scholarly journals The Kumaraswamy Lindley Regression Model with Application on the Egyptian Stock Exchange

2021 ◽  
Vol 18 (1) ◽  
pp. 1-11
Author(s):  
Samy Abdelmoezz ◽  
Salah M. Mohamed
Keyword(s):  
Regression Model ◽  
Stock Exchange ◽  
Maximum Likelihood Estimates ◽  
Finite Sample ◽  
Monte Carlo Simulation Study ◽  
Hazard Functions ◽  
Martingale Residual ◽  
Egyptian Stock Exchange ◽  
Regression Residual ◽  
Residual Deviance

We introduce and study the Kumaraswamy Lindely Distribution (KLD)  model, which has increasing, decreasing, upside-down bathtub and bathtub shaped hazard functions.. We perform a Monte Carlo simulation study to assess the finite sample behavior of the maximum likelihood estimates of the parameters. We define a new regression model based on the new distribution. The new regression was applied to data from the Egyptian stock exchange in the period of (2015-2019). Finally, we study some properties of regression Residual analysis The martingale residual, Deviance component residual.

The beta exponentiated Nadarajah-Haghighi distribution: theory, regression model and application

2019 ◽  
Vol 69 (4) ◽  
pp. 939-952
Author(s):  
Abdus Saboor ◽  
Muhammad Nauman Khan ◽  
Gauss M. Cordeiro ◽  
Ibrahim Elbatal ◽  
Rodrigo R. Pescim
Keyword(s):  
Monte Carlo Simulation ◽  
Diabetic Retinopathy ◽  
Regression Model ◽  
Quantile Function ◽  
Maximum Likelihood Estimates ◽  
Finite Sample ◽  
Monte Carlo Simulation Study ◽  
Hazard Functions ◽  
Mathematical Properties ◽  
New Distribution

Abstract We introduce and study the beta exponentiated Nadarajah-Haghighi model, which has increasing, decreasing, upside-down bathtub and bathtub shaped hazard functions. Some of its mathematical properties are determined including a power series for the quantile function. We perform a Monte Carlo simulation study to assess the finite sample behavior of the maximum likelihood estimates of the parameters. We define a new regression model based on the new distribution. The potentiality of this regression model is proved empirically by means of a real dataset related to diabetic retinopathy study.

scholarly journals The Lagged Effect of Advertising Expenditures on the Financial Measures of Brand Equity in the Egyptian Context

2021 ◽  
Vol 04 (09) ◽  
Author(s):  
Nermin M. Gohar
Keyword(s):  
Brand Equity ◽  
Quantitative Research ◽  
Stock Exchange ◽  
Secondary Data ◽  
Financial Reports ◽  
Financial Measures ◽  
The Impact ◽  
Corporate Brands ◽  
The Relationship ◽  
Egyptian Stock Exchange

This research intends to fill the gap in the literature by studying the impact of lagged real advertising expenditures on different perspectives of brand equity in the Egyptian context, which are: Firm-based and Market-based brand equity. The research follows the quantitative research-based approach, with the descriptive explanatory method. Secondary data was collected from firms’ financial reports of sixteen sectors for the period 2013 - 2020 to consider the effect of real advertising expenditures on firm-based and market-based brand equity models. Data was collected from 168 listed companies in the Egyptian stock exchange market, after deleting the financial institutions. The unit of analysis was the corporate brands and data collected was panel data analyzed using Eviews program – version 10, using GLS regression. Results showed that market risk significantly moderates the relationship between advertising expenditures and Firm-based and Market-based brand equity.

scholarly journals CAPITAL STRUCTURE DETERMINANTS OF PLANTATION SUB-SECTOR COMPANIES IN INDONESIA STOCK EXCHANGE PERIOD 2014 – 2018

2020 ◽  
Vol 1 (3) ◽  
pp. 455-468
Author(s):  
Septian Wildan Mujaddid ◽  
Bambang Santoso Marsoem
Keyword(s):  
Capital Structure ◽  
Regression Model ◽  
Significant Relationship ◽  
Stock Exchange ◽  
The Other ◽  
Corporate Liquidity ◽  
Independent Variables ◽  
Other Hand

The purpose of this study is to analyze the factors that influence the Debt to Asset Ratio which is a proxy of Capital Structure as the dependent variable. The independent variables studied as determinants of Capital Structure (DAR) include Size (SIZE), Profitability (ROA), Asset Structure (SA), and Corporate Liquidity (CR) using regression model. The population in this study are plantation sub-sector companies listed on the Indonesia Stock Exchange for the period 2014 - 2018. The findings suggest that ROA negatively significant affect DAR, while SA positively significant affect DAR. On the other hand, both SIZE & CR have no significant relationship with DAR

scholarly journals Trading Volume as a Predictor of Market Movement

2019 ◽  
Vol 8 (2) ◽  
pp. 57-69
Author(s):  
Edson Kambeu
Keyword(s):  
Logistic Regression ◽  
Stock Market ◽  
Regression Model ◽  
Trading Volume ◽  
Logistic Regression Model ◽  
Predictive Analytics ◽  
Stock Exchange ◽  
Stock Market Index ◽  
Trading Volumes ◽  
Popular Language

A logistic regression model is has also become a popular model because of its ability to predict, classify and draw relationships between a dichotomous dependent variable and dependent variables. On the other hand, the R programming language has become a popular language for building and implementing predictive analytics models. In this paper, we apply a logistic regression model in the R environment in order to examine whether daily trading volume at the Botswana Stock Exchange influence daily stock market movement. Specifically, we use a logistic regression model to find the relationship between daily stock movement and the trading volumes experienced in the recent five previous trading days. Our results show that only the trading volume for the third previous day influence current stock market index movement. Overall, trading volumes of the past five days were found not have an impact on today’s stock market movement. The results can be used as a basis for building a predictive model that utilizes trading as a predictor of stock market movement.

The relationship between intellectual capital and financial statements readability: the role of management characteristics

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahdi Salehi ◽  
Hassan Mohammadzadeh Moghadam ◽  
Zohreh Hajiha
Keyword(s):  
Regression Model ◽  
Intellectual Capital ◽  
Fixed Effects ◽  
Stock Exchange ◽  
Hypothesis Test ◽  
Financial Statements ◽  
Multiple Regression Model ◽  
Content Type ◽  
The Relationship

Purpose The present study aims to investigate the relationship between intellectual capital and the readability of financial statements with the mediating role of management characteristics of companies listed on the Tehran Stock Exchange. In other words, this research tries to find the answer to whether intellectual capital can positively affect the readability of financial statements. Design/methodology/approach A multivariate regression model was used to test the hypotheses for this purpose. The research hypotheses were tested using a sample of 1,309 observations listed on the Tehran Stock Exchange from 2012 to 2018 and a multiple regression model based on panel data and fixed-effects models. Findings The results indicate that intellectual capital has a positive and significant relationship with the readability of financial statements, which means that with increasing intellectual capital in companies, financial statements’ readability also increases. Based on the hypothesis test results, it has been determined that narcissism, accrual and real earnings management have a negative effect on the relationship between intellectual capital and the readability of financial statements. Originality/value Since the present study examines such an issue in emerging markets, it provides users, analysts and legal entities with useful information about management’s inherent and acquired characteristics that significantly impact the purchase of audit opinion. This study’s results also contribute to developing science and knowledge in this field and close the literature gap.

scholarly journals Price-Volume Granger Causality Tests in the Egyptian Stock Exchange (EGX)

2019 ◽  
Vol 8 (3) ◽  
pp. 48
Author(s):  
Kobana Abukari ◽  
Tov Assogbavi
Keyword(s):  
Trading Volume ◽  
Stock Exchange ◽  
Price Change ◽  
Wall Street ◽  
Diffusion Of Information ◽  
Bull Markets ◽  
Volume Relationship ◽  
Causality Tests ◽  
Sequential Information ◽  
Egyptian Stock Exchange

Using weekly Egyptian stock exchange data on the 34 most active companies stretching from 2011 to 2017, this study finds that price changes Granger cause trading volume up to 8 weeks (lags), supporting the sequential information arrival model in the EGX. We also find a robust contemporaneously positive asymmetric relationship between price change and trading volume, confirming two well-documented characteristics of the price-volume relationship as well as two major adages of Wall Street: “it takes volume to move prices” and “volume in bull markets is heavier than volume in bear markets”. Overall, our results imply that although there is some sequential diffusion of information, the EGX’s efforts at improving its microstructure through initiatives such as the 2009 Presidential Degree on structure and governance, appear to have helped in improving instantaneous access to information – as exemplified by our evidence of strong contemporaneous positive price-volume relationship.

scholarly journals Generalized Exponentiated Weibull Linear Model in the Presence of Covariates

2017 ◽  
Vol 6 (3) ◽  
pp. 75
Author(s):  
Tiago V. F. Santana ◽  
Edwin M. M. Ortega ◽  
Gauss M. Cordeiro ◽  
Adriano K. Suzuki
Keyword(s):  
Regression Model ◽  
Linear Model ◽  
Goodness Of Fit ◽  
Likelihood Function ◽  
Confidence Bands ◽  
Model Parameters ◽  
Random Component ◽  
Monte Carlo Simulation Study ◽  
New Model ◽  
Exponentiated Weibull

A new regression model based on the exponentiated Weibull with the structure distribution and the structure of the generalized linear model, called the generalized exponentiated Weibull linear model (GEWLM), is proposed. The GEWLM is composed by three important structural parts: the random component, characterized by the distribution of the response variable; the systematic component, which includes the explanatory variables in the model by means of a linear structure; and a link function, which connects the systematic and random parts of the model. Explicit expressions for the logarithm of the likelihood function, score vector and observed and expected information matrices are presented. The method of maximum likelihood and a Bayesian procedure are adopted for estimating the model parameters. To detect influential observations in the new model, we use diagnostic measures based on the local influence and Bayesian case influence diagnostics. Also, we show that the estimates of the GEWLM are  robust to deal with the presence of outliers in the data. Additionally, to check whether the model supports its assumptions, to detect atypical observations and to verify the goodness-of-fit of the regression model, we define residuals based on the quantile function, and perform a Monte Carlo simulation study to construct confidence bands from the generated envelopes. We apply the new model to a dataset from the insurance area.

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