Journal articles: 'Stock analysis software'

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HSM, Zani Anjani Rafsanjani. "ANALISA LAJU PERUBAHAN HARGA SAHAM LQ45 MENGGUNAKAN PERSAMAAN DIFERENSIAL." Jurnal Riset Akuntansi Politala 3, no. 2 (December 29, 2020): 60. http://dx.doi.org/10.34128/jra.v3i2.68.

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The stock price movement is a very interesting discussion today. Dynamic price changes every time requires deep analysis to determine trends and stock price predictions in the future. There have been many methods used to analyze and predict stock prices. This paper will analyze the acceleration of stock price changes using a mathematical approach, known as a second-order differential equation. The benefit of this research is to obtain a coefficient of change in stock prices that can be used to predict stock prices in the future. Stock prices that will be observed are stocks including the LQ45 category. Furthermore, program analysis is carried out using Matlab software. At the end of the study, the coefficient of price change for LQ45 stocks was generated through provided historical data.

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Zhu, Rong, Zuo Quan Zhang, Xiao Yue Li, Xuan Wu, and Su Zhang. "The Study on the Plasticity Theoretical Models of the Volatility of Stock Prices." Advanced Materials Research 518-523 (May 2012): 5963–67. http://dx.doi.org/10.4028/www.scientific.net/amr.518-523.5963.

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This paper analyzes the characteristics of the stock price fluctuation compared with elastic-plastic theory in mechanics and introduces the concept of stock equilibrium price, plasticity of stock price analogically. A basic model of the stock plasticity under the relationship between stock price fluctuation and trading volume changes is also built. Tested by 20 kinds of stocks from Shanghai and Shenzhen stock markets in China by using the econometric analysis software Eviews3.0 afterwards, the basic model is improved, and three developed models are built from it. Finally, this paper obtains more scientific and reasonable stock price plasticity model after the comparative analysis of the four previous models.

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Peng, Xia, and Ping Zhu. "Requirement Analysis of Storage Management System." Applied Mechanics and Materials 263-266 (December 2012): 1438–41. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.1438.

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The storage management system manages and controls for storage in-out stock activities, and has an important significance for coordinating production and operation of enterprise, improving economic efficiency. Requirement analysis is the basis of software development, mainly is functional requirement analysis and performance requirement analysis. First, do the functional requirement analysis, through analysis the business processes, analysis the main functions and processes of system with data flow diagram, and list the buyer, purchase commodity information, sales production, commodity stock table and data dictionary item. Then, do performance requirement analysis; describe the main content of the three aspects of accuracy, time characteristics and flexibility, especially analysis the C/S structure model to build software systems. In this paper, describes the overall concept of software function and performance as the specific software requirement specification, lays a foundation for the development of storage management system.

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Barberà-Mariné, M. Glòria, Yanina Laumann, and Laura Fabregat-Aibar. "Analysis of Fuzzy Beta Coefficients. Evidence from the Mexican Stock Market." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 26, Suppl. 1 (December 2018): 59–69. http://dx.doi.org/10.1142/s0218488518400044.

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This paper represents a contribution to the empirical literature on systematic risk at a sectoral level in an emerging market, the Mexican Stock Market, incorporating all the available information of the different asset quoted prices for the beta calculation. We estimate the fuzzy beta coefficients for individual stocks as well as for sectoral indices comparing the results with OLS beta coefficients. Then, we contrast if the fuzzy estimations verify two hypothesis of the traditional portfolio theory, specifically those related to the influence of the number of stocks and the length of estimation period over beta stability. The methodology used to calculate the fuzzy beta coefficients is the fuzzy linear regression. The results suggest that, in the Mexican Stock Market, hypotheses of the portfolio theory are also verified when the return of the portfolio is considered as an uncertain data.

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Dařena, František, Jonáš Petrovský, Jan Žižka, and Jan Přichystal. "Machine Learning-Based Analysis of the Association Between Online Texts and Stock Price Movements." Inteligencia Artificial 21, no. 61 (May 9, 2018): 95. http://dx.doi.org/10.4114/intartif.vol21iss61pp95-110.

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The paper presents the result of experiments that were designed with the goal of revealing the association between texts published in online environments (Yahoo! Finance, Facebook, and Twitter) and changes in stock prices of the corresponding companies at a micro level. The association between lexicon detected sentiment and stock price movements was not confirmed. It was, however, possible to reveal and quantify such association with the application of machine learning-based classification. From the experiments it was obvious that the data preparation procedure had a substantial impact on the results. Thus, different stock price smoothing, lags between the release of documents and related stock price changes, five levels of a minimal stock price change, three different weighting schemes for structured document representation, and six classifiers were studied. It has been shown that at least part of the movement of stock prices is associated with the textual content if a proper combination of processing parameters is selected.

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Li, Xiaodong, Haoran Xie, Ran Wang, Yi Cai, Jingjing Cao, Feng Wang, Huaqing Min, and Xiaotie Deng. "Empirical analysis: stock market prediction via extreme learning machine." Neural Computing and Applications 27, no. 1 (February 2, 2014): 67–78. http://dx.doi.org/10.1007/s00521-014-1550-z.

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Hayat, Nur Mishbah, Agung Budi Prasetijo, and Risma Septiana. "Analisis Kinerja Algoritma J48 Decision Tree untuk Pengambilan Keputusan Beli/Jual pada Saham PT Harum Energi Tbk. (HRUM)." JTIM : Jurnal Teknologi Informasi dan Multimedia 1, no. 3 (November 7, 2019): 244–53. http://dx.doi.org/10.35746/jtim.v1i3.43.

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The problem that is often faced by investors in selling / buying stocks is the difficulty in analyzing a dataset of stock prices in large quantities.This analysis aims to predict the rise or fall of stock prices based on data obtained. To assist investors in determining buying / selling decisions on stock analysis based on technical and equipped with classification techniques in data mining. This study analyzes the performance of the J48 Decision Tree algorithm in the Waikato Environmental Software for Knowledge Analysis (WEKA) version 3.8.2 for PT. Harum Energi Tbk. (HRUM). The results showed in the testing data, the percentage of testing on data without normalization was higher by 87.3 (non-aggressive) and 88.8 (aggressive) compared to normalized data 84.2 (non-aggressive) and 85 (aggressive ). The biggest stock profit generated is in non-aggressive type data without normalized by 48.75 or Rp. 48,750.00.

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Shen, Kao-Yi, and Gwo-Hshiung Tzeng. "Combined soft computing model for value stock selection based on fundamental analysis." Applied Soft Computing 37 (December 2015): 142–55. http://dx.doi.org/10.1016/j.asoc.2015.07.030.

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Li, Hua, and Hong Zhou. "An Empirical Analysis on the Influence Factors of Stock Market." Advanced Materials Research 403-408 (November 2011): 353–57. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.353.

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Many scholars have studied the influence of the single variable to the stock market. In this paper, regression analysis method and Econometrics software Eviews 6.0 are used to solve the problem. Through analyzing the inner relationship among stock trading volume, money supply, interbank lending rates, and consumer confidence index, this paper attempts to establish a multiple regression equation and eliminate the problems of multicollinearity, autocorrelation and heteroscedasticity at the same time. The empirical analysis proves the model has certain rationality which can provide the basis for investors on stock investment.

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Jin, Zhigang, Yang Yang, and Yuhong Liu. "Stock closing price prediction based on sentiment analysis and LSTM." Neural Computing and Applications 32, no. 13 (September 19, 2019): 9713–29. http://dx.doi.org/10.1007/s00521-019-04504-2.

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Thawornwong, Suraphan, David Enke, and Cihan Dagli. "Neural Networks as a Decision Maker for Stock Trading: A Technical Analysis Approach." International Journal of Smart Engineering System Design 5, no. 4 (October 2003): 313–25. http://dx.doi.org/10.1080/10255810390245627.

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Telang, Rahul, and Sunil Wattal. "An Empirical Analysis of the Impact of Software Vulnerability Announcements on Firm Stock Price." IEEE Transactions on Software Engineering 33, no. 8 (August 2007): 544–57. http://dx.doi.org/10.1109/tse.2007.70712.

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Wang, Rui Zhong. "The Association Analysis of Technical Indicators of Shanghai Stock Market." Applied Mechanics and Materials 651-653 (September 2014): 1651–54. http://dx.doi.org/10.4028/www.scientific.net/amm.651-653.1651.

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This paper selected as part of a number of technical indicators, the main use of data mining software for different technical indicators signal given trading technical analysis of association rules. By studying the resulting characteristics of the relationship between the rules and give the stock market investors a certain decision support, to enable investors to operate with a higher success rate.

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HARA, AKIRA, and TOMOHARU NAGAO. "CONSTRUCTION AND ANALYSIS OF STOCK MARKET MODEL USING ADG: AUTOMATICALLY DEFINED GROUPS." International Journal of Computational Intelligence and Applications 02, no. 04 (December 2002): 433–46. http://dx.doi.org/10.1142/s1469026802000749.

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In real market, the squares of stock price change rates have high autocorrelation, and the change rates show high peak and fat tail distribution. With the aim of analyzing the mechanism of the stock price change, we construct an artificial stock market composed of multiple agents whose investment strategies are represented by tree-shaped programs. The market is optimized by using a Genetic Programming so that the change of its stock price resembles that of "real" stock market statistically. In order to perform an efficient optimization and to analyze agents' behavior easily, we use ADG; Automatically Defined Groups previously proposed by authors. We show experimentally that complex changes such as real market appear in the proposed artificial market. Moreover we analyze the interaction of agents which causes realistic stock price changes.

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Azizah, Mia, Erwin Riyanto Ardli, and Eming Sudiana. "ANALISIS STOK KARBON HUTAN MANGROVE PADA BERBAGAI TINGKAT KERUSAKAN DI SEGARA ANAKAN CILACAP." Jurnal Sains Natural 3, no. 2 (December 1, 2017): 161. http://dx.doi.org/10.31938/jsn.v3i2.66.

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Cabrbon Stock Analysis of Mangrove Forest in Every Damaged Level in Segara Anakan Cilacap Mangrove is a specific vegetation type, found in tropical and subtropical beach area which located in Cilacap at a sloping beach area near the mouth of a river and the beach protected from the waves. Segara anakan is one of mangroves region which located at 108 º 46'-109 º 03 'E and 07 º 34' - 07 º 47 'South Latitude. Human activities series in Segara anakan mangrove lead the damage of this region, it affects to the ecological and biological or mangrove function as carbon storage place. The aims of this research was to analyze the damage level of mangrove in Segara anakan, Cilacap; to know the spatial distribution of mangrove damage level in Segara anakan; analyze the amount of biomass and carbon stocks at various of damage level in Segara anakan, and to know the number corelation of carbon stocks with damage level in Segara anakan, Cilacap.The research used survey method with purposive random sampling that determine the sampling location based on the damage level. Damage analysis used assessment teristis method (field survey) and than spasial distribution used surfer 9.0 and ArcView GIS 3.2. Biomass analysis and the amount of carbon stock used descriptive methods, damage level correlation and the amount of carbon stock used Pearson correlation analysis (SPSS software vs. 19).The result was Segara anakan mangrove, Cilacap currently was divided into not damage (7 station), damaged (3 station) and heavily damaged (5 station) categories. The amount of biomass and carbon stocks in not damaged area (57,67 tons/ha and 26,50 tons/ha); damaged area (23,40 tons/ha and 10,74 tons/ha, and the heavily damaged area (9,49 tons/ha and 4,37 tons/ha). The destruction of mangrove forest affected the amount of biomass and carbon stocks in Segara anakan, Cilacap.Keywords : mangrove, carbon stock, damage level, Segara Anakan Cilacap ABSTRAK Hutan mangrove merupakan tipe vegetasi khas, terdapat di daerah pantai tropis dan subtropis yang tumbuh subur di daerah pantai yang landai di dekat muara sungai dan pantai yang terlindung dari hempasan gelombang. Segara Anakan adalah salah satu kawasan hutan mangrove yang terletak pada koordinat 07º34’ - 07º47’ LS dan 108º46’- 109º03’ BT. Serangkaian aktivitas manusia di kawasan hutan mangrove Segara Anakan menyebabkan kawasan ini mengalami kerusakan, hal tersebut berpengaruh terhadap fungsi ekologis dan biologis serta fungsi hutan mangrove sebagai penyimpan karbon. Penelitian ini bertujuan untuk menganalisis dan mengetahui tingkat kerusakan hutan mangrove di Segara Anakan Cilacap; mengetahui distribusi spasial potensi stok karbon hutan mangrove di Segara Anakan Cilacap dan mengetahui korelasi jumlah stok karbon dengan tingkat kerusakan di Segara Anakan Cilacap.Penelitian ini menggunakan metode survei dengan menggunakan teknik purposive random sampling yaitu menentukan lokasi sampling berdasarkan pada tingkat kerusakan. Analisis kerusakan menggunakan metode penilaian teristis (survey lapangan) yang selanjutnya didistribusi spasial menggunakan surfer 9.0 dan Arcview GIS 3.2. Analisis biomassa dan jumlah stok karbon menggunakan metode deskriptif, korelasi tingkat kerusakan, dan jumlah stok karbon menggunakan analisis korelasi Pearson (Software SPSS vs. 19). Hasil yang diperoleh adalah hutan mangrove Segara Anakan Cilacap saat ini terbagi menjadi area dengan kategori tidak rusak (7 stasiun), rusak (3 stasiun) dan rusak berat (5 stasiun). Jumlah biomassa dan stok karbon di area yang tidak mengalami kerusakan (57,67 ton/ha dan 26,50 ton/ha), area yang rusak (23,40 ton/ha dan 10,74 ton/ha, dan area yang rusak berat (9,49 ton/ha dan 4,37 ton/ha). Kerusakan hutan mangrove berpengaruh terhadap jumlah biomassa dan stok karbon di Segara Anakan.Kata Kunci: mangrove, stok karbon, tingkat kerusakan,SegaraAnakan Cilacap

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Krissinel, Eugene. "Stock-based detection of biological assemblies in PISA software." Acta Crystallographica Section A Foundations and Advances 70, a1 (August 5, 2014): C1745. http://dx.doi.org/10.1107/s2053273314082540.

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PISA (Protein Interfaces, Surfaces and Assemblies) software from CCP4 remains a popular computational tool for the prediction of biological assemblies (complexes) from macromolecular crystallography data [1]. The method is based on the estimation of the dissociation free energy of predicted complexes, and reaches 90-95% correct results for the current content of the PDB. It was found that the probability of getting wrong predictions grows exponentially with the decrease in the dissociation free energy, reaching over 50% for complexes bound as weakly as few kcal/mol [2]. Among few reasons for this behaviour [2] is the fact that oligomeric state of weakly bound complexes is expected to vary in dependence of chemical environment, in particular, protein concentration. It has been noticed in multiple use cases, that a considerable share of disagreements between predicted and measured oligomeric states belongs to situations where the relation between experimental conditions and protein's working environment in the cell is unclear. We report further advance in PISA software, which allows a researcher to model concentration dependence of predicted oligomeric states, and by this to improve interpretation of both experiments and computations in the biologically interesting case of weakly bound macromolecular associations. The new PISA is based on the concept of assembly stock, which represents an equilibrated set of of all complexes, compatible with crystal packing. Graphical representation of concentration (or newly introduced aggregation index) profiles of stock's components allows a user to quickly identify the most probable oligomeric state. This is vastly superior over the previous way of analysis, based on the interpretation of bare figures for dissociation free energies. Other developments include advanced graphical interface and multi-parametric interaction radar, which indicates the likelihood for interface to represent a biologically-relevant interaction.

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Saleh, E. S., and A. M. Kimiagari. "Ranking Tehran’s Stock Exchange Top Fifty Stocks Using Fundamental Indexes and Fuzzy TOPSIS." Engineering, Technology & Applied Science Research 7, no. 4 (August 9, 2017): 1863–69. http://dx.doi.org/10.48084/etasr.1252.

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Investment through the purchase of securities, constitute an important part of countries economic exchange. Therefore, making decisions about investing in a particular stock has become one of the most controversial areas of economic and financial research and various institutions have began to rank companies stock and determine priorities of stock purchase to investment. The current research, with the determination of important required indexes for companies ranking based on their shares value on the Tehran stock exchange, can greatly help to the accurate ranking of fifty premier listed companies. Initial ranking indicators are extracted and then a decision-making group (exchange experts) with the use of the Delphi method and also non-parametric statistic methods, determines the final indexes. Then, by using Fuzzy ANP, weight criteria are obtained with taking into account their interaction with each other. Finally, using fuzzy TOPSIS and information extraction about the premier fifty listed companies of Tehran stock exchange in 2014 are ranked with the software "Rahavard Novin”. Sensitivity analysis to criteria weight and relevant analysis presentation was conducted at the end of the study procedures.

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Chege, Gabriel, and Stanley Kirika. "EFFECT OF MACROECONOMIC FACTORS ON TRADING VOLUMES OF MANUFACTURING AND ALLIED COMPANIES LISTED IN NAIROBI SECURITIES EXCHANGE." International Journal of Finance and Accounting 6, no. 1 (August 11, 2021): 32–52. http://dx.doi.org/10.47604/ijfa.1337.

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Purpose: The purpose of the study was to establish the effect of macroeconomic factors on stocks trading volumes of manufacturing and allied companies listed in Nairobi Securities Exchange. Materials and Methods: The research adopted a quantitative descriptive design that focuses on nine manufacturing and allied companies listed in NSE and make up in the list of 25-share index companies. The nine manufacturing and allied companies were selected through purposive sampling techniques, where samples were selected based specific factors. The data used in the research was collected from Central Bank of Kenya, Nairobi Security Exchange and Kenya Bureau of Statistics. This research employed a panel data analysis using STATA software. Treasury bill rate was dropped from the model due to multicollinearity. Results: The analysis found that there was a negative relationship between inflation on trading volume, exchange rate had a negative correlation with stock trading, lending rate had a negative correlation with stock trading volume of manufacturing and allied companies listed in the Nairobi Stock Exchange. Unique contribution to theory, practice and policy: The study recommends the government should initiate policies that will lower the lending rate in Kenya as lower lending rate may translate to higher stock trading volumes. Further studies should research on other factors affecting stock trade volume which may include the value of the stocks and the information size in the market.

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Frankandinata, Frankandinata, and Yoyo Cahyadi. "Analisis Keakuratan Indikator Bollinger Bands Terhadap Pergerakan Harga Saham: Studi Kasus pada Saham PT Astra Agro Lestari Tbk." Binus Business Review 5, no. 1 (May 30, 2014): 112. http://dx.doi.org/10.21512/bbr.v5i1.1201.

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Technical analysis is an analytical tool to analyze price movement of an investment instrument like stock. Practically, there are a lot of indicators that can be used in technical analysis. One of them is Bolinger Bands. Bolinger Bands has 3 moving averages lines, which are Upper Band, Middle Band, and Lower Band. Study used library research and software review by analyzing the candlestick chart of stock price with ChartNexus software. The stock for this study was Astra Agro Lestari (AALI) and the period was 1 July 2010 until 31 May 2013. Results showed that Bolinger Bands gave 45 signals in the period with 75.56% accuracy.

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Sharma, Surbhi, and Baijnath Kaushik. "Quantitative Analysis of Stock Market Prediction for Accurate Investment Decisions in Future." Journal of Artificial Intelligence 11, no. 1 (December 15, 2017): 48–54. http://dx.doi.org/10.3923/jai.2018.48.54.

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Ruan, Yefeng, Arjan Durresi, and Lina Alfantoukh. "Using Twitter trust network for stock market analysis." Knowledge-Based Systems 145 (April 2018): 207–18. http://dx.doi.org/10.1016/j.knosys.2018.01.016.

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Chen, Dongdong, Xingchen Guo, Jianjia Wang, Jiatong Liu, Zhihong Zhang, and Edwin R. Hancock. "Thermodynamic motif analysis for directed stock market networks." Pattern Recognition 114 (June 2021): 107872. http://dx.doi.org/10.1016/j.patcog.2021.107872.

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Salsabila, Nadiah Ayu, and Titis Miranti. "FAKTOR PENGARUH RASIO KEUANGAN TERHADAP HARGA SAHAM PERUSAHAAN JAKARTA ISLAMIC INDEX (JII)." El Muhasaba Jurnal Akuntansi 12, no. 1 (January 26, 2021): 42–55. http://dx.doi.org/10.18860/em.v12i1.10123.

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Jakarta Islamic Index is a stock index in the IDX that can use as an alternative In Islamic investment. In choosing an investment object in Islamic stocks, it necessary to pay attention to the financial ratios and stock prices of companies. The purpose of this study was to determine the effect of financial ratios on stock prices on companies listed on the Jakarta Islamic Index (JII). The type of this research is quantitative. The population of 56 companies registered on the Jakarta Islamic Index (JII) for the 2012-2018 period with a sample of 11 companies. The analysis model use panel data regression using Eviews software. The type of data uses secondary data accessed through the Indonesia Stock Exchange (IDX) website. The results showed that earning per share variable has a significant effect on stock prices. While the current ratio, debt to equity ratio, total assets turnover and net profit margin variables have no significant impact on stock prices. Simultaneously variables of current ratio, debt to equity ratio, total assets turnover, net profit margin and earning per share have significant effects on stock prices. The contribution of this research can use as a reference for companies to pay attention to financial ratios that affect stock prices.

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Violita, Rinda Firma, Sri Widowati, and Prati Hutari Gani. "Application of the TROPOS Method to Development a Website-Based Blood Stock Management System at Palang Merah Indonesia (PMI) in Bandung City." Jurnal Sisfokom (Sistem Informasi dan Komputer) 9, no. 2 (June 14, 2020): 185. http://dx.doi.org/10.32736/sisfokom.v9i2.856.

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Palang Merah Indonesia (PMI) is a social organization in the city of Bandung. In the business process, the blood donor section has not used any software that satisfies the need to connect communities and PMI on blood donor information. So it takes software that can help the process of running blood donor business to minimize the problems that occur such as human error and not spread information about blood supply. RE (Requirement Engineering) is an early stage as an important task, as many software failures come from inconsistent, incomplete or just wrong specification requirements. In RE there is a process that is requirement analysis to do analysis of user needs. Goal Oriented Requirements Engineering (GORE) is one of the models that can be used to analyse user needs. One method on the GORE model is the TROPOS method. The use of TROPOS on the development of the blood stock management software to focus on the needs analysis on the stages of modeling early requirement and late requirement. The results of the analysis are implemented into web software design. Software that has been created based on the modeling evaluated using BlackBox Testing with user acceptance test (UAT) by stakeholders. Based on the results of the assessment UAT score, the results of the respondents assessment is 3.55%, so that the blood stock management software can be used as a supporting tool to run the blood stock business process of PMI.

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Yamaguchi, Takahira. "A technical analysis expert system in the stock market." Future Generation Computer Systems 5, no. 1 (August 1989): 21–27. http://dx.doi.org/10.1016/0167-739x(89)90016-2.

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Absari Indah Pratiwi, Risdy, Isfenti Sadalia, and Sutarman Sutarman. "Dampak Perubahan Tick Size Terhadap Likuiditas Saham (Studi Empiris Pada Bursa Efek Indonesia Berdasarkan Tick Size 6 Januari 2014)." Bahtera Inovasi 2, no. 2 (November 18, 2019): 152–62. http://dx.doi.org/10.31629/bi.v2i2.1628.

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The objective of the research was to find out and to analyze the influence of the change in tick size on stock liquidity and the factors which influenced stock liquidity. Tick size which became the research object in this evet study was the tick size on January 6, 2014. The sources of data were secondary data from BEI and Yahoo Finance. The samples were 147 stocks before the change in tick size and 147 stocks after the change in tick size, using purposive sampling technique.The data were analyzed by using Wilcoxon signed-rank test and regression analysis with an SPSS software program. The result of the research showed that spread and depth decreased significantly after the change in tick size. Lower spread and depth had contradictory implication on stock liquidity. Based on the dimension of immediacy cost and width, lower spread indicated that stock liquidity increased, while based on the dimension of market depth, lower depth indicated that stock liquidity decreased. In order to settlethis contradiction, the researcher used depth to spread ratio. Intuitively, this ratio measured whether the decrease in depthwas bigger or smaller that the decrease in spread. The result of Wilcoxon signed-rank test indicated that depth to spread ratio increased significantly which indicated that the decrease in depth was smaller than in spread so that it was concluded that stock liquidity increased after the change in tick size. The result of F-test showed that stock price, stock return volatility, and stock trading frequency simultaneously had significant influence on spread and depth. The result of t-test also indicated that stock price, stock return volatility, and stock trading frequency partially had significant influence on spread and depth.

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Evbayiro-Osagie, Esther Ikavbo, and Ifuero Osad Osamwonyi. "A Comparative Analysis of Four-Factor Model and Three-Factor Model in the Nigerian Stock Market." International Journal of Financial Research 8, no. 4 (September 14, 2017): 38. http://dx.doi.org/10.5430/ijfr.v8n4p38.

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The study investigates if the three-factor model explains variation in expected returns of stocks on the Nigerian Stock Exchange (NSE); and also ascertains if the four-factor model explains the variation in expected returns of stocks on the NSE better than the three-factor model. The study use a sample size of 139 stocks with continuous trading on the NSE for the period January 2007 to December 2014 to construct 10 portfolios on the bases of size, value and returns. By means of multiple OLS regression analysis method with the aid of StataC13 software the analysis was done. The empirical analysis reveals that the three-factor model explains cross sectional variation in expected returns in the NSE. Also, the study shows that the size effect, value effect as well as momentum effect is present in the market. Comparing the four-factor model with three-factor model, shows that the four-factor model have better explanatory power than the three-factor model in explaining returns in the Market. It is recommended that equity investors, fund/portfolio managers and investment advisers should embed in their operational strategies the explanatory power of market beta, size and value as well as momentum on stock/portfolio returns to enable them build up trading strategies that minimize loss and maximize returns. Market regulators and policy makers should ensure appropriate measures are in place to improve market viability and liquidity in order to enhance the depth and breathe of the market.

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LONG, NGUYEN CONG, NAWAPORN WISITPONGPHAN, PHAYUNG MEESAD, and HERWIG UNGER. "CLUSTERING STOCK DATA FOR MULTI-OBJECTIVE PORTFOLIO OPTIMIZATION." International Journal of Computational Intelligence and Applications 13, no. 02 (June 2014): 1450011. http://dx.doi.org/10.1142/s1469026814500114.

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Portfolio selection is a vital research field in modern finance. Multi-objective portfolio optimization problem is the portfolio selection process that results in the highest expected return rate and the lowest identified risk among the various financial assets. This paper proposes a model that can efficiently suggest a portfolio that is worth investing. First, a cluster analysis model is introduced in order to categorize a huge amount of stock data into several groups based on their associated return rate and the risk. Several validity indexes are used to select the optimal number of clusters/stocks to be included in the portfolio. Finally, the multi-objective genetic algorithm is used to build portfolio optimization with highest return rate and lowest risk. The proposed model is tested on the data obtained from the Stock Exchange of Thailand.

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Siregar, Kurniawan, and Afriapollo Syafarudin. "ANALYSIS OF CRUDE PALM OIL (CPO) PRODUCTION VOLUME AND PRICE ON PROFITABILITYAND ITS IMPACT ON STOCK RETURNS." International Journal of Engineering Technologies and Management Research 6, no. 7 (March 31, 2020): 87–100. http://dx.doi.org/10.29121/ijetmr.v6.i7.2019.419.

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This study aims to examine and analyze the effect of production volume and crude palm oil (CPO) prices on profitability (proxied by return on assets, ROA) and its impact on stock returns (proxied by capital gains) in plantation industry sector companies listed on the Indonesia Stock Exchange (BEI) 2013 - 2017. The sampling method used was purposive sampling. From the population of 18 plantation industry companies, 12 companies met the criteria to be sampled. The type of data used is panel data, which is collected by documentation techniques. The analytical method used in this study is multiple linear regression using Eviews version 9.0 software. The results showed that CPO production had a positive and not significant effect on ROA. The price of CPO has a negative and not significant effect on ROA. ROA has a positive and not significant effect on stock returns. CPO production has a negative and not significant effect on stock returns. CPO prices have a positive and not significant effect on stock returns. Simultaneously CPO production and prices have no significant effect on ROA and stock returns. CPO production and CPO prices simultaneously contribute more to stock returns than through ROA as an intervening variable.

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Alizadeh, Meysam, Roy Rada, Fariborz Jolai, and Elnaz Fotoohi. "An adaptive neuro-fuzzy system for stock portfolio analysis." International Journal of Intelligent Systems 26, no. 2 (November 10, 2010): 99–114. http://dx.doi.org/10.1002/int.20456.

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Reza Alfianto Siregar, Muhammad, and Pardomuan Sihombing. "DETERMINANT ANALYSIS OF FINANCIAL RATIO ON STOCK RETURNS IN CONSTRUCTION COMPANIES REGISTERED AT INDONESIA STOCK EXCHANGE 2015-2019." Dinasti International Journal of Education Management And Social Science 2, no. 1 (November 17, 2020): 67–80. http://dx.doi.org/10.31933/dijemss.v2i1.598.

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The growth of the construction sector in Indonesia has indirectly contributed to the growth in the performance of construction companies. This construction performance growth has an impact on stock price movements, apart from the influence of demand and supply of shares. The condition of fluctuating stock price movements requires investors to analyze financial statements before making investment decisions. To find out how the stock price performance can be done by measuring stock returns. In connection with these conditions, the purpose of this study is to analyze the effect of ROE, DER, CR, PBV and TATO on stock returns in construction companies listed on the IDX in 2015 - 2019. This research is included in the category of comparative causal research. The number of samples used in this study were 13 sample companies, with the sampling technique using purposive sampling. The type of data in this study is secondary data taken by the documentation method at Yahoo Finance. The data analysis method uses panel data regression analysis assisted by the Eviews 9.0 software. The results of the study partially show that ROE; DER, CR, PBV, and TATO have a positive and significant effect on stock returns. In addition, ROE, DER, CR, PBV, and TATO simultaneously have a significant effect on stock returns.

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Li, Xiaodong, Haoran Xie, Li Chen, Jianping Wang, and Xiaotie Deng. "News impact on stock price return via sentiment analysis." Knowledge-Based Systems 69 (October 2014): 14–23. http://dx.doi.org/10.1016/j.knosys.2014.04.022.

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Bisoi, Ranjeeta, and P. K. Dash. "A hybrid evolutionary dynamic neural network for stock market trend analysis and prediction using unscented Kalman filter." Applied Soft Computing 19 (June 2014): 41–56. http://dx.doi.org/10.1016/j.asoc.2014.01.039.

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Chege, Gabriel Njogu, and Stanley Kirika. "EFFECT OF MACROECONOMIC FACTORS ON TRADING VOLUMES OF MANUFACTURING AND ALLIED COMPANIES LISTED IN NAIROBI SECURITIES EXCHANGE." International Journal of Finance and Accounting 5, no. 2 (November 10, 2020): 27. http://dx.doi.org/10.47604/ijfa.1166.

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Purpose: The purpose of this study was to establish the effect of inflation, lending rate, exchange rates and Treasury bill interest rate on trading volumes of manufacturing and allied companies listed in the Nairobi Stock Exchange. Materials and Methods: The research adopted a quantitative descriptive design that focuses on nine manufacturing and allied companies listed in NSE and make up in the list of 25-share index companies. The nine manufacturing and allied companies were selected through purposive sampling techniques, where samples were selected based specific factors. The data used in the research was collected from Central Bank of Kenya, Nairobi Security Exchange and Kenya Bureau of Statistics. This research employed a panel data analysis using STATA software. Treasury bill rate was dropped from the model due to multicollinearity. Results: The analysis found that there was a negative relationship between inflation on trading volume, exchange rate had a negative correlation with stock trading, lending rate had a negative correlation with stock trading volume of manufacturing and allied companies listed in the Nairobi Stock Exchange. Unique contribution to theory, practice and policy: The study recommends the government should initiate policies that will lower the lending rate in Kenya as lower lending rate may translate to higher stock trading volumes. Further studies should research on other factors affecting stock trade volume which may include the value of the stocks and the information size in the market.

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Ali, Karnila. "Forecasting Analysis of Share Price Index in Construction Companies Registered in Indonesia Stock Exchange 2015-2019." Journal of Economics Research and Social Sciences 5, no. 1 (February 24, 2021): 42–63. http://dx.doi.org/10.18196/jerss.v5i1.11044.

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Stock is one of the investment instruments that many investors choose, both short and long term. Meanwhile, the stock price index is an essential indicator for investors deciding whether to buy, sell, or hold the stock. This study aims to determine what methods are suitable for predicting the Stock Price Index of Construction Companies Listed on the Indonesia Stock Exchange in 2015-2019. By selecting a model that matches the existing time series data, to evaluate the results of the forecasting, the researcher uses a measure of accuracy with Mean Absolute Percentage Error (MAPE), Mean Absolute Deviation (MAD), and Mean Squared Deviation (MSD). This type of research is a quantitative study with a research population of 16 companies listed on the Indonesia Stock Exchange. Only four samples were used that fit the specified criteria, and only five years of research were conducted, namely in 2015 to 2019. data can be seen from historical data or actual data and tested using Minitab software version 19. The results showed that Double Exponential Smoothing (Holt's) and Double Moving Average Method could be used to forecast the Construction Company Stock Price Index. Obtaining the smallest error value of the four construction companies, namely WSKT company with MAPE = 7.3, MAD = 148.8, and MSD = 40506.0 for the Holt'sand MAPE method = 5.3, MAD = 110.1, and MSD = 22006.9 for the Double Moving Average method.

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Megalooikonomou, Konstantinos G. "PHAETHON: Software for Analysis of Shear-Critical Reinforced Concrete Columns." Modern Applied Science 12, no. 3 (February 7, 2018): 1. http://dx.doi.org/10.5539/mas.v12n3p1.

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Earthquake collapse of substandard reinforced concrete (RC) buildings, designed and constructed before the development of modern seismic design Codes, has triggered intense efforts by the scientific community for accurate assessment of this building stock. Most of the proposed procedures for the prediction of building strength and deformation indices were validated by assembling databases of RC column specimens tested under axial load and reversed cyclic lateral drift histories. Usually a column structural behavior is assessed by considering all involving mechanisms of behavior, namely flexure with or without the presence of axial load, shear and anchorage. In the present paper a force-based fiber beam/column element was developed accounting for shear and tension stiffening effects in order to provide an analytical test-bed for simulation of experimental cases such as the lightly reinforced columns forced to collapse. Their peculiar characteristics are the outcome of the shear – flexure interaction mechanism modeled here based on the Modified Compression Field Theory (MCFT) and the significant contribution of the tensile reinforcement pullout from its anchorage to the total column’s lateral drift. These features are embedded in this first-proposed stand-alone Windows program named “Phaethon” -with user’s interface written in C++ programming language code- aiming to facilitate engineers in executing analyses both for rectangular and circular substandard RC columns.

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Triani, Triani, and Siti Nur Amiin. "Pengaruh Profitabilitas dan Kualitas Pengungkapan Corporate Social Responsibility terhadap Harga Saham." Jurnal Ilmiah Aset 21, no. 2 (March 6, 2020): 129–35. http://dx.doi.org/10.37470/1.21.2.154.

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This study aims to determine the effect of Earning Per Share (EPS), Return On Equity (ROE) and Quality of CSR on LQ 45 Company Stock Prices on the Indonesia Stock Exchange in 2015-2017. The population of this study was 45 companies and the sample was 36 LQ 45 companies listed on the Indonesia Stock Exchange for the period 2015-2017. The method of analysis uses classical assumption test calculations and analysis tools using multiple linear regression with SPSS software. Partial results show that Earning Per Share (X1) and Return On Equity (X2) have a significant influence on stock prices, while the quality of CSR (X3) does not affect stock prices. Simultaneously test all Earning Per Share (EPS), Return On Equity (ROE) and Quality of CSR have an effect on the Stock Price of LQ 45 companies listed on the Indonesia Stock Exchange in 2015-2017.

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Bawono, Anton, and Imamul Mutaqin. "Analysis of Macroeconomics Effects on the Indonesian Sharia Stock Index." SERAMBI: Jurnal Ekonomi Manajemen dan Bisnis Islam 1, no. 2 (July 31, 2019): 1–12. http://dx.doi.org/10.36407/serambi.v1i2.66.

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Purpose- The purpose of this study was to analyze the response shown by the Indonesian sharia stock index (ISSI) against the shock that occurred in inflation, IDR / USD exchange rate, interest rate, money supply (JUB), world oil prices and world gold prices. Methods- This research is quantitative research using the VAR model as data analysis. The data have been obtained and analyzed using Eviews software tool version 9. Findings- These results indicate that the ISSI responded negatively and permanently against shock happens to inflation, ISSI responded negatively and permanently against the shock that occurred at the BI Rate, the ISSI responded positively and permanently to the shock that occurred in world oil prices, the ISSI responded positively and permanently to the shock that occurred at world gold prices. Research implications- Investors should pay attention to changes that might occur in inflation, interest rate, world oil prices and world gold prices because in the results of this study show that the stock index will respond at least 10 months ahead when inflation, BI Rate, world oil prices and world gold prices experience shock. The government is expected to maintain economic stability so investors remain interested in investing in the domestic stock market

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Sumantri, Vietha Devia Sagita. "Analysis Factors Affecting Indonesia Stock Market (Case Studies on Consumer Goods Index)." ACTA VŠFS 14, no. 1 (April 2020): 10–23. http://dx.doi.org/10.37355/acta-2020/1-01.

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This study aims to examine the eﬀect of exchange rate and inﬂation on the stock market. The exchange rate used is the Rupiah against the US Dollar and the Consumer Price Index as a measure of inﬂation. While the sector used as a stock market case study is the Consumer Goods Index Sector. The study period during 2010–2017. The method used multiple linear regression with R software. The classic assumption test results show the existence of autocorrelation problems, but can be correcting by the Cochrane-Orcutt method on Eviews after 8 model iterations. The results of multiple linear regression tests showed that the exchange rate has a significant negative eﬀect, while inﬂation has no significant eﬀect on the Consumer Goods Index.

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Benghali, Sofiane Mohamed el Amine, and Ali Kherraz. "Assessment of the biological reference point F0.1 of Greater Forkbeard, in the bay of Mostaganem west Algeria." South Asian Journal of Experimental Biology 11, no. 1 (February 19, 2021): 8–14. http://dx.doi.org/10.38150/sajeb.11(1).p8-14.

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The Biological Reference Points are values of the level of fishing mortality or of the biomass of the stock which seek a long-term sustainable exploitation of the stocks, with the best possible catch. Von Bertalanffy's growth parameters: L∞ = 39.64 (cm), K = 0.36 (year-1), t0 = -0.22 (year), W∞ = 454.85 (g), and the monthly monitoring of size frequencies, allowed to identify the size of first sexual maturity L50, total mortality (Z = 2.11), natural mortality (M = 0.57) and fishing mortality (F = 1.54), all these values were evaluated in the objective to estimate the biological reference points. The assessment was performed using length cohort analysis (LCA) and biomass and yield per recruit’s analyses as implemented in VIT4Win software, the program reconstructs the population using mortality vectors and the production per recruit analysis is based on fishing mortality (F). The values of mortality determined seem concentrated on individuals with a size between 22 and 26 cm Lt, Maximum Sustainable Yield MSY 43.25g,the total balanced biomass was estimated at 3.84 t and the yield per recruit analysis (Y/R = 27.87 g) based on current fishing effort showed that the stock is at its minimum operating limit.

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Rigin, Anton Mikhailovich, and Sergey Andreevich Shershakov. "Method of Performance Analysis of Time-Critical Applications Using DB-Nets." Proceedings of the Institute for System Programming of the RAS 33, no. 3 (2021): 109–22. http://dx.doi.org/10.15514/ispras-2021-33(3)-9.

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These days, most of time-critical business processes are performed using computer technologies. As an example, one can consider financial processes including trading on stock exchanges powered by electronic communication protocols such as the Financial Information eXchange (FIX) Protocol. One of the main challenges emerging with such processes concerns maintaining the best possible performance since any unspecified delay may cause a large financial loss or other damage. Therefore, performance analysis of time-critical systems and applications is required. In the current work, we develop a novel method for a performance analysis of time-critical applications based on the db-net formalism, which combines the ability of colored Petri nets to model a system control flow with the ability to model relational database states. This method allows to conduct a performance analysis for time-critical applications that work as transactional systems and have log messages which can be represented in the form of table records in a relational database. One of such applications is a FIX protocol-based trading communication system. This system is used in the work to demonstrate applicability of the proposed method for time-critical systems performance analysis. However, there are plenty of similar systems existing for different domains, and the method can also be applied for a performance analysis of these systems. The software prototype is developed for testing and demonstrating abilities of the method. This software prototype is based on an extension of Renew software tool, which is a reference net simulator. The testing input for the software prototype includes a test log with FIX messages, provided by a software developer of testing solutions for one of the global stock exchanges. An application of the method for quantitative analysis of maximum acceptable delay violations is presented. The developed method allows to conduct a performance analysis as a part of conformance checking of a considered system. The method can be used in further research in this domain as well as in testing the performance of real time-critical software systems.

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Chen, Yu, Ruixin Fang, Ting Liang, Zongyu Sha, Shicheng Li, Yugen Yi, Wei Zhou, and Huilin Song. "Stock Price Forecast Based on CNN-BiLSTM-ECA Model." Scientific Programming 2021 (July 8, 2021): 1–20. http://dx.doi.org/10.1155/2021/2446543.

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Financial data as a kind of multimedia data contains rich information, which has been widely used for data analysis task. However, how to predict the stock price is still a hot research problem for investors and researchers in financial field. Forecasting stock prices becomes an extremely challenging task due to high noise, nonlinearity, and volatility of the stock price time series data. In order to provide better prediction results of stock price, a new stock price prediction model named as CNN-BiLSTM-ECA is proposed, which combines Convolutional Neural Network (CNN), Bidirectional Long Short-term Memory (BiLSTM) network, and Attention Mechanism (AM). More specifically, CNN is utilized to extract the deep features of stock data for reducing the influence of high noise and nonlinearity. Then, BiLSTM network is employed to predict the stock price based on the extracted deep features. Meanwhile, a novel Efficient Channel Attention (ECA) module is introduced into the network model to further improve the sensitivity of the network to the important features and key information. Finally, extensive experiments are conducted on the three stock datasets such as Shanghai Composite Index, China Unicom, and CSI 300. Compared with the existing methods, the experimental results verify the effectiveness and feasibility of the proposed CNN-BILSTM-ECA network model, which can provide an important reference for investors to make decisions.

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Oleyinka, Okeyo, and Tyronni Chadire. "The Influence of Accounting Information on Stock Prices of Food and Beverage Manufacturing Companies." Journal La Bisecoman 2, no. 3 (September 6, 2021): 11–16. http://dx.doi.org/10.37899/journallabisecoman.v2i3.406.

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The purpose of this study is to determine the effect of accounting information on stock prices of manufacturing companies in the food and beverage sub-sector This research takes place at the Stock Market office. The sample selection method in this study is a purposive sampling method with a total sample of 5 companies. The data collection techniques collect data on the company's financial statements during the research period. The data analysis method used was multiple regression with the help of SPSS for windows 25.00 software. The results showed that 1) Based on the results of data analysis, the coefficient values of ROA, ROE, NPM, and EBIT showed an effect on stock prices simultaneously. 2) Based on the results of data analysis ROA, ROE, NPM partially significant effect on stock prices, while EBIT has no effect on stock prices of manufacturing companies in the food and beverage sub-sector on the Stock Market. 3) The most dominant variable that influences ROA, ROE, NPM and EBIT on stock prices of manufacturing companies in the food and beverage sub-sector on the Stock Market is the ROA variable

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El qendouci, Mouna, Fatima Wariaghli, Mehria Saadaoui, Lobna Boudaya, Lassad Neifar, Abderrahim Sadak, and Ahmed Yahyaoui. "Stock Identification of Engraulis encrasicolus (Linnaeus, 1758) by Discriminant Function Analysis (DFA) of Morphometric Characters in The North of Atlantic and Mediterranean Moroccan Coasts." Turkish Journal of Fisheries and Aquatic Sciences 21, no. 11 (July 14, 2021): 553–58. http://dx.doi.org/10.4194/1303-2712-v21_11_03.

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The European anchovy, Engraulis encrasicolus (Linnaeus, 1758) is a small pelagic fish found in the eastern Atlantic, the Mediterranean Sea and the Black Sea. Anchovy (E. encrasicolus) are among the important finfishes harvested in Moroccan coasts. The stock structure of European anchovy in NW Africa is not truly known (FAO, 2013). To effectively manage the anchovy fisheries, it is important to understand the anchovy stock structure. Therefore, discriminant function analysis (DFA) based on morphometric characters was conducted on a total of 204 adult anchovy specimens, seasonally collected by commercial fishing vessels from the region of Mehdia in the North Atlantic area and from the region of M’diq in the Mediterranean coast during the year 2019. Body shape variation, which is often environmentally induced, may provide a good record population structuring. Our data were subjected to univariate statistics of variance (ANOVA) by using SPSS 20 software version. The morphometric characteristics show a separation of two stocks of Engraulis encrasicolus between the two localities. These findings will have major implications for anchovy fisheries management in Morocco.

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Narayan, Parab, and Y. V. Reddy. "Exploring the Causal Relationship Between Stock Returns, Volume, and Turnover across Sectoral Indices in Indian Stock Market." Metamorphosis: A Journal of Management Research 16, no. 2 (November 12, 2017): 122–40. http://dx.doi.org/10.1177/0972622517730140.

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The traditional saying “Market Discounts Everything” is applicable to stock returns, trading volume, and turnover as well. The present study is an analytical attempt to examine the causal relationship between stock returns, trading volume, and turnover across 10 sectoral indices of National Stock Exchange (NSE) for the period 2006–2016. To critically examine this relation, the study uses various statistical techniques such as descriptive statistics, correlation analysis, regression analysis, and econometric tests such as Granger causality test and augmented Dickey–Fuller test. The required analyses have been performed using statistical software E-views, SPSS, and Microsoft Excel. The study noticed a weak positive relationship between stock returns and turnover for Nifty Auto Index, Nifty Bank Index, Nifty Financial Services Index, Nifty Media Index, Nifty Metal Index, and Nifty Private Bank Index. The study also found a significant impact of turnover on stock returns in the case of Nifty Auto Index, Nifty Bank Index, Nifty FMCG Index, Nifty Metal Index, and Nifty Pharma Index and a significant impact of volume on stock returns in the case of Nifty Bank Index, Nifty FMCG Index, and Nifty Pharma Index. Augmented Dickey–Fuller test suggests that there exists no unit root in the data ( p < 1) and the data are stationary. It is evident from the study that the causal relationship between stock returns, turnover, and volume varies across the sectoral indices.

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Wang, Jianjia, Xingchen Guo, Weimin Li, Xing Wu, Zhihong Zhang, and Edwin R. Hancock. "Statistical mechanical analysis for unweighted and weighted stock market networks." Pattern Recognition 120 (December 2021): 108123. http://dx.doi.org/10.1016/j.patcog.2021.108123.

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Naeem, Mahpara, and Sadaf Mustafa Sadaf Mustafa. "Is Pakistan stock exchange a true reflector of economic requisite??" Global Journal for Management and Administrative Sciences 1, no. 2 (December 31, 2020): 1–17. http://dx.doi.org/10.46568/gjmas.v1i2.20.

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Stock market returns, another indicator of financial health of stock market and investors as well. Deviations in returns may vary country to country, investor to investor and market to market. There are many causes behind deviations in returns such as micro and macro variables. This study is aimed to identify causes behind stock market deviation theoretically and practically. Time span of 2002-2018 is examined as a sample year for practical analysis while literature on implementation of economic theories is considered for theoretical analysis. Statistical software EVIEWS is employed on the driven equation to conclude practical inferences by drawing critical region and sign of coefficient. Results indicates that EMH and APT theories exist in Pakistan while CAMP approach is invalid for Pakistan Stock Exchange. Furthermore, practically stock returns of Pakistan are not true reflector of economic requisite of Pakistan.

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Gifford, Robert B., Alexander R. Bandar, John P. Coulter, and Wojciech Z. Misiolek. "The Analysis and Control of Micro-Hardness Distribution During Wire Drawing." Journal of Manufacturing Science and Engineering 126, no. 2 (May 1, 2004): 247–54. http://dx.doi.org/10.1115/1.1688380.

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During wire drawing processes a critical parameter is the micro-hardness distribution imposed. The present numerical and experimental investigation focused on the effects of and interdependence between processing parameters such as die angle, bearing length, lubrication, and draw speed during wire drawing. The micro-hardness distribution imparted by the drawing process was selected as the focal product quality attribute. The goal of the study was to evaluate the ability to create desired hardness levels in a drawn wire product. The numerical component of the study was performed using DEFORM-2D™, a commercially available metal forming software package based on the finite element method. In addition, experimental verifications of the software predictions were completed wherever possible. Full factorial designs of the processing parameters were studied, and it was found that the final hardness distribution was primarily affected by the die angle. Interactions between the four processing parameters were negligible. Based upon this finding, it was concluded that strength and hardness variations inherent to stock wire could be detected and minimized during wire drawing through the appropriate science-based selection of die angle. This could dramatically enhance the consistency of the wide range of common metal products that are manufactured from wire stock.

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Pauzi Harahap, Nurul Ramadhani, Idhar Yahya, and Abdillah Arif Nasution. "The Effect of Free Cash Flow, Debt to Equity Ratio, Working Capital Turnover and Earnings Per Share on Stock Prices with Stock Beta as Moderating Variable in Construction Sub-Sector Companies Listed on the IDX for the 2013-2019 Period." International Journal of Research and Review 8, no. 8 (August 17, 2021): 244–53. http://dx.doi.org/10.52403/ijrr.20210834.

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The purpose of this study aims to discover the effect of free cash flow, debt to equity ratio working capital turnover, and earning per share on stock price with stock beta as moderating variables. This research was conducted on Construction Sub-Sector Companies listed on the Indonesia Stock Exchange for 2013-2019. The technique in this study uses a purposive sampling technique. The sampling technique shows that the research sample is ten companies with seven years of research, so the number of observations in this study is 70. The data analysis method used in this study is Panel Data Regression Analysis which was carried out with the help of EViews software. The results showed that free cash flow, working capital turnover did not significantly affect stock prices and earnings per share, and the debt to equity ratio had a significant effect on stock prices. The stock beta variable can moderate the effect of free cash flow, debt to equity ratio, working capital turnover, and earnings per share on stock prices. Keywords: Free Cash Flow, Working Capital Turnover, Earnings Per Share and Debt to Equity Ratio, Stock Price and Stock Beta.

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Seng, Jia-Lang, and Hsiao-Fang Yang. "The association between stock price volatility and financial news – a sentiment analysis approach." Kybernetes 46, no. 8 (September 4, 2017): 1341–65. http://dx.doi.org/10.1108/k-11-2016-0307.

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Purpose The purpose of this study is to develop the dictionary with grammar and multiword structure has to be used in conjunction with sentiment analysis to investigate the relationship between financial news and stock market volatility. Design/methodology/approach An algorithm has been developed for calculating the sentiment orientation and score of data with added information, and the results of calculation have been integrated to construct an empirical model for calculating stock market volatility. Findings The experimental results reveal a statistically significant relationship between financial news and stock market volatility. Moreover, positive (negative) news is found to be positively (negatively) correlated with positive stock returns, and the score of added information of the news is positively correlated with stock returns. Model verification and stock market volatility predictions are verified over four time periods (monthly, quarterly, semiannually and annually). The results show that the prediction accuracy of the models approaches 66% and stock market volatility with a particular trend-predicting effect in specific periods by using moving window evaluation. Research limitations/implications Only one news source is used and the research period is only two years; thus, future studies should incorporate several data sources and use a longer period to conduct a more in-depth analysis. Practical implications Understanding trends in stock market volatility can decrease risk and increase profit from investment. Therefore, individuals or businesses can feasibly engage in investment activities for profit by understanding volatility trends in capital markets. Originality/value The ability to exploit textual information could potentially increase the quality of the data. Few scholars have applied sentiment analysis in investigating interdisciplinary topics that cover information management technology, accounting and finance. Furthermore, few studies have provided support for structured and unstructured data. In this paper, the efficiency of providing the algorithm, the model and the trend in stock market volatility has been demonstrated.

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Journal articles on the topic 'Stock analysis software'

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