Stock Price Valuation Research Articles

Perancangan Strategi Perusahaan Berdasarkan Rasio Finansial pada PT Fajar Surya Wisesa Tbk Sebelum dan Sesudah Munculnya Covid-19

This study aims to design strategic recommendations based on financial ratios at PT Fajar Surya Wisesa Tbk before and after Covid-19. This research is motivated by a decline in global paper demand and production as well as a decline in the value of stock prices in the manufacturing sector. Particularly at PT Fajar Surya Wisesa Tbk. In this study, data was collected using the financial reports and stock prices of PT Fajar Surya Wisesa Tbk 12 quarters before the emergence of Covid-19 (April 2017–March 2020) and 12 quarters after the emergence of Covid-19 (April 2020 – March 2023). The data processing method used is the Wilcoxon Signed Ranks Test. The results of the Wilcoxon signed ranks test in the form of 9 financial ratio variables found a significant difference between the values before and after Covid-19. Meanwhile, for the 6 other financial ratio variables and stock prices, there is no significant difference between the values before and after Covid-19. After that, strategic recommendations are given based on test results, and a mapping is carried out on the Strengths and Weaknesses quadrants to get recommendations for strategies that are suitable for the company. In this study the authors provide recommendations on strategies that can be implemented by companies to improve financial performance.

The Roadmap of a Cash Dupont Analysis and Its Impact on Stock Valuation Strategy

It is a common belief that capital intensive corporations are associated with relatively low profit margins. They operate in environments where it may be a struggle to keep returns in excess of their capital costs. This further implies a possible decline in stock value because of these lower margins. This paper extends the financial literature on the effects of capital intensity on firm performance through the introduction of the Cash DuPont Model in conjunction with a Monte Carlo Simulation. The model’s use of the free cash flow to equity (FCFE), cash conversion factor (CCF), and resulting Cash ROE ultimately leads to the determination of the fair price to book value multiple. All of these data metrics are blended into a process of stock price valuation that explains both the possibility and probability of the mispricing of a stock. The results reveal that a capital-intensive firm can show undervalued tendencies despite low profit margins.

Is There A Conflict Of Interest In Indonesia’s Soe Investment Decision?

In financial management, the Director of State-Owned Enterprises (SOEs) in Indonesia synergizes with the Ministry of SOE to make investment decisions. One of the most common types of investment in SOEs is the purchase of shares in private companies. Through buying shares, SOEs can expand their business lines and project bigger profits. However, it is often found that the decision to purchase private company shares is made by SOEs due to a conflict of interest. This paper aims to determine the level of involvement of conflicts of interest in the decisions of SOEs in Indonesia to invest in the purchase of shares of private companies. Due to data limitations, the authors used a qualitative technique with an explanatory case study to meet the research aims. The analysis tested of 14 Indonesian SOEs' investment decisions when investing in the purchase of shares in private companies during the 2013–2022 period. The findings show allegations of conflicts of interest in several share investment decisions made by SOEs in Indonesia. This conflict of interest can occur because of a family relationship between the Board of Directors of SOEs and the management of private companies. In addition, there is also a political-party relationship between the parties involved. These findings can help several parties, including SOE and the Ministry of SOE, better understand the limits of investment that can be made. In the long run, the Ministry of SOE, as the supervisor of SOEs, can establish an early warning system to determine whether or not the investments made are appropriate. Most of the previous research only examined the effects of a company's investment and its impacts. It explores the company's stock price valuation process. No research has been found that specifically discusses SOE investment in Indonesia in private company shares.

The risks of a collapse in the value of stock prices and its impact on the assessment of banking stability: An analytical study of a sample of Iraqi banks for the period 2015-2020

The risks of a collapse in the value of stock prices and its impact on the assessment of banking stability: An analytical study of a sample of Iraqi banks for the period 2015-2020

Relationship between Wastewater Quality and Corporate Stock Price

Almost all industrial players handle wastewater treatment in one way or another by themselves, no matter the industry or company’s size. Some companies have wastewater treatment plants, and others are considering investments for construction or modernisation. Occasionally, industrial wastewater is discharged to a municipal wastewater treatment plant; however, it must sometimes be pre-treated. Corporate wastewater quality is imperative for environmental responsibility, corporate legitimacy and financial performance. This paper examines the relationship between the reduction of hydrocarbon content of offshore and onshore wastewater and the stock price presented in TotalEnergies. The data on hydrocarbon content reduction in offshore and onshore wastewater discharge was collected from the TotalEnergies 2022 Sustainability and Climate Progress Report. In addition, the data on TotalEnergy’s stock price was collected from the FusionMedia online stock price index. Data was analysed quantitatively through the application of a graphical approach. Findings from the graphical analysis of data depict two important dimensions of the stock value effect. Firstly, the results show a corresponding relationship between the reduction in the hydrocarbon content of wastewater and an increase in the stock price value of TotalEnergies. Secondly, the results show that the increase in stock price value continues even beyond the times of hydrocarbon reduction, which shows that investors compensate the company for its previously good performance in hydrocarbon reduction. This legitimacy-ingrained performance shows that hydrocarbon reduction protects the company’s value even during uncertainties and/or hindrances in wastewater quality. Based on this finding, the paper develops an inductive hypothesis, opening a new research agenda. The findings are of practical significance for industrial hydrocarbon content reduction and the attraction of short- and long-term financial value to the industry.

Predicting stock market by sentiment analysis and deep learning

The stock market may be unpredictable; understanding when to purchase and sell can greatly assist businesses and individuals in maximizing profits and minimizing losses. Many companies have previously modified time-series analysis, a data mining technique, to forecast stock price movement. The idea of textual data mining has recently come up in debates about stock market forecasts. In this study, five of the largest firms’ historical stock prices were used to train two deep learning models—long short-term memory (LSTM) and one-dimensional convolutional neural network (1D CNN), then the results of all the models were compared. To connect price value fluctuations with the general public, sentiment scores were offered in addition to stock price values by employing natural language processing techniques (TextBlob) to tweets.

Stock Price Prediction Using Machine Learning

Abstract—As the need for precise and fast stock price projections is growing as financial markets continue to become more complicated. The use of Long Short-Term Memory (LSTM) neural networks for stock price forecasting is investigated in this paper. LSTMs are especially important for time series prediction tasks because they are good at capturing temporal dependencies in sequential data. In this study, LSTM models are trained and evaluated using historical stock price data while taking into account a variety of input features and hyperparameters. By contrasting the performance of LSTM models with conventional machine learning techniques, the advantages and disadvantages of each methodology are brought to light. The findings showed that LSTM models offer greater predictive capabilities, highlighting its potential in improving investment decisions and furthermore, the analysis of IBM Company Stock Price Values and model performance configurations add to the expanding body of knowledge about using deep learning approaches for financial forecasting. Keywords—Machine Learning, Neural Networks, RNN, Linear Regression, LSTM, Supervised Learning.

MODEL VOLATILITAS SAHAM LQ45 DENGAN PENDEKATAN MARKOV-SWITCHING GARCH

Financial markets have an important role in the economy of a country including Indonesia. One of the activities chosen by investors in the financial market is investing. In the world of investment, especially in stocks, there is a phenomenon of volatility, which is a situation where a stock price value increases and decreases. Volatility in this financial market is something that is very interesting for investors because of its impact on the existence of global financial markets. The purpose of this study is to model the LQ45 index data using a model that can overcome the problem of heteroscedasticity and changes in data structure. The commonly used model for heteroscedasticity problem is ARCH/GARCH. Furthermore, a model that can account for structural changes is the Markov Switching model. The model that can overcome the problem of heteroscedasticity as well as structural changes is the MS GARCH model. The financial data used in this study are daily data for the LQ45 Index from 10 June 2019 to 28 May 2020. Based on the results of data analysis conducted using the MS GARCH model is the best model in modelling the volatility of the LQ45 index. The best model selection uses the criteria for the AIC and BIC values with the smallest value

Comparative Analysis of Sharia Stock Prices and Returns in the Health Sector Before and During the Covid-19 Pandemic

Determining the Covid-19 pandemic as a national non-natural disaster in Indonesia impacts all sectors, including the Islamic capital market. The covid-19 pandemic can send a negative signal to investors, it is expected to cause a decrease in stock prices, trading volume, and abnormal stock returns. This study aims to analyze the impact of the Covid-19 pandemic on price changes and Islamic stock returns of PT. Kalbe Farma, Tbk. The analysis technique used is the paired sample T test for normally distributed data and the Wilcoxon signed rank test for abnormally distributed data. The results of the study show that the price of sharia stocks in the health sector did not experience a significant difference either before or during the Covid-19 pandemic. Likewise, the statistical test results show that Islamic stock returns did not experience a significant difference before and during the Covid-19 pandemic, meaning that this variable did not react negatively to the Covid-19 pandemic. The implication of this research is that PT. Kalbe Farma, Tbk is expected to try to maintain stock price stability in order to maintain investor confidence and interest because a stable stock price value can increase stock returns. Share prices are influenced by the demand and supply of services or products traded by the company so PT. Kalbe Farma, Tbk can maximize performance, product innovation, and momentum to achieve optimal returns. It is hoped that this research can become additional literature material on the topic of Islamic stock analysis during the Covid-19 pandemic.

Pengaruh Inflasi, Suku Bunga, dan Nilai Tukar Terhadap Harga Saham Perusahaan Pertambangan Periode 2019-2021

The development of world capital markets has a positive impact on the country's economy. In the capital market there is stock trading which helps companies in obtaining capital. The price of shares that are traded has different price changes that can go up or down. The movement of stock prices every day increases or decreases. Factors that can cause price changes are macroeconomic conditions, such as economic inflation, changes in exchange rates and interest rates. The purpose of this research was to describe the effect of exchange rates, interest rates and inflation on the value of stock prices in a mining business entity for the 2019-2021 period. In the research conducted, there are several supporting data, namely secondary data, which is data obtained from an official website, such as the website of the Central Statistics Agency (BPS), IDX, and BI. Data were obtained using a purposive sampling technique with criteria for 2019 to 2021. Testing variable data in this study used the eviews 12 application. The test used was the panel data test, in the form of a partial test (t test), simultaneous test (f test), and a coefficient of determination (R2). Then in carrying out a research conducted, it is known that inflation has an effect but not significantly on the share price of a mining business entity, interest rates do not have a significant effect on the share price of a mining company, and the exchange rate has a significant effect on the share price of a mining company. 
 Keywords: Inflation, Interest Rates, Exchange Rates, Stock Prices

Formation of Optimal Portfolio on JII Stock using Sharpe, Treynor, and Jensen Indices during the Period of 2018-2023

Investment is an activity carried out by investors by placing their funds in an asset. The purpose of investment is to gain long-term profits in the future. These profits come from changes in the price of assets in the future, which refers to the increase in the value of an asset over time. Currently, there are several types of investments. However, the type of investment that is quite widely practiced by Indonesian society is stock investment. The Indonesia Stock Exchange (IDX) groups the stocks available in the stock market into several indexes. One index that is currently receiving attention from Indonesian society is the Jakarta Islamic Index (JII). The JII is a collection of shares from companies that adhere to sharia principles in their business operations. Investment activities must be carried out carefully by conducting analysis beforehand so that investors do not make mistakes in choosing the stocks to be purchased. Several popular methods for selecting stocks are the Sharpe, Treynor, and Jensen indexes. These three indexes can be used to select the best stocks based on their respective criteria. This study combine these three indexes to prioritize the formation of a portfolio. The data used in this study is the closing value of stock prices in the JII index from March 2018 to February 2023. The optimization resulted in a composition of 69.17% for MDKA shares, 26.55% for HRUM shares, and 4.28% for BRIS shares of the total portfolio composition.

Optimizing LQ45 Stock Portfolio To Maximize Sharpe Ratio Value Using LSTM

Investment is an investment activity within a certain period with the hope of getting a profit. Things that need to be considered by investors when investing are not just yields (return), but investors need to consider the purpose of the investment and the investment period. This study optimizes the formation of portfolios by utilizing the predicted value of stock prices using LSTM. The test used five daily stock indices from LQ45, namely BBCA, BBRI, TLKM, UNVR, and BMIR, from April 2010 – April 2020. The portfolio was built using the Genetic Algorithm and Equal-Weight (EW) method. Portfolio of Genetic Algorithm and Equal-Weight (EW) without predictions used as a benchmark. The experimental results show that using the LSTM prediction and Genetic Algorithm can produce an optimal portfolio with the highest Sharpe ratio value at 1.3950.

Stock price valuation analysis of the digital technology industry based on the HP-ARIMA method - with 18 listed companies of different volume sizes in its 3 segments as an example

The world securities market has formed a more complete system since its origin in the 17th century, with a considerable number of small and medium-sized investors and institutional investors, and proposing innovative new methods for securities valuation models can assist investors in making more accurate investment decisions. This paper proposes for the first time to use an interdisciplinary analysis method, ARIMA + HP filter analysis, to analyze the valuation of the securities market, by taking the opening prices of individual stocks in digital technology industry segments: blockchain, artificial intelligence, and Beidou navigation as examples for valuation analysis, firstly, the initial data of the opening prices of individual stocks from 2019-2021 are analyzed by HP filter analysis, and secondly, the data are analyzed while doing Tobit model test. By analyzing the long-term trend of the digital technology industry after noise reduction, its corresponding valuation forecast and value judgment results show that the head effect of the digital technology industry is more significant, and the opening price volatility shows a U-shaped relationship with company size and profitability, and the opening price volatility of individual stocks is less, while the shorter the company's establishment time, the greater the stock price volatility. While the past literature focused on the traditional valuation of financial conditions and historical data analysis of a single variable, this paper analyzes the data of individual stocks in the digital technology industry through an interdisciplinary analysis method, which allows for a more comprehensive use of historical data and prediction of possible stochastic fluctuations, providing a more reliable valuation method for securities investors and opening up new ideas for research related to the field of valuation analysis.

STOCK VALUATION USING THE PRICE TO EARNING RATIO METHOD IN THE STOCK OF MINING SECTOR IN IDX HIGH DIVIDEND 20 YEARS 2019-2020

Stock valuation is an assessment of the fair price of a stock. Stock valuation is carried out to anticipate potential losses that will be received by investors. This study aims to determine the fair price of the stock and choose the appropriate stock to be used as an investment choice in the IDX High Devidend 20 Index stock. Stock price valuation is measured using the Price Earning Ratio (PER) approach. In conclusion, from the stock valuation results, it can be seen that ADRO, ITMG, and PTBA shares in 2019 were undervalued or cheap so the investment decision that can be taken is to buy shares in that year. In 2020 stocks with the code ADRO, ITMG, and PTBA are also still classified as undervalued so the investment decision that can be taken is to buy shares

Research on the Corporate Value of Toyota Based on Multiple Valuation Method

Toyota corporation’s stock prices are determined by valuations, which are important in making a comparison between the company's financial status and stock price to its principal competitors' stock prices. The most common multiple valuation methods used by analysts include the Price-Earnings (P/E) ratio and the Enterprise Value to Adjusted EBITDA (EV/EBITDA) ratio. This paper uses these two compelling ratios to describe the stock prices of a corporation throughout the process of analyzing the financial ratios of a financial statement. The P/E ratio and EV/EBITDA, two key multiple valuation tools, as well as the financial data from Toyota Industries Group's primary competitors, are used to determine whether the stock prices of Toyota corporation over the past three years are overvalued, undervalued, or fair. The conclusive findings that can be drawn from the enterprise values of Toyota corporation are that they are undervalued, even though the stock prices are appropriate. Besides, through stock price valuation, investors can make judgments and choose to continue to hold or sell.

Stock Price Valuation Analysis for Investment Decision Making in PT Telkom Before and During Covid-19

Investors' decisions in terms of selling or buying shares, on average, are more concerned with the company's profit performance. This study was conducted to determine the intrinsic value of shares and the ratio of book value per share of TLKM for the period 2016-2020. The analytical tools used are the Dividend Discount Model (DDM), Price Earning Ratio (PER) and Price to Book Value (PBV). In this study using qualitative methods with secondary data, namely the financial statements of PT TLKM. The results of the study show that the intrinsic value of TLKM shares assessed using the DDM and PER approaches resulted in the same condition, namely overvalued in the pre-covid-19 period (2016-2019), except in 2018 in the undervalued category. Meanwhile, during the Covid-19 (2020) period, TLKM shares were in the undervalued category. The results showed that the right decision during the covid-19 period was buying TLKM shares. The novelty in this research is to analyze stock price valuation through intrinsic value and book value. Keywords: Dividend Discount Mode l ; Price to Book Valu e; Pri ce Earning Ratio ; Stock Price

A Study of Interlinkages among Exchange Rate and Stock Price for India

This paper is an attempt to examine the empirical relation between exchange rate and Indian stock price using the monthly time series data over the period 2011-2021. Johansen’s cointegration test has been applied to test the long run relationship between exchange rate and stock price. Both the trace and Maximum Eigenvalue test statistic are less than the 0.05 critical values. Thus, the null hypothesis of no cointegration is accepted and no long run stable equilibrium relation was found to exist between exchange rate and stock price. The analysis further reveals the prevalence of unidirectional causal relationship from stock price to exchange rate by employing the Granger causality test. Thus, the study is found to support the Stock oriented model. So, regulators can predict the trends in exchange rate from the past values of stock prices which can induce profitable trading in the currency market. This study would be of immense importance for various stakeholders like investors, practitioners and policy makers to reduce the information symmetry owing to the volatile nature of the two variables.

Analysis of Electronic Industry Stock Price Valuation Based on HP-ARMA Method——Take 9,105 Samples from 15 Enterprises

The electronics industry plays an increasingly important role in GDP, and it is of great significance to study the valuation of the stock price of the electronics industry. In the process of reading the literature, the author found the possible deficiencies in the related fields: (1) The existing studies lack timeliness and are of little reference significance. (2)There is less research on stock price valuations in the electronics industry. After summing up the previous theoretical results, in the electronics industry sub-plate: semiconductor, consumer electronics, PCB, optical optoelectronics and security take 3 leading stocks, the data of 607 trading days of these 15 stocks from 2020 to July 6,2022 are selected. Based on the ARMA model, the long-term trend of stock price separated by HP Filter is used to predict and analyze the future stock price. According to the overall empirical results, this paper draws the following conclusions. (1) The semiconductor sector is more dependent on imports, and the stock price volatility is higher; (2) The stock price of companies with smaller assets is less correlated with the number of trading days; (3) The overall stock price of the electronics industry basically shows a steady upward trend, with huge growth potential.

PENGARUH PROFITABILITAS DAN VALUASI HARGA SAHAM TERHADAP RETURN SAHAM (Studi Kasus pada Perusahaan Konsumer Non-siklikal PT. Indofood CBP Sukses Makmur, Tbk Q1 2011 – Q4 2021)

The existence of the stock exchange is widely known by the public, as reflected in the SID which shows a significant increase from 2017 to 2021. One popular stock exchange investment instrument is stocks, with the highest probability of return but accompanied by great risk. Specifically, non-cyclical consumer companies can provide investment security because of stable profit growth in the long term, making it attractive for investors with long investment timeframes. However, efforts to achieve optimal returns require an analytical process, involving financial statements as a fundamental aspect. There are important ratios, one of which is profitability shown through Net Profit Margin and Return On Equity. In addition, the rational analysis process can be strengthened by evaluating stock prices. This research aims to determine the impact of profitability and stock price valuation on stock returns of PT. Indofood CBP Sukses Makmur, Tbk (ICBP). One of the reasons why ICBP was chosen as the object of research is because as a leading company in the non-cyclical consumer sector with good profitability, however, ICBP's stock price tends to decline at this time. This research uses a quantitative method with multiple linear regression through Eviews 12. The results of the research prove that there is a significant and positive impact of Return On Equity and stock price valuation on stock returns. Meanwhile, Net Profit Margin does not have a significant impact on stock returns.

Determinants of Dividend Policy and its Impact on Firm's Value: An Evidence of Automobile Sector in Pakistan

Research on a company's dividend policy is crucial because it ultimately affects the growth and performance of the company. The study's objective is to determine the variables that affect dividend policy, and both micro and macroeconomic indicators have been selected. Dividend policy is an important factor that successfully mediates the connection between certain economic variables and the firm value. Data were gathered from five publicly traded automobile firms in Pakistan for the years 2011 to 2021. The stock price valuation of automobile companies has been determined using the Linear Regression Model for relationship analysis of variables and the Sobel test method for the mediation impact of dividend policy. The study's findings demonstrate that economic variables like micro and macro include a most important impact on the dividend policy, and the results of the Sobel technique and findings on the stock prices of Pakistan’s automobile firms confirm these findings.