scholarly journals An explanatory model of stock prices in the Brazilian transport sector

2021 ◽  
Vol 9 (18) ◽  
Author(s):  
Alexandre Rodrigues Da Silva
Keyword(s):  
Stock Prices ◽  
Explanatory Model ◽  
Share Price ◽  
Stock Index ◽  
Transport Sector ◽  
Rate Variation ◽  
Analysis Tool ◽  
Linear Coefficient ◽  
Financial Profile ◽  
Linear Regressions

The aim of this study is to establish an explanatory model of the variation of the prices of shares from the transport sector listed in B3. Methodology: Daily stock prices were collected from companies in the transport sector listed on B3 since its IPO until December 31, 2019. Companies that were not on the floor on this date were discarded. As an analysis tool, simple and multiple linear regressions were used. The dependent variable (annual variation in the share price of the transport sector) was subjected to variables such as exchange rate variation, economic activity, as well as important inputs such as wages and fuel, and the Ibovespa variation. Results and conclusions: a model with less variables (Ibovespa variation and inflation variation) was adopted, where a determination coefficient of 0.5131 was obtained (linear coefficient of 0.716). The model, therefore, is closely linked to the stock index and the variation in the inflation index, giving a much more financial profile to these assets.

scholarly journals Financial Ratios and Share Prices of JII70 Indexed Companies for the 2018-2020 Period

2021 ◽  
Vol 6 (1) ◽  
pp. 23
Author(s):  
Ahmad Fauzan ◽  
Rindang Matoati
Keyword(s):  
Panel Data ◽  
Capital Market ◽  
Stock Prices ◽  
Stock Price ◽  
Share Price ◽  
Stock Index ◽  
Financial Ratios ◽  
Financial Ratio ◽  
Panel Data Regression ◽  
Data Regression

  Abstract: The sharia capital market in Indonesia has grown over the last five years. One of the members of the sharia capital market instrument is sharia shares. During the 2015-2020 period, the number of Islamic stock issuers continued to grow. The stock index is used by investors as a tool to choose stocks that suit their needs. IDX has issued three sharia stock indexes, and the most recent one is the JII70 index. A stock index is a collection of statistics about the price movement of a group of stocks that is evaluated periodically. One of the many factors that influence stock prices is the company's financial ratios. This study aims to analyze the influence of financial ratio factors such as Current Ratio (CR), Debt to Equity Ratio (DER), Total Assets Turnover (TATO), Return on Equity (ROE) and Earning per Share (EPS) on the stock price of JII70 indexed companies. The data used is secondary data in the form of JII70 indexed company financial statements in the 2018-2020 period. The method of determining the sample using purposive sampling. This research uses panel data regression analysis method. The results of this study show a significant effect of the DER and EPS variables on stock prices, while the CR, TATO and ROE variables do not significantly affect stock prices.Keywords: Share Price, JII70, Financial Ratio, Panel Data Regression, Sharia Shares

scholarly journals Analysis of the Influence of the Price of Raw Oil and Natural Gas on the Prices of Indices and Shares of the Turkish Stock Exchange

2021 ◽  
Vol 66 (1) ◽  
pp. 151-166
Author(s):  
Nurkhodzha Akbulaev ◽  
Basti Aliyeva ◽  
Shehla Rzayeva
Keyword(s):  
Natural Gas ◽  
Stock Prices ◽  
Stock Exchange ◽  
Share Price ◽  
Stock Index ◽  
Linear Regression Models ◽  
Oil And Natural Gas ◽  
Statistical Program ◽  
The Cost ◽  
The Impact

This article is a review on the impact of prices and their dependence on the cost of oil and natural gas on the world stock markets. The main studies and results achieved in the field of the impact of prices on both the stock index and industrial stocks and the dependence on the level of oil prices are presented. The paper presents an econometric study on the choice of offers on the securities market that allows us to identify the main specifics of changes in prices for the stock index and industrial shares in the daily period from 13. 05. 2012 to 01. 12. 2019. The article uses methods for estimating the impact of the price of natural gas and WTI crude oil using the Gretl statistical program, taking into account the selection of the main correlation features of the price matrix. Of the 13 proposed research models, only one model showed its statistical insignificance. A paired linear model of the CocaCola share price dependence and its dependence on NGFO prices was presented and analyzed in detail. Based on the results of econometric modeling, linear regression models were constructed for the dependence of stock prices on the NGFO and WTISPOT prices. The Gretl environment allows you to evaluate the situation in the econometric environment and make a forecast based on the obtained models of the dependence of stock prices and make appropriate conclusions.

Effect Of Leverage, Inflation And GDP To Share Price Pt. Astra Otoparts Tbk.

ProBank ◽  
2018 ◽  
Vol 3 (2) ◽  
pp. 17-21
Author(s):  
Heriyanta Budi Utama ◽  
Florianus Dimas Gunurdya Putra Wardana
Keyword(s):  
Gross Domestic Product ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Sampling Technique ◽  
Share Price ◽  
Domestic Product ◽  
Coefficient Of Determination ◽  
Test Results ◽  
Purposive Sampling

The purpose of this study was to obtain empirical evidence about the effect of leverage, inflation and Gross Domestic Product (GDP) of the share price at PT. Astra Autopart, Tbk. companies in Indonesia Stock Exchange in 2011-2015. The sampling technique in this study using a purposive sampling. With the technique of purposive  sampling, all the members of the research samples by criteria. Samples that meet the criteria are used research data. Then followed the classic assumption test and test hypotheses by linear regression. The results of this study demonstrate the regression results in regression equation that Y = 2605,424 + 1561,550 X1 + 2,338 X2 + 38,994X3. T test results showed that the leverage anda GDP (Gross Domestic Product) is positive and significant effect on stock prices, while inflation is not positive and significant effect on stock prices. F test results showed that jointly leverage variables, inflation and GDP variables affecting the stock price significantly. The test results R2 (coefficient of determination) found that the variable leverage, inflation and GDP able to explain 35,4% of the stock price variable, while the remaining 64,6% is explained by other variables.Keywords: leverage, inflation, GDP, and the share priceThe purpose of this study was to obtain empirical evidence about the effect of leverage, inflation and Gross Domestic Product (GDP) of the share price at PT. Astra Autopart, Tbk. companies in Indonesia Stock Exchange in 2011-2015.The sampling technique in this study using a purposive sampling. With the technique of purposive  sampling, all the members of the research samples by criteria. Samples that meet the criteria are used research data. Then followed the classic assumption test and test hypotheses by linear regression.The results of this study demonstrate the regression results in regression equation that Y = 2605,424 + 1561,550 X1 + 2,338 X2 + 38,994X3. T test results showed that the leverage anda GDP (Gross Domestic Product) is positive and significant effect on stock prices, while inflation is not positive and significant effect on stock prices. F test results showed that jointly leverage variables, inflation and GDP variables affecting the stock price significantly. The test results R2 (coefficient of determination) found that the variable leverage, inflation and GDP able to explain 35,4% of the stock price variable, while the remaining 64,6% is explained by other variables.Keywords: leverage, inflation, GDP, and the share price

PENGARUH RASIO KEUANGAN TERHADAP HARGA SAHAM PERUSAHAAN LQ45 PERIODE 2013-2017

2019 ◽  
Vol 5 (1) ◽  
pp. 1-17
Author(s):  
Nuri Maulana Ikhsan ◽  
Yohanes Rully Dermawan
Keyword(s):  
Stock Prices ◽  
Share Price ◽  
Financial Ratios ◽  
Total Asset ◽  
Current Ratio ◽  
Return On Equity ◽  
Book Value ◽  
Earnings Per Share ◽  
Asset Turnover ◽  
Equity Ratio

This study aims to determine the effect of financial ratios on stock prices. Financial ratios used in this study is the Current Ratio, Debt to Equity Ratio, Return On Equity, Total Asset Turnover, Earning Per Share, and Price to Book Value. The type of research used is quantitative to observe the effect of financial ratios on stock prices. This study used a purposive sampling method with a total sample of 20 companies registered in the LQ45 index for the period 2013-2017 and fulfilling the research criteria. The statistical method used is multiple linear regression analysis The results of this study indicate that partially, the variable debt to equity ratio, return on equity, total asset turnover, earnings per share, and price to book value have a significant partial effect on stock prices, while the current ratio variable does not have a partial significant effect on stock prices. Simultaneously the current ratio variable, debt to equity ratio, return on equity, total asset turnover, earnings per share, and price to book value have a significant simultaneous effect on stock prices. And the most dominant influential variable is earnings per share. Keywords:  Current Ratio, Debt to Equity Ratio, Return On Equity, Total Asset Turnover, Earning Per Share, Price to Book Value, and Stock Price.  

scholarly journals PENGARUH INFLASI, PROFITABILITAS, STRUKTUR MODAL, DAN EARNING PER SHARE TERHADAP HARGA SAHAM PERUSAHAAN CONSUMER GOODS

2019 ◽  
Vol 8 (6) ◽  
pp. 3930
Author(s):  
Septia Wulandari Suarka ◽  
Ni Luh Putu Wiagustini
Keyword(s):  
Data Collection ◽  
Consumer Goods ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Participant Observation ◽  
Share Price ◽  
Significant Positive Effect ◽  
Positive Effect

The purpose of this study is to analyze the significance of the influence of inflation, ROE, DER, and EPS on stock prices. This research was conducted at Concern Goods Companies that are listed on the Indonesia Stock Exchange (IDX) for the 2015-2017 period. The number of samples of this study were 31 companies. Data collection is done by the method of non-participant observation. Based on the results of the analysis found that inflation, ROE. DER, and EPS simultaneously have a significant effect on stock prices. Partially Inflation and DER have no significant effect on stock prices, this indicates that investors do not see Inflation and DER as a decision to buy shares. While partially ROE and EPS have a significant positive effect on stock prices, this shows that investors pay attention to ROE and EPS in deciding to invest. The higher the ROE and EPS, the higher the investor's interest in investing in the company's capital, so that the share price will go up. Keywords: Inflation, ROE, DER, EPS, stock price    

Rajeev Pundir

2021 ◽  
Vol 17 (2) ◽  
pp. 105-113
Author(s):  
Rajeev Pundir
Keyword(s):  
Capital Markets ◽  
Capital Market ◽  
Poverty Line ◽  
Vital Role ◽  
Capital Inflows ◽  
Share Price ◽  
Stock Index ◽  
Recent Past ◽  
Indian Government ◽  
Asset Class

Put not your trust in money, but put your money in trust.”A capital market can provide huge impetus to the development of any economy .so, it can be said that the growth and sustainability of capital markets plays an important role towards the development of the economy. It is being observed that huge fluctuations are happening in Indian capital market in recent past, but with the help of proper mechanism, which is being observed in India and after examining various risk factors involved in capital markets, we attempt to say that the growth which has been observed in Indian capital market in recent past is a realty, but not a myth. Right from the independence, thanks to steps initiated by the Indian government especially after the post liberalization era. A huge growth has been observed in the aspects of quality and quantity. Huge increase has been observed in the volumes of trade. We know that capital markets play a vital role in Indian economy, the growth of capital markets will be helpful in raising the per-capita income of the individuals, decrease the levels of un-employment, and thus reducing the number of people who lies below the poverty line. With the increasing awareness in the people they start investing in capital markets with long-term orientations, which would provide capital inflows to the sectors requiring financial assistance.“Hedge risk; make the derivatives market your investment option”Derivative is finally engineered instruments which derive its value from price of a specific asset. Value of Equity Derivatives is derived from share price of any company or share index. In India trading of two types of derivatives are permitted – Futures and Options. Derivatives trading desks face a growing number of challenges – more sophisticated derivative instruments, fiercer competition, and stricter risk reporting and compliance requirements. It is now common to trade options with multi-asset-class underlying instruments quoted in different currencies, such as an option offering the best return between a Brazilian bond and a U.S. stock index. Investor uses the derivatives as an edged sword. Derivatives instruments are like a mother’s womb that cares of her baby (Investor) from volatility in the market. In nutshell this study is an effort to analyze the trading mechanism which has been followed by the investors in current scenario.

العلاقة التبادلية بين سعر الصرف وأسعار الأسهم دراسة تطبيقية في سوق اسطنبول للأوراق المالية للمدة 2005-2020

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
سعدالله ألنعيمي
Keyword(s):  
Exchange Rate ◽  
Stock Prices ◽  
Negative Impact ◽  
Reciprocal Relationship ◽  
Nominal Exchange Rate ◽  
Share Price ◽  
Theoretical Interpretation ◽  
Short Term ◽  
The Exchange Rate

The study aims to analyzing the reciprocal relationship between the nominal exchange rate of the Turkish lira versus the U.S. dollar and the stock prices of the companies listed on the Istanbul Stock Exchange (ISE) expressed in the general market index for the period from 2005 to 2020 with 192 monthly observations, based on the traditional theory and the theory of portfolio balance model in theoretical interpretation for that relationship, aiming to identify the effect of the exchange rate on stock prices, as well as to analyze the causal relationship between those variables and to identify which of them is the cause or which is the result, using the Autoregressive Distributed Lag (ARDL) model. The research found that the exchange rate has a positive effect on stock prices in the long term, despite the emergence of the negative impact in the short term, but the long-term relationship has corrected the course of the short-term relationship with a time period not exceeding one month, in addition to proving that this relationship takes one direction. From the exchange rate towards stock prices, that is, the exchange rate is the reason and stock prices are the result, therefore the results of this research helps investors to predict future trends of stock prices depending on the exchange rate changes, and it also enables the companies, especially those with foreign transactions, to manage price risks the exchange rate in order to avoid its negative impact on its share price, as it represents an obstacle to achieving its main goal of maximizing the share price

scholarly journals Predicting Stock Market Index Using Hybrid Intelligence Model

2018 ◽  
Vol 7 (3.15) ◽  
pp. 36 ◽  
Author(s):  
Sarah Nadirah Mohd Johari ◽  
Fairuz Husna Muhamad Farid ◽  
Nur Afifah Enara Binti Nasrudin ◽  
Nur Sarah Liyana Bistamam ◽  
Nur Syamira Syamimi Muhammad Shuhaili
Keyword(s):  
Time Series ◽  
Stock Prices ◽  
Linear Models ◽  
Forecast Error ◽  
Arima Model ◽  
Real Data ◽  
Stock Index ◽  
Support Vector ◽  
Ann Model ◽  
Stock Market Index

Predicting financial market changes is an important issue in time series analysis, receiving an increasing attention due to financial crisis. Autoregressive integrated moving average (ARIMA) model has been one of the most widely used linear models in time series forecasting but ARIMA model cannot capture nonlinear patterns easily. Generalized autoregressive conditional heteroscedasticity (GARCH) model applied understanding of volatility depending to the estimation of previous forecast error and current volatility, improving ARIMA model. Support vector machine (SVM) and artificial neural network (ANN) have been successfully applied in solving nonlinear regression estimation problems. This study proposes hybrid methodology that exploits unique strength of GARCH + SVM model, and GARCH + ANN model in forecasting stock index. Real data sets of stock prices FTSE Bursa Malaysia KLCI were used to examine the forecasting accuracy of the proposed model. The results shows that the proposed hybrid model achieves best forecasting compared to other model.  

scholarly journals Multivariate and Online Prediction of Closing Price Using Kernel Adaptive Filtering

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Shambhavi Mishra ◽  
Tanveer Ahmed ◽  
Vipul Mishra ◽  
Manjit Kaur ◽  
Thomas Martinetz ◽  
...  
Keyword(s):  
Adaptive Filtering ◽  
Stock Prices ◽  
High Frequency ◽  
Time Windows ◽  
Stock Index ◽  
Level Data ◽  
Traditional Classification ◽  
Regression Problems ◽  
The Common ◽  
Online Prediction

This paper proposes a multivariate and online prediction of stock prices via the paradigm of kernel adaptive filtering (KAF). The prediction of stock prices in traditional classification and regression problems needs independent and batch-oriented nature of training. In this article, we challenge this existing notion of the literature and propose an online kernel adaptive filtering-based approach to predict stock prices. We experiment with ten different KAF algorithms to analyze stocks’ performance and show the efficacy of the work presented here. In addition to this, and in contrast to the current literature, we look at granular level data. The experiments are performed with quotes gathered at the window of one minute, five minutes, ten minutes, fifteen minutes, twenty minutes, thirty minutes, one hour, and one day. These time windows represent some of the common windows frequently used by traders. The proposed framework is tested on 50 different stocks making up the Indian stock index: Nifty-50. The experimental results show that online learning and KAF is not only a good option, but practically speaking, they can be deployed in high-frequency trading as well.

scholarly journals ANALISIS PERGERAKAN SAHAM PERUSAHAAN SUB SEKTOR FARMASI MENGGUNAKAN INDIKATOR BOLLINGER BAND DI TENGAH PANDEMI COVID-19

2020 ◽  
Vol 3 (2) ◽  
pp. 77-88
Author(s):  
Intan Elita ◽  
K. Bagus Wardianto ◽  
M. Iqbal Harori
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Sampling Method ◽  
Sample Selection ◽  
T Test ◽  
Analysis Tool ◽  
Selection Technique ◽  
Purposive Sampling ◽  
Analysis Technique ◽  
Significant Difference

This study aims to measure the accuracy of technical analysis using the Bollinger Band indicator in predicting stock prices in the middle of pandemic covid-19. The concept in this study is to compare daily stock price predictions according to technical indicators with the closing prices that occured on that day. Sample selection technique used in this research used a purposive sampling method and obtained 9 pharmaceutical sub-sector companies listed on the IDX from February to April 2020. The type of data used is a chart of the company's daily stock price movements obtained from finance.yahoo.com. The data analysis technique used was the paired sample t-test and used the SPSS 26 analysis tool. The results of this study indicate that the Bollinger indicator does not have a significant difference. ABSTRAK Penelitian ini bertujuan untuk mengukur keakuratan analisis teknikal dengan indikator Bollinger Band dalam memprediksi harga saham pada masa pandemi Covid-19. Konsep pada penelitian ini adalah membandingkan prediksi harga saham harian menurut indikator teknikal dengan harga penutupan yang terjadi pada hari tersebut. Teknik pengambilan sampel dalam penelitian ini menggunakan metode purposive sampling dan diperoleh sebanyak 9 perusahaan sub sektor farmasi yang terdaftar di BEI selama Februari hingga April 2020. Jenis data yang digunakan yaitu berupa grafik pergerakan harga saham harian perusahaan yang diperoleh dari finance.yahoo.com. Teknik analisis data yang digunakan adalah uji independent sample t-test dan menggunakan alat analisis program SPSS 26. Hasil penelitian ini menunjukkan bahwa indikator Bollinger tidak memiliki perbedaan yang signifikan.

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