribute analysis, our review also considers external factors that can significantly influence stock prices. These factors include a broad range of variables, such as economic conditions, geopolitical events, corporate news, and market sentiment. Understanding the interaction between these external elements and stock market dynamics is essential for developing more robust and reliable prediction models.

Decoding Stock Price Movements: How Net Profit Margin and Debt-to-Equity Ratio Drive Value, with Earnings per Share as the Game-Changer

This research investigates the relationships between Net Profit Margin (NPM), Debt-to-Equity Ratio (DER), Earnings per Share (EPS), and stock prices within the context of the Indonesian stock market. Utilizing a quantitative analysis approach, the study employs panel data regression to assess the statistical significance of these financial metrics on stock valuations. The findings reveal that NPM has a meaningful and statistically significant positive impact on stock prices, indicating that higher profit margins are associated with increased investor confidence and market valuation. Conversely, the results show that DER does not significantly influence stock prices, suggesting that investors may perceive high debt levels as a risk that diminishes stock value. Furthermore, the study finds that EPS does not moderate the relationship between NPM and stock prices, nor does it strengthen the effect of DER on stock valuations. These conclusions contribute to understanding financial determinants in stock price movements, emphasizing the importance of profit margins while highlighting the limited role of leverage and earnings per share in this context. The research provides recommendations for investors and corporate managers and suggests avenues for future studies, including broader geographic comparisons and integrating qualitative factors into stock valuation analysis.

A Stock Prediction Method Based on Multidimensional and Multilevel Feature Dynamic Fusion

Stock price prediction has long been a topic of interest in academia and the financial industry. Numerous factors influence stock prices, such as a company’s performance, industry development, national policies, and other macroeconomic factors. These factors are challenging to quantify, making predicting stock price movements difficult. This paper presents a novel deep neural network framework that leverages the dynamic fusion of multi-dimensional and multi-level features for stock price prediction, which means we utilize fundamental trading data and technical indicators as multi-dimensional data and local and global multi-level information. Firstly, the model dynamically assigns weights to multi-dimensional features of stocks to capture the impact of each feature on stock prices. Next, it applies the Fourier transform to the global features to capture the long-term trends of the global environment and dynamically fuses these with local and global features of the stocks to capture the overall market environment’s impact on individual stocks. Finally, temporal features are captured using an attention layer and an RNN-based model, which incorporates historical price data to forecast future prices. Experiments on stocks from various industries within the Chinese CSI 300 index reveal that the proposed model outperforms traditional methods and other deep learning approaches in terms of stock price prediction. This paper proposes a method that facilitates the dynamic integration of multi-dimensional and multi-level features in an efficient manner and experimental results show that it improves the accuracy of stock price predictions.

The Influence of Economic Variables on Stock Prices of Telecommunications Companies

The general background fluctuation of stock prices is a critical concern for investors, particularly in dynamic economic environments where various indicators can significantly impact financial performance. The specific background of this study focuses on the telecommunications sector, which has been increasingly influenced by economic variables such as the Inflation Rate, SBI Interest Rate, Earnings Per Share, Rupiah Exchange Rate, and Company Fundamentals. Despite existing research, there is a knowledge gap regarding how these factors collectively influence stock prices in publicly listed telecommunications companies. This study aims to investigate the effects of these economic variables on stock prices from 2020 to 2023, utilizing a quantitative approach with secondary data obtained from annual financial reports of 16 companies. The results demonstrate that all examined variables—Inflation Rate, SBI Interest Rate, Earnings Per Share, Rupiah Exchange Rate, and Company Fundamentals—significantly affect stock prices. The novelty of this research lies in its comprehensive analysis of the interplay between these economic indicators specifically within the telecommunications sector. The implications of these findings suggest that investors and policymakers should consider these economic factors when making investment decisions, thereby enhancing their financial strategies and contributing to a more robust understanding of stock market dynamics in the telecommunications industry. Highlights: All examined economic variables significantly affect stock prices. The study analyzes data from 16 publicly listed telecommunications companies. Findings enhance investment strategies and understanding of market dynamics. Keywords: Inflation, Interest Rate, Earnings Per Share, Exchange Rate, Stock Price

MACROECONOMIC ASPECTS IN INFLUENCING STOCK PRICE MOVEMENT ON THE INDONESIAN SHARIA STOCK INDEX 2018-2022

This study aims to analyze the influence of macroeconomic variables and world oil prices in influencing stock price movements on the Indonesian Sharia Stock Index (ISSI) in 2018-2022. In this case, stock price movements can be influenced by several factors, one of which is macroeconomics. The research methodology used in this study is to use a quantitative research approach and secondary data type, with quarterly samples from each year 2018 to 2022 which amounted to. The research model carried out is log linear regression panel data analysis conducted through the chow test and classical assumptions using Eviews 10 tools. Based on the results of this study, it states that partially shows the variables of Inflation, BI Interest Rate Economic Growth (GDP) and Money Supply. While simultaneously all variables did not have a significant effect on the Indonesian Sharia Stock Index (ISSI).

The Link Effect of ESG Score, Stock Price Volatility, and Tax Payment: Doing Well while Doing Good

This study aims to identify how environmental, social and governance (ESG) performance influences stock price volatility, explicitly focusing on the moderating role of tax engagement. ESG performance is measured by an ESG Score calculated from the weighting of three dimensions: environmental, social and governance. Stock price volatility is measured by the degree of price variations over 12 months based on the last 52 weeks’ prices. A sample of Indonesia-listed firms is used, with 770 observations from 2023. The results show that the ESG Score negatively impacts stock price volatility, which is more significant in the social dimension than in the environmental and governance dimensions. In addition, the tax payment variable moderates the relationship and increases the effect of the ESG Score on stock price volatility. These findings suggest that ESG practices and tax transparency are ethical elements and critical components for financial stability, promoting the high-quality development of listed firms. This study is significant for firms, regulators, policymakers and investors. Overall, it underrates the importance of firms adopting ESG activities and engaging in tax management to mitigate risks and maintain viability in the contemporary business environment. This study provides new empirical evidence regarding the factors driving corporate stock price volatility. In addition, it offers pertinent policy recommendations for businesses and governments regarding the significance of ESG investments.

Pengaruh Earning Per Share, Return on Equity dan Price to Book Value Terhadap Harga Saham Periode 2019-2021 (Studi Kasus pada Perusahaan Sub Sektor Otomotif dan Komponenya di BEI)

The phenomenon that occurred during the Covid-19 pandemic that spread in Indonesia in early 2020 has an impact on all aspects of life, including the capital market. The spread of Covid-19 in Indonesia has caused fear for investors so that many of them choose to leave risky assets. This affects the movement of the Composite Stock Price Index (IHSG). The problem in this study aims to determine the effect of EPS (Earning Per Share), ROE (Return on Equity) and PBV (Price to Book Value) on stock prices in automotive companies listed on the IDX for the period 2019 - 2021. The type of research used is quantitative research with secondary data sources. The population in this study is automotive companies listed on the Indonesia Stock Exchange for the period 2019 - 2021 as many as 15 companies. Sampling using purposive sampling technique as many as 10 companies that meet the criteria. Data analysis techniques using multiple linear regression analysis techniques. The results of the study indicate that EPS can influence stock prices, and ROE also influences stock prices, and PBV influences company value. Simultaneously, the variables EPS (Earning Per Share), ROE (Return on Equity) and PBV (Price to Book Value) influence stock prices.

Research on the Dynamics of Word-of-Mouth Influencing Stock Prices

Word-of-mouth (WOM) can be considered one form of public opinion, reflecting consumers’ views towards product or service quality. With the development of social media, WOM holds influence over investors and subsequently impacts the stock prices of companies. The purpose of this study is to uncover the dynamics encompassing the factors that influence WOM, its propagation mechanisms, and the consequential impact on reality illustrated through fluctuations in stock prices. The mathematical model to describe the whole process can be separated into two components: information propagation model and stock price fluctuation model. The cumulative abnormal return (CAR) is used to demonstrate fluctuations in stock prices. Utilizing a Lyapunov function, it is proven that the equilibrium point of the model is globally asymptotically stable. As for the real world, it suggests that WOM will eventually prevail online, leading to fluctuations in stock prices. Based on the event study method, the empirical examination of 43 real events shows that our model can effectively predict the CAR and reflect the influence on stock prices caused by WOM in real-world scenarios.

Pengaruh Return On Assets (ROA), Return On Equity (ROE), Earning Per Share (EPS) dan Debt to Equity Ratio (DER) Terhadap Harga Saham

This research aims to analyze the influence of Return On Assets (ROA), Return On Equity (ROE), Earning Per Share (EPS), and Debt to Equity Ratio (DER) on share prices in 34 LQ45 index companies during 2018–2020. The research method used is associative with the population of companies listed on the LQ45 index of the Indonesian Stock Exchange. Data collection was carried out through annual financial reports from 34 companies during the 2018-2020 period. The sampling method uses purposive sampling with certain criteria, and data analysis is carried out using multiple linear regression using SPSS software. The research results show that these four variables simultaneously influence stock prices. Specifically, Earning Per Share (EPS) has a positive influence, while Debt to Equity Ratio (DER) has a negative influence. Return On Assets (ROA) and Return On Equity (ROE) do not have a significant effect on stock prices.

Pengaruh ROA, ROE, dan EPS Terhadap Harga Saham Perbankan Buku III Yang Tercatat di BEI

The investment in the capital market is currently increasing among the public, emphasizing the urgency of providing financial literacy to enable individuals to make informed and intelligent investment decisions in the capital market. BUKU III was selected due to the relatively low per-share stock prices of the existing banks, allowing the public to have higher purchasing power. ROA, ROE, and EPS were chosen as the factors under review due to their widespread availability in financial reports, serving as a reference for the public in determining their investment choices. Previous studies focused on the impact of ROA, ROE, and EPS on stock prices in the BUKU IV (Tahir, Djuwarsa, and Mayasari, 2021). Their findings revealed that ROA had no significant independent influence on stock prices. Conversely, ROE and EPS, independently, significantly influenced stock prices in BUKU IV banks. Additionally, the simultaneous impact of ROA, ROE, and EPS affected the stock prices of BUKU IV banks. This study aims to explore whether ROA, ROE, and EPS exert influence on the BUKU III banks stock prices listed on the Indonesia Stock Exchange. The research method employed is the hypotheticodeductive method, utilizing quarterly data from 2018 to 2022, with a sample size of 5 companies. Data were collected from Stockbit, and the analysis methods used included t-tests, F-tests, and multiple linear regression analysis using Microsoft Office Excel and SPSS tools. The results indicate that ROA, ROE, and EPS do not have a partial or simultaneous impact on the stock prices of BUKU III banks.

Resilience and Adaptation: Investment Metrics of Indonesian Healthcare Companies Before and During the COVID-19 Pandemic

The impact of dividend policy and stock valuation (price earning proportion and price to book value) on the prices of healthcare industry stocks listed on the Indonesia Stock Trade somewhere in the range of 2016 and 2021 is examined in this study. The research data used in this quantitative analysis are secondary data. This study included eighteen healthcare sector companies in its sample. Purposive sampling is the methodology used in this study, and SPSS 24 is the analysis tool. We explained the relationship between stock prices, dividend policy, and stock valuation. We order the variables into pre-pandemic and during-pandemic categories subsequent to testing them for like clockwork. That's what the experimental results demonstrate, for all periods, the earning-per-share notation has a significant impact on stock prices. Stock valuation, on the other hand, has a significant impact on stock prices, as does the final dividend policy with dividend payout proportion and dividend per share. Meanwhile, results from the pre-pandemic time frame indicate that EPS and DPR didn't significantly influence results; results from the pandemic time frame indicate that stock valuation didn't significantly influence stock price. This research provides fresh insights into what the recovery of economic exposure means for corporate conduct in Indonesia, where persistent financial and economic pressures from stock market unpredictability give substantial sources of uncertainty.

Corporate earnings, dividend payments, and stock price behavior of manufacturing firms listed in Nigeria

The purpose of the study is to investigate the effects of corporate earnings and dividend payments on the stock price behaviour of manufacturing firms in Nigeria between 2013 and 2022. The study adopted an ex-post facto research design, and deployed Generalised Method of Moments (sys-GMM) and Granger causality tests for the data analysis. The two-step system GMM is used to control for omitted variables such as bias, unobserved panel heterogeneity or heteroscedasticity, autocorrelation within panels or groups, endogeneity issues, and measurement errors in the data. Findings show that share price (SP) and its predictors yield valuable insights into the factors influencing stock valuation. Dividend per share (DPS) emerges as a significant positive predictor, suggesting a notable impact on share price. Firm size (FSZ) proves to be a statistically significant predictor, indicating that the size of a firm plays a role in influencing stock prices, with larger firms associated with a decrease in share price. Conversely, Earnings per Share (EPS) and Dividend Yield (DY3) do not exhibit statistical significance, suggesting limited predictive power in the model. By way of conclusion, the study provides an understanding of the factors influencing share price behavior within the Nigerian manufacturing sector and the positive impact of past performance, particularly lagged share prices, confirming the persistence of stock market trends. The practical implications of this study are that it underscores the understanding of financial dynamics in emerging economies, particularly in the context of manufacturing firms in Nigeria.