scholarly journals Performances of LAD Regression, M-Regression and Quantile Regression Methods in order to Investigate Stock Prices of the Banks in the BIST Bank Index

2018 ◽  
Vol 6 (04) ◽  
Author(s):  
Umran Munire Kahraman ◽  
Neslihan Iyit
Keyword(s):  
Quantile Regression ◽  
Stock Prices ◽  
Robust Regression ◽  
Mean Squared Error ◽  
Stock Exchange ◽  
Standard Errors ◽  
Parameter Estimates ◽  
Regression Methods ◽  
Istanbul Stock Exchange ◽  
Error Terms

In this study, performances of LAD regression, M-regression, Q25 and Q75 quantile regression models as robust regression methods alternative to the classical LS method are compared in the case of violations from the normality assumption of the error terms and the presence of an outlier. By using these alternative regression methods, stock prices of the 12 commercial banks and 1 participation bank listed in the Istanbul Stock Exchange (BIST) bank index between 2012 and 2016 are investigated in terms of equity size and equity profitability. As a result of this study, M-regression is the most suitable robust regression model with the smallest value of the mean squared error (MSE) measure and the small values for the standard errors of the parameter estimates belonging to the equity size and equity profitability. The smaller the standard errors of the parameter estimates, the narrower the resulting confidence intervals are obtained in M- regression. The accuracy as a measure of closeness of parameter estimates to the true values of the parameters is also obtained higher in M-regression.

scholarly journals Marginal quantile regression for longitudinal data analysis in the presence of time-dependent covariates

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
I-Chen Chen ◽  
Philip M. Westgate
Keyword(s):  
Parameter Estimation ◽  
Longitudinal Data ◽  
Quantile Regression ◽  
Mean Squared Error ◽  
Time Dependent ◽  
Regression Methods ◽  
Squared Error ◽  
Highly Correlated ◽  
Time Dependent Covariates ◽  
Independence Structure

AbstractWhen observations are correlated, modeling the within-subject correlation structure using quantile regression for longitudinal data can be difficult unless a working independence structure is utilized. Although this approach ensures consistent estimators of the regression coefficients, it may result in less efficient regression parameter estimation when data are highly correlated. Therefore, several marginal quantile regression methods have been proposed to improve parameter estimation. In a longitudinal study some of the covariates may change their values over time, and the topic of time-dependent covariate has not been explored in the marginal quantile literature. As a result, we propose an approach for marginal quantile regression in the presence of time-dependent covariates, which includes a strategy to select a working type of time-dependency. In this manuscript, we demonstrate that our proposed method has the potential to improve power relative to the independence estimating equations approach due to the reduction of mean squared error.

Mixed integer programming approach for seasonal anomalies in stock markets: A case study for BIST

2018 ◽  
Vol 5 (2) ◽  
pp. 19-28
Author(s):  
Oguzhan Ahmet Arik
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Stock Prices ◽  
Stock Markets ◽  
Stock Exchange ◽  
Mixed Integer ◽  
Programming Approach ◽  
The Past ◽  
Istanbul Stock Exchange

This paper proposes a mixed integer programming approach for seasonal anomalies in stock markets and presents a case study for the XU030 index in the stock market of Istanbul Stock Exchange (BIST). Stock markets are significant for economies of countries all over the world. Investors get economical wealth or lose some of their investment by selling and buying stocks. Therefore, buying and selling times of stocks are so important. This paper investigates a well-known effect called as ‘Sell in May and Go Away’ by proposing a MIP approach that searches best times for buying and selling of stocks in a year. Furthermore, this paper includes a numerical example of XU030 stock prices for the past 5 years and shows that most of the XU030 stocks have seasonal anomalies.Keywords: First keyword, second keyword, third keyword, forth keyword.

Robust regression with asymmetric loss functions

2021 ◽  
pp. 096228022110120
Author(s):  
Liya Fu ◽  
You-Gan Wang
Keyword(s):  
Robust Regression ◽  
Parameter Estimates ◽  
Asymmetric Distribution ◽  
Simulation Studies ◽  
Robust Methods ◽  
Symmetric Methods ◽  
Tuning Parameters ◽  
Regression Parameters ◽  
Error Terms ◽  
Better Than

In robust regression, it is usually assumed that the distribution of the error term is symmetric or the data are symmetrically contaminated by outliers. However, this assumption is usually not satisfied in practical problems, and thus if the traditional robust methods, such as Tukey’s biweight and Huber’s method, are used to estimate the regression parameters, the efficiency of the parameter estimation can be lost. In this paper, we construct an asymmetric Tukey’s biweight loss function with two tuning parameters and propose a data-driven method to find the most appropriate tuning parameters. Furthermore, we provide an adaptive algorithm to obtain robust and efficient parameter estimates. Our extensive simulation studies suggest that the proposed method performs better than the symmetric methods when error terms follow an asymmetric distribution or are asymmetrically contaminated. Finally, a cardiovascular risk factors dataset is analyzed to illustrate the proposed method.

The Impact of Crises

2013 ◽  
pp. 1206-1221
Author(s):  
Emre Ergin
Keyword(s):  
Stock Prices ◽  
Stock Exchange ◽  
Debt Crisis ◽  
Abnormal Returns ◽  
The Other ◽  
Political Crisis ◽  
Accounting Fraud ◽  
Istanbul Stock Exchange ◽  
Overreaction Hypothesis ◽  
The Impact

Stock markets are the barometers of an economy. They are very sensitive to the news and can measure economic pressures to forecast economy. They react momentarily to crises that might be triggered by such events as a currency crisis, a debt crisis, a political crisis, or an accounting fraud crisis. According to technical analysts, drastic decreases in stock prices recover from their crash value rapidly since these decreases are realized with low traded values. The overreaction hypothesis affirms that extreme price movements are subsequently adjusted by opposite direction. This chapter analyses these assertions by measuring the impacts of the crises on the Istanbul Stock Exchange (ISE) over the last decade. The duration of the crises and weekly negative abnormal percentage returns in the period of 01.01.2000-31.12.2011 are analyzed using a regression model. In this period, from a total of 621 weeks, 277 weeks have negative returns, 93 of which are identified as negative abnormal returns. The results are statistically significant, and suggest that the duration of the crises is related to the magnitude of negative returns. On the other hand, research shows that the duration of the crisis and traded value are positively correlated. This study offers empirical observations that would be useful for technical analysts and stock investors.

scholarly journals PENGARUH KINERJA KEUANGAN TERHADAP PERUBAHAN HARGA SAHAM BANK UMUM SYARIAH NASIONAL DI BURSA EFEK INDONESIA (Studi Kasus: PT Bank Panin Dubai Syariah, Tbk.)

2019 ◽  
Vol 11 (1) ◽  
pp. 23
Author(s):  
Benny Barnas
Keyword(s):  
Linear Regression ◽  
Financial Performance ◽  
Multiple Linear Regression ◽  
Stock Prices ◽  
Commercial Banks ◽  
Stock Exchange ◽  
Financial Data ◽  
Return On Assets ◽  
Regression Methods ◽  
Earnings Per Share

Abstract: The purpose of this research is to examine the effect of Financial Performance, namely Return on Assets (ROA) and Earnings Per Share (EPS) on the stock price’s changes of National Sharia Commercial Banks are listed on the Indonesia Stock Exchange (IDX). The research hypothesis was analyzed using multiple linear regression methods, while the financial data is taken from Bank Panin Dubai Syariah, Tbk. with the period of 2014-2017. The results indicate that Return on Assets (ROA) and Earnings per Share (EPS) both partially and simultaneously influence on stock prices. However, the result of adjusted R2 show that 38,30 percent of stock prices are influenced by the Return on Assets (ROA) and Earning per Share (EPS), while 87,90 percent is influenced by other variables outside this model. Keywords: Return on Asset (ROA), Earning per Share (EPS), and Price of Share.

scholarly journals The Effect of the Exchange Rate Risk on the Stock Prices of the Energy Companies

2013 ◽  
Vol 5 (2) ◽  
pp. 106-116
Author(s):  
Ayhan Kapusuzoglu
Keyword(s):  
Regression Analysis ◽  
Exchange Rate ◽  
Stock Prices ◽  
Stock Exchange ◽  
Energy Sector ◽  
Exchange Rate Risk ◽  
Market Return ◽  
Rate Risk ◽  
Istanbul Stock Exchange ◽  
Energy Companies

The purpose of this study is the examination of the effect of the unexpected exchange rate risk on the stock prices of the energy companies which are transacted in the ISE (Istanbul Stock Exchange) National 100 index, for the period of 03/01/2005 – 29/06/2012. In addition, the study has investigated the effect of the market return on the stocks of the related companies in the same period. In line with that purpose, a multi-regression analysis has been realized in order to examine whether there was any effect or not. At the end of this inquiry, it was concluded that the unexpected exchange rate risk had a very small effect on the companies which are active in the energy sector and the return on market, on the contrary, had a very big effect thereon.

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