Covariance Structure and Systematic Risk of Market Index Portfolio

Static Systematic Risk Profile of Nifty 100 Stocks: A Year on Year Analysis of Beta

GIS Business ◽

10.26643/gis.v12i5.3346 ◽

2017 ◽

Vol 12 (5) ◽

pp. 75-83

Author(s):

Neeraj Sangh

Keyword(s):

Stock Exchange ◽

Systematic Risk ◽

Regression Function ◽

Least Square ◽

Market Model ◽

Rate Of Return ◽

Market Theory ◽

Ols Regression ◽

Index Model ◽

Market Index

Beta Coefficient, as a measurement statistic of systematic risk of securities, was initially explained by Sharpe as a slope of simple linear regression function using rate of return on a market index as independent variable and a securitys rate of return as dependent variable. National Stock Exchange (NSE), the leading stock exchange of India, practice this ordinary least square (OLS) regression based single index market model for disseminating beta coefficients of prominent NIFTY 100 stocks. OLS regression based index model presumes that beta coefficients of securities should remain stable for accuracy of predicted returns. Brenner and Smidt (1977) emphasized the importance of having accurate beta forecast mainly because of (i) understanding risk-return relationships in capital market theory and (ii) extensive usage of beta in making investment decisions. The objective of this paper is to examine year on year stability of beta coefficients of NIFTY 100 index stocks.

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Analisis Pengaruh Beta Saham, Debt To Equity Rasio (DER) terhadap Return On Asset (ROA) Perusahaan di Bursa Efek Indonesia

Jurnal STEI Ekonomi ◽

10.36406/jemi.v28i02.251 ◽

2019 ◽

Vol 28 (02) ◽

pp. 198-212

Author(s):

Muhammad Ikhsan ◽

Eko Budi Santoso

Keyword(s):

Stock Returns ◽

Stock Exchange ◽

Systematic Risk ◽

Net Income ◽

Financial Leverage ◽

Return On Equity ◽

Market Index ◽

Sample Data ◽

Equity Ratio ◽

Excess Stock Returns

Perhitungan rasio keuangan penting bagi perusahaan.. Investor dapat melihat kinerja perusahaan apakah perusahaan berkinerja baik dibandingkan dari rata-rata industri. Rasio adalah ukuran perbandingan antara pos dalam laporan keuangan dengan pos lainnya. Misalnya rasio profitabilitas yaitu Return on Asset makin tinggi ROA makin baik karena Net income makin tinngi. Demikian juga Debt to Equity ratio yaitu berapa batasan berhutang yang ideal yaitu financial leverage berapa ukuran maksimal sehingga net income maksimal.Resiko sistematis atau Beta saham didapat dari slope hasil regresi antara ekses return saham dengan ekses pasar adalah ukuran resiko juga dalam berinvestasi saham . Resiko adalah hal yang menyimpang dari target yang kita inginkan atau sesuatu pencapaian yangberbeda dari hal atau sesuatu yang kita inginkan atau harapkan. Contoh Resiko berinvestasi adalah jika kita menderita kerugian atau kehilangan pokok yang kita tanankan. Resiko yang mempengaruhi saham di bursa yaitu bisa resikosistematik atau bisa juga resiko unsistematis atau resiko di dalam perusahaan misalnya manajemennya. Resiko sistematisjuga disebut resiko pasar yang menimpa semua saham seperti pengaruh dari luar yaitu inflasi, kurs mata uang atau kebijakan pemerintah.Penelitian ini akan membahas apakah ada pengaruh Debt to equity ratio dan beta saham/ resiko sistematis terhadap nilai ROA karena bagi perusahaan net income adalah penting juga bagi investor untuk membeli saham.Sampel datayang diambil penulis sebanyak 35 macam saham dengan cara mengambil secara acak saham-saham yang ada di Bursa efek Indonesia. Data sampel akan diolah dengan statistik menjadi informasi dalam menjawab permasalahan dengan Aplikasi SPSS edisi 19. Hasil penelitian ini yaitu secara bersama-sama variabel Debt to Equity ratio dengan Beta saham mempunyai pengaruh yang signifikan terhadap Return on Equity (ROA) perusahaan di Bursa Efek Indonesia Calculation of finance ratios is important for the company. Investors can view the performance of the company if the company performs well compared to the average industry. The ratio is a measure of the ratio between account in the financial statements with another accounts. For example profitability ratios Return on Assets( ROA) higher is better because Net income increasing. Likewise with Debt to Equity ratio, is how much restriction ideal loanlikethe ideal size of financial leverage to maximum net income. Beta is a systematic risk obtained from the slope of the regression results between excess stock returns with excess return of the capital market index. This is a measure of risk in stock investing. Risk is something that deviates from the target that we want or something less achievement from thing or something we want or expect. Examples of investment risk is if we suffer any loss of money that we invest. Risks of invest stocks is a systematic risk or a unsystematis risk for examplelike a management in the company. Systematic risk is also called market risk hapend to all shares like outside influence,for example inflation, foreign exchange rates or government policy. This research will address the influence Debt to equity ratio and beta stocks / systematic risk to the value of Return of Asset (ROA) because for the company's net income is important for investors to decide buy shares. Sample data is retrieved author as many as 35 kinds of stocks by taking random stocks that exist in the Indonesian Stock Exchange. The sample data will be processed with statistical information in the answer problems with SPSS applications editions 19. Results of this research is jointly variable Debt to Equity ratio with Beta stocks have a significant influence on Return on Equity (ROA) companies in Indonesia Stock Exchange

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OPTIMAL QUADRATIC UNBIASED ESTIMATION FOR MODELS WITH LINEAR TOEPLITZ COVARIANCE STRUCTURE

Statistics ◽

10.1080/02331880309260 ◽

2003 ◽

Vol 37 (1) ◽

pp. 1-15

Author(s):

JEAN-MICHEL MARIN ◽

THIERRY DHORNE

Keyword(s):

Covariance Structure ◽

Unbiased Estimation

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Power of Modified Brown-Forsythe and Mixed-Model Approaches in Split-Plot Designs

Methodology ◽

10.1027/1614-2241/a000124 ◽

2017 ◽

Vol 13 (1) ◽

pp. 9-22 ◽

Cited By ~ 1

Author(s):

Pablo Livacic-Rojas ◽

Guillermo Vallejo ◽

Paula Fernández ◽

Ellián Tuero-Herrero

Keyword(s):

Repeated Measures ◽

Statistical Power ◽

Mixed Model ◽

Covariance Structure ◽

Simulation Method ◽

Future Research ◽

Repeated Measures Design ◽

Fixed And Random Effects ◽

Split Plot ◽

High Level

Abstract. Low precision of the inferences of data analyzed with univariate or multivariate models of the Analysis of Variance (ANOVA) in repeated-measures design is associated to the absence of normality distribution of data, nonspherical covariance structures and free variation of the variance and covariance, the lack of knowledge of the error structure underlying the data, and the wrong choice of covariance structure from different selectors. In this study, levels of statistical power presented the Modified Brown Forsythe (MBF) and two procedures with the Mixed-Model Approaches (the Akaike’s Criterion, the Correctly Identified Model [CIM]) are compared. The data were analyzed using Monte Carlo simulation method with the statistical package SAS 9.2, a split-plot design, and considering six manipulated variables. The results show that the procedures exhibit high statistical power levels for within and interactional effects, and moderate and low levels for the between-groups effects under the different conditions analyzed. For the latter, only the Modified Brown Forsythe shows high level of power mainly for groups with 30 cases and Unstructured (UN) and Autoregressive Heterogeneity (ARH) matrices. For this reason, we recommend using this procedure since it exhibits higher levels of power for all effects and does not require a matrix type that underlies the structure of the data. Future research needs to be done in order to compare the power with corrected selectors using single-level and multilevel designs for fixed and random effects.

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Outlier Detection for Covariance Structure Analysis

PsycEXTRA Dataset ◽

10.1037/e602812011-003 ◽

1992 ◽

Author(s):

Robert Cudeck

Keyword(s):

Outlier Detection ◽

Structure Analysis ◽

Covariance Structure ◽

Covariance Structure Analysis

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Pengaruh Faktor Fundamental, Risiko Sistematis Dan Ekonomi Makro Terhadap Return Saham Syariah Yang Tergabung Di Jakarta Islamic Index (JII) Pada Periode 2010 – 2014

Kajian Bisnis STIE Widya Wiwaha ◽

10.32477/jkb.v24i1.217 ◽

2017 ◽

Vol 24 (1) ◽

pp. 54-70

Author(s):

Hasanah Setyowati ◽

Riyanti Ningsih

Keyword(s):

Exchange Rate ◽

Stock Exchange ◽

Systematic Risk ◽

Secondary Data ◽

Analysis Model ◽

Macroeconomic Factors ◽

Return On Equity ◽

Equity Ratio ◽

Regression Techniques ◽

The Exchange Rate

This study aimed to obtain empirical evidence on the influence of fundamental factors, systematic risk and macroeconomics on the returns Islamic stock of companies incorporated in the Jakarta Islamic Index in 2010-2014. The variables used were the fundamental factors that are proxied by Earning Per Share (EPS), Return on Equity (ROE), Debt to Equity Ratio (DER); Systematic risk is proxied by Beta Shares; macroeconomic factors is proxied by the inflation rate and the exchange rate. The samples of this study are the enterprises incorporated in Jakarta Islamic Index (JII) at the Indonesian Stock Exchange. The sampling method was using purposive sampling. There were 12 samples of Islamic stocks that meet the criteria to be used as samples. The analysis model used is multiple linear regression techniques and the type of data used is secondary data. The study found that all variables, which are Earning Per Share (EPS), Return on Equity (ROE), Debt to Equity Ratio (DER), Beta stock, inflation and the exchange rate do not significantly affect the return of sharia stock either simultaneously or partially.

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