scholarly journals Analisis Pengaruh Variabel-Variabel Makroekonomi terhadap Tingkat Pengembalian di Pasar Modal Periode 2000 -2011 dengan Membandingkan Hasil Estimasi OLS, GLS dan MLE

2014 ◽  
Vol 5 (1) ◽  
pp. 267
Author(s):  
Sari Minjari Damayanti
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Consumer Price Index ◽  
Ordinary Least Squares ◽  
Least Square ◽  
Rate Of Return ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Macroeconomic Variables ◽  
Macro Variables

The factors in macroeconomic gives enormous influence on the fluctuation rate of return on stocks that is reflected in the stock price movement in the stock market. Movements in excess of the normal state, such as those caused by the global economic crisis, from the macro variables will create specific shocks on the capital markets, which will affect the value of the return on stocks in the capital market. To determine the effect of the factors or macroeconomic variables on the return of the index shares on BEI, empirical tests are accurately performed on these variables. This study has two main objectives: first to test how much the influence of macroeconomic variables on the return of the shares in the Indonesian Stock Exchange (BEI). Second, empirical research testing of variables using three different estimation methods, namely, Ordinary Least Squares (OLS), Generalized Least Square (GLS) and Maximum Likelihood Estimation (MLE) to find out how much the estimation accuracy of the three methods. The empirical result shows that there is a significant relationship between composite stock returns BEI and three macroeconomic variables, the consumer price index (inflation rate), exchange rate and interest rate of SBI. These results indicate that the three macro variables that affect the rate of return on the stock market.

Macroeconomic Factors and Pakistani Equity Market”

2004 ◽  
Vol 43 (4II) ◽  
pp. 619-637 ◽  
Author(s):  
Muhammad Nishat ◽  
Rozina Shaheen
Keyword(s):  
Stock Market ◽  
Industrial Production ◽  
Stock Prices ◽  
Stock Price ◽  
Consumer Price Index ◽  
Reverse Causality ◽  
Macroeconomic Factors ◽  
Macroeconomic Variables ◽  
Equilibrium Relationships

This paper analyzes long-term equilibrium relationships between a group of macroeconomic variables and the Karachi Stock Exchange Index. The macroeconomic variables are represented by the industrial production index, the consumer price index, M1, and the value of an investment earning the money market rate. We employ a vector error correction model to explore such relationships during 1973:1 to 2004:4. We found that these five variables are cointegrated and two long-term equilibrium relationships exist among these variables. Our results indicated a "causal" relationship between the stock market and the economy. Analysis of our results indicates that industrial production is the largest positive determinant of Pakistani stock prices, while inflation is the largest negative determinant of stock prices in Pakistan. We found that while macroeconomic variables Granger-caused stock price movements, the reverse causality was observed in case of industrial production and stock prices. Furthermore, we found that statistically significant lag lengths between fluctuations in the stock market and changes in the real economy are relatively short.

A quantile regression approach to evaluate the relative impact of global and local factors on the MENA stock markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Slah Bahloul ◽  
Nawel Ben Amor
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Stock Returns ◽  
Stock Markets ◽  
Financial Integration ◽  
Ordinary Least Squares ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
The Impact

PurposeThis paper investigates the relative importance of local macroeconomic and global factors in the explanation of twelve MENA (Middle East and North Africa) stock market returns across the different quantiles in order to determine their degree of international financial integration.Design/methodology/approachThe authors use both ordinary least squares and quantile regressions from January 2007 to January 2018. Quantile regression permits to know how the effects of explanatory variables vary across the different states of the market.FindingsThe results of this paper indicate that the impact of local macroeconomic and global factors differs across the quantiles and markets. Generally, there are wide ranges in degree of international integration and most of MENA stock markets appear to be weakly integrated. This reveals that the portfolio diversification within the stock markets in this region is still beneficial.Originality/valueThis paper is original for two reasons. First, it emphasizes, over a fairly long period, the impact of a large number of macroeconomic and global variables on the MENA stock market returns. Second, it examines if the relative effects of these factors on MENA stock returns vary or not across the market states and MENA countries.

WAVELET ESTIMATORS FOR LONG MEMORY IN STOCK MARKETS

2009 ◽  
Vol 12 (03) ◽  
pp. 297-317 ◽  
Author(s):  
ANOUAR BEN MABROUK ◽  
HEDI KORTAS ◽  
SAMIR BEN AMMOU
Keyword(s):  
Maximum Likelihood ◽  
Least Squares ◽  
Stock Returns ◽  
Long Memory ◽  
Weighted Least Squares ◽  
Ordinary Least Squares ◽  
Estimation Accuracy ◽  
Approximate Maximum Likelihood ◽  
Approximate Maximum Likelihood Estimator ◽  
Wavelet Estimators

In this paper, fractional integrating dynamics in the return and the volatility series of stock market indices are investigated. The investigation is conducted using wavelet ordinary least squares, wavelet weighted least squares and the approximate Maximum Likelihood estimator. It is shown that the long memory property in stock returns is approximately associated with emerging markets rather than developed ones while strong evidence of long range dependence is found for all volatility series. The relevance of the wavelet-based estimators, especially, the approximate Maximum Likelihood and the weighted least squares techniques is proved in terms of stability and estimation accuracy.

scholarly journals ANALISIS PORTOFOLIO SEBAGAI DASAR PENGAMBILAN KEPUTUSAN INVESTASI SAHAM YANG TERDAFTAR DI BEI

IQTISHODUNA ◽  
2013 ◽  
Author(s):  
Sri Yati
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Analytical Method ◽  
Stock Exchange ◽  
Investment Decisions ◽  
Portfolio Analysis ◽  
Rate Of Return ◽  
Expected Returns ◽  
Risk Level ◽  
Expected Return

This study aims to analyze rate of return and risk as the tools to form the portfolio analysis on 15 the most actives stocks listed in Indonesian Stock Exchange. Descriptive analytical method is used to describe the correlation between three variables: stock returns, expected returns of stock market, and beta in order to measure the risk of stocks to help the investors in making the investment decisions. The research materials are 15 the most actives stocks listed in Indonesian Stock Exchange during 2008-2009. The results show that PT. Astra International Tbk. has the highest average expected return of individual stock (Ri) of 308,3355685, while PT. Perusahaan Gas Negara Tbk. has the lowest of -477,0827847. The average expected return of stock market (Rm) is 0,00247163. PT. Astra International Tbk. has the highest systematic risk level of 20229,14205, while the lowest of -147,5793279 is PT. Kalbe Farma Tbk. Furthermore, the results also indicate that there are 9 stocks can be combined to form optimal portfolio because they have positive expected returns.

scholarly journals Analysis of Capital Flight in Developing Countries: A Study on Turkey between 1980 and 2010

2013 ◽  
Author(s):  
Ali Özer ◽  
Aslı Cansın Doker ◽  
Adem Türkmen
Keyword(s):  
Foreign Direct Investment ◽  
Direct Investment ◽  
Consumer Price Index ◽  
External Debt ◽  
Estimation Method ◽  
Ordinary Least Squares ◽  
Capital Flight ◽  
Causality Test ◽  
Macroeconomic Variables ◽  
Long Run

The aim of this study is to determine whether there is a relationship between Capital flight and some macroeconomic variables by using anual data between 1980 and 2010 in Turkey. Capital flight measured by World Bank (1985) method, was used as dependent variable and external debt, foreign direct investment, uncertainty, real GDP growth, exchange rates, trade balance and consumer price index were used as independent variables. Ordinary Least squares estimation method, Johansen-Jeselius cointegration test, Granger causality test and variance decomposition results produced by VEC model were used in the study. After those econometrics and economics analysis, this paper put forward that there is a long run relationship between some macroeconomic variables and capital flight.The results show external debt, foreign direct investment inflows, and foreign reserves to be the major effector of capital flight.

scholarly journals Determination of Support Vector Boundaries in Generalized Maximum Entropy for Multilevel Models

2016 ◽  
Vol 5 (6) ◽  
pp. 10
Author(s):  
Serpil Kilic Depren ◽  
Özer Depren
Keyword(s):  
Maximum Entropy ◽  
Iterative Procedure ◽  
Real Life ◽  
Least Square ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Support Vector ◽  
Determine Parameter ◽  
Generalized Maximum Entropy ◽  
Support Vectors

Generalized Maximum Entropy (GME) approach is one of the alternative estimation methods for Regression Analysis. GME approach is superior to other classical approaches in terms of parameter estimation accuracy when some or none of the assumptions of classical approaches are violated. However, determining bounds of parameter support vectors is one of the open parts of this approach when researchers have no prior information about the parameters. If support vectors cannot be determined correctly, parameters estimations will not be obtained correctly. There are some theoretical studies about GME for different datasets in the literature, but there are fewer studies about how to determine parameter support vectors. To obtain robust parameter estimations in GME, we introduced a new iterative procedure for determining parameter support vectors bounds for multilevel dataset. In this study, the new iterative procedure was applied for multi-level random intercept model and the new procedure was tested both simulation study and the real life data. The Classical and the new procedures of GME estimations were compared to Generalized Least Square Estimations in terms of Root Mean Square Error (RMSE) statistics. As a result, the estimations of the new approach provided lower RMSE values than classical methods.

scholarly journals Reaction of stock market returns to COVID-19 pandemic and lockdown policy: evidence from Nigerian firms stock returns

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Isiaka Akande Raifu ◽  
Terver Theophilus Kumeka ◽  
Alarudeen Aminu
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
Estimation Methods ◽  
Panel Var ◽  
Impulse Response Functions ◽  
Market Returns ◽  
Stock Market Returns ◽  
Long Run ◽  
Policy Shocks

AbstractGiven the effects COVID-19 pandemic on the financial sectors across the world, this study examined the reaction of stock returns of 201 firms listed in the Nigerian Stock Exchange to the COVID-19 pandemic and lockdown policy. We deployed both Pooled OLS and Panel VAR as estimation methods. Generally, the results from POLS show the stock market returns of the Nigerian firms reacted negatively more to the global COVID-19 confirmed cases and deaths than the domestic COVID-19 confirmed cases and deaths and lockdown policy. The results of the impulse response functions revealed that the effects of COVID-19 confirmed cases and deaths and lockdown policy shocks on stock returns oscillate between negative and positive before the stock market returns converge to the equilibrium in the long run. The FEVD results showed that growth in the COVID-19 confirmed cases, deaths and lockdown policy shocks explained little variations in stock market returns. Given our finding, we advocate for the relaxation of policy of lockdown and the combine use of monetary and fiscal policies to mitigate the negative effect of COVID-19 pandemic on stock market returns in Nigeria.

scholarly journals The Effects of COVID-19 Pandemic on Stock Market Performance in Africa

2021 ◽  
Author(s):  
Isiaka Akande Raifu
Keyword(s):  
Stock Market ◽  
Least Squares ◽  
Ordinary Least Squares ◽  
Estimation Methods ◽  
Negative Effects ◽  
Market Returns ◽  
African Countries ◽  
Daily Growth ◽  
Stock Market Returns ◽  
Stock Market Performance

Abstract This study is conducted to investigate the response of stock market returns to daily growth in COVID-19 confirmed cases and deaths in 14 African countries using both time series and panel approaches. The study employs three estimation methods, Ordinary Least Squares/Robust Ordinary Least Squares (OLS/ORLS), Pooled Ordinary Least Squares (POLS) and Panel Vector Autoregressive (PVAR). While the OLS and POLS are used to examine a conditional mean effect of COVID-19 confirmed cases and deaths on stock market returns PVAR is used to estimate and trace the response of stock market return to shocks from daily growth in COVID-19 confirmed cases and deaths. OLS results show that stock market returns react negatively and significantly to daily growth in COVID-19 confirmed cases in countries like Botswana, Kenya, Tanzania, Tunisia and Uganda while the negative effects of daily growth in COVID-19 confirmed deaths on stock market returns are negligible. Evidence from POLS reveals that the impacts of an increase in COVID-19 confirmed cases and deaths are insignificant. This is corroborated by the results of FEVD. IRF results show that stock market returns react positively to COVID-19 confirmed cases and deaths shocks before declining and returning towards normal returns in the long-run. Our findings underscore the importance of analysing individual country’s socioeconomic reaction to COVID-19 pandemic instead of pooling countries together.JEL Classification: I12, G1

scholarly journals Macroeconomic impact on stock returns in the Croatian hospitality industry

2019 ◽  
Vol 7 (1) ◽  
pp. 53-68
Author(s):  
Siniša Bogdan
Keyword(s):  
Stock Returns ◽  
Stock Prices ◽  
Stock Price ◽  
Hospitality Industry ◽  
Price Index ◽  
Explanatory Power ◽  
Consumer Price Index ◽  
Stock Index ◽  
Macro Variables ◽  
The Impact

Tourism is one of the most important sectors in the Republic of Croatia. It plays a significant role in its economic development. This research investigates whether the macro-variables have an impact on the stock returns in the hospitality industry. The focus of the work consists in causality relationship between four macro variables (consumer price index, industrial production, exchange rate and number of tourist arrivals) and a stock index composed of Croatian hospitality companies. After applying Granger-causality tests based on the VAR methodology, results suggest that only consumer price index Granger-cause stock returns in the hospitality industry in the observed period from July 2008 to July 2018. Further analysis through impulse response function indicates that the impulse responses of inflation meet expectations in terms of the direction of impact. In the second month, stock prices react negatively to shock, implying that higher inflation causes negative stock price returns. After applying the variance decomposition method, a very low explanatory power of consumer price index on stock returns in the hospitality industry was revealed. This paper contributes to the existing literature on the topic of the impact of macro-economic variables on hospitality stock returns by extending the scope to Croatia and by testing a different set of variables compared to those from previous studies.

scholarly journals Household Income Diversification and Food Security: Evidence from Rural and Semi-Urban Areas in Ethiopia

2019 ◽  
Vol 11 (12) ◽  
pp. 3232 ◽  
Author(s):  
Bekele Gebisa Etea ◽  
Deyi Zhou ◽  
Kidane Assefa Abebe ◽  
Dessalegn Anshiso Sedebo
Keyword(s):  
Food Security ◽  
Food Insecurity ◽  
Household Income ◽  
Urban Areas ◽  
Binary Logistic Regression ◽  
Ordinary Least Squares ◽  
Least Square ◽  
Estimation Methods ◽  
Income Diversification ◽  
Access To Food

Reducing food insecurity remains a major public policy challenge in developing countries. Food insecurity becomes severe in areas where households highly depend on undiversified livelihoods. However, studies linking household income diversification to food security are limited. This study, therefore, examined the effect of income diversification on food security in the Ambo district, Ethiopia. A survey of rural (n = 175) and semi-urban (n = 175) households was conducted. The Simpson’s index of diversity (SID) was used to measure the level of household income diversity. Food security (access) was measured using the daily calorie consumption (nutrition-based) and the household food insecurity access scale (HFIAS) (experience-based) methods. Consequently, we used binary logistic regression and ordinary least squares (OLS) estimation methods to determine the effect of household income diversity on food security. The instrumental variable (IV) method was also employed to overcome an endogeneity bias. The results revealed that the level of household income diversification was low, and the majority of households were food insecure. The binary logistic and the second-stage least square (2SLS) regression results suggested that income diversification contributes significantly and positively to food security in the study areas. Therefore, we conclude that income diversification reduces food insecurity by enhancing households’ access to food.

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