scholarly journals Existe Alguma Relação entre Retornos Contábeis e Retornos do Mercado de Ações no Brasil?

2007 ◽  
Vol 5 (2) ◽  
pp. 233
Author(s):  
Newton Carneiro Affonso da Costa Jr. ◽  
Roberto Meurer ◽  
César Medeiros Cupertino
Keyword(s):  
Stock Market ◽  
Granger Causality ◽  
Stock Exchange ◽  
Granger Causality Test ◽  
Market Returns ◽  
Causality Test ◽  
Stock Market Returns ◽  
Weak Evidence ◽  
Causality Tests ◽  
The Relationship

This paper examines the relationship between accounting and stock market returns of Brazilian companies on a quarterly basis. The sample consisted of 97 companies with stocks traded in the Sao Paulo Stock Exchange from January of 1995 to March of 2007. A Granger causality test was applied to the two return series for each of the sampled companies. The results of the causality tests suggested that there is weak evidence that accounting returns lead stock market returns rather than the reverse.

scholarly journals Nexus between Stock Market Returns and Economic Variables: Evidence

2017 ◽  
Vol 4 (01) ◽  
Author(s):  
Vanitha Chawla ◽  
Shweta .
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Granger Causality ◽  
Granger Causality Test ◽  
Market Returns ◽  
Causality Test ◽  
Stock Market Returns ◽  
Macroeconomic Variables ◽  
Indian Stock Market ◽  
The Impact

The paper examines the impact of selected macroeconomic variables on the Indian stock market. The macroeconomic variables used in the study are interest rate, exchange rate, index of industrial production (IIP) and gold price. BSE Sensex is used as proxy for Indian stock market. We have used the monthly data for all the variables from January 2001 to December 2016. Regression analysis and Granger Causality test is used to establish the relationship between the stock market and macroeconomic variables. The results show significant impact of only exchange rate on stock returns. All the other variables have shown insignificant impact on the stock market returns. The results of Granger causality test show unidirectional relationship between exchange rate and stock prices and bi-directional relation between IIP and SENSEX.

The Relationship Between Stock Market Indices of the Biggest Six Economies of the European Union and BIST 100

2020 ◽  
pp. 257-275
Author(s):  
Serdar Ögel ◽  
Fatih Temizel
Keyword(s):  
European Union ◽  
Stock Market ◽  
Granger Causality ◽  
Granger Causality Test ◽  
Var Model ◽  
The European Union ◽  
Causality Test ◽  
Integration Test ◽  
Causality Relationship ◽  
The Relationship

This chapter examines the relationship between stock market indices of the biggest six economies of the European Union and BIST 100. In this context, this study used the daily time series regarding indices of DAX for Germany, CAC 40 for France, FTSE MIB for Italy, IBEX 35 for Spain, AEX for Holland, FTSE 100 for United Kingdom, and BIST 100 for Turkey from 2014 to 2018. To test whether there is a co-integration relationship among indices, Johansen co-integration test was used. Since a co-integration relationship was not found between series, causality relationship between the European stock market indices and Turkey was tested with Granger causality test by establishing standard VAR model. As a result, a unidirectional Granger causality relationship was found from DAX, FTSE 100, CAC 40, IBEX 35, and AEX to BIST 100 according to lag length 1 and 2. However, a unidirectional Granger causality relationship was only found from FTSE MIB to BIST 100 for lag length 1. For lag length 1 and 2, no causality relationship was found from BIST 100 to the selected European stock market indices.

PENGARUH VOLATILITAS NILAI TUKAR, IDR-USD TERHADAP RETURN SAHAM DI BURSA EFEK INDONESIA: PENERAPAN MODEL GARCH

2019 ◽  
Vol 14 (2) ◽  
pp. 95
Author(s):  
Rahmadiva Dianitha Danial ◽  
Brady Rikumahu
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Granger Causality ◽  
Stock Price ◽  
Foreign Exchange Market ◽  
Stock Exchange ◽  
Composite Index ◽  
Granger Causality Test ◽  
Causality Test ◽  
Stock Market Returns

Penelitian ini bertujuan untuk menguji pengaruh  volatilitas return nilai Kurs IDR-USD terhadap volatilitas return pasar saham di Bursa Efek Indonesia. Dari pengambilan data sekunder dari 3 Januari 2012 hingga 29 September 2017 diperoleh data time series sebanyak 1404 hari. Data  dianalisis dengan model  GARCH dan Uji Granger Causality. Berdasarkan hasil permodelan GARCH(1,1), volatilitas kurs mempengaruhi volatilitas IHSG. Uji Granger Causality menunjukkan bahwa volatilitas kurs  dan IHSG memiliki hubungan yang kausal dua arah. Penelitian ini menunjukkan bahwa informasi kurs dapat memprediksikan kondisi harga indeks saham di pasar modal di periode hari berikutnya, begitupun sebaliknya. Prediksi tepat yang dilakukan oleh investor akan mengurangi risiko dan meningkatkan imbal hasil dalam berinvestasi jika pasar uang maupun pasar modal yang sedang bergejolak.  Kata Kunci: GARCH, Volatilitas, IHSG, Nilai Tukar ABSTRACT This study aims to examine the effect of the volatility of the return on the IDR-USD exchange rate toward  the volatility of stock market returns in the Indonesia Stock Exchange. From the data collection from 3 January 2012 until 29 September 2017 we obtained 1404 time series. Analyzing data, this study used  GARCH modeling and Granger Causality Test. The selected GARCH (1,1) modeling result shows that the volatility of exchange rate influences the volatility of Indonesian Composite Index.  Granger Causality test shows that the volatility of exchange rate and volatility of Indonesian Composite Index have two-way granger cause. This study indicates that exchange rate information can predict the condition of stock price index in capital market and movement of Indonesian Composite Index (ICI) can predict exchange rate movement in foreign exchange market. Appropriate predictions by investors will reduce the risk and increase the yield in investing if the money market and capital markets are fluctuating high. Keywords: GARCH, Volatility, ICI, Exchange Rate

scholarly journals Stock Market Reactions to COVID-19 Pandemic Outbreak: Quantitative Evidence from ARDL Bounds Tests and Granger Causality Analysis

2020 ◽  
Vol 17 (18) ◽  
pp. 6729 ◽  
Author(s):  
Ștefan Cristian Gherghina ◽  
Daniel Ștefan Armeanu ◽  
Camelia Cătălina Joldeș
Keyword(s):  
Stock Market ◽  
Granger Causality ◽  
Stock Exchange ◽  
Causality Analysis ◽  
Market Returns ◽  
Stock Market Returns ◽  
Quantitative Evidence ◽  
Granger Causality Analysis ◽  
Gold Silver ◽  
The Impact

This paper examines the linkages in financial markets during coronavirus disease 2019 (COVID-19) pandemic outbreak. For this purpose, daily stock market returns were used over the period of December 31, 2019–April 20, 2020 for the following economies: USA, Spain, Italy, France, Germany, UK, China, and Romania. The study applied the autoregressive distributed lag (ARDL) model to explore whether the Romanian stock market is impacted by the crisis generated by novel coronavirus. Granger causality was employed to investigate the causalities among COVID-19 and stock market returns, as well as between pandemic measures and several commodities. The outcomes of the ARDL approach failed to find evidence towards the impact of Chinese COVID-19 records on the Romanian financial market, neither in the short-term, nor in the long-term. On the other hand, our quantitative approach reveals a negative effect of the new deaths’ cases from Italy on the 10-year Romanian bond yield both in the short-run and long-run. The econometric research provide evidence that Romanian 10-year government bond is more sensitive to the news related to COVID-19 than the index of the Bucharest Stock Exchange. Granger causality analysis reveals causal associations between selected stock market returns and Philadelphia Gold/Silver Index.

scholarly journals COUNTRY RATING AND STOCK MARKET VOLATILITY: AN EMPIRICAL ESTIMATION FOR KARACHI STOCK EXCHANGE

2014 ◽  
Vol 02 (01) ◽  
pp. 07-14
Author(s):  
Muhammad Bilal Saeed ◽  
◽  
Arshad Hassan ◽  
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Empirical Estimation ◽  
Market Returns ◽  
Stock Market Returns ◽  
Daily Data ◽  
Asymmetric Garch ◽  
The Relationship

This study is aimed to explore the relationship between country rating and volatility of Karachi Stock Exchange for the period 1999 to 2012. This study employs daily data of country ratings and stock market returns to investigate influence of rating on volatility of market. Univariate Asymmetric GARCH model is used to explore the relationship and results reveal that country rating has a significant role in explaining volatility in Karachi Stock Exchange.

scholarly journals RELATIONSHIP BETWEEN STOCK MARKET RETURNS AND EXCHANGERATES IN EMERGING STOCK MARKETS

IKONOMIKA ◽  
2017 ◽  
Vol 1 (2) ◽  
pp. 131
Author(s):  
M.N. Arshad ◽  
M.H. Yahya
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Exchange Rates ◽  
Stock Markets ◽  
Market Returns ◽  
Stock Market Returns ◽  
Emerging Stock Markets ◽  
Long Run ◽  
Causality Tests ◽  
The Relationship

Abstract-This paper aims to study the relationship between stock market returns and exchange rates in emerging stock markets including Malaysia, Singapore, Thailand, Indonesia and Philippines. The data is taken from January 2003 to December 2012 using weekly closing indices and separated in two periods; before (2003-2007) and second, after (2008-2012) the financial crisis of 2008. Johansen-Juselius (JJ). Granger causality tests show that unidirectional causality exists between the stock market returns and exchange rates for Thailand before the financial crisis, whilst, for Indonesia and Singapore, the unidirectional causality between the two variables is detected in the period after the financial crisis. Error Correction Model (ECM) indicates the existence of long run causality between the two variables for Philippines. This study also finds that most of the emerging stock markets are informationally inefficient.

The relationship between financial development and economic growth in Eswatini (formerly Swaziland)

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Siphe-okuhle Fakudze ◽  
Asrat Tsegaye ◽  
Kin Sibanda
Keyword(s):  
Economic Growth ◽  
Granger Causality ◽  
Financial Development ◽  
Granger Causality Test ◽  
Causality Test ◽  
Content Type ◽  
Distributed Lag ◽  
Long Run ◽  
Short Run ◽  
The Relationship

PurposeThe paper examined the relationship between financial development and economic growth for the period 1996 to 2018 in Eswatini.Design/methodology/approachThe Autoregressive Distributed Lag bounds test (ARDL) was employed to determine the long-run and short-run dynamics of the link between the variables of interest. The Granger causality test was also performed to establish the direction of causality between financial development and economic growth.FindingsThe ARDL results revealed that there is a long-run relationship between financial development and economic growth. The Granger causality test revealed bidirectional causality between money supply and economic growth, and unidirectional causality running from economic growth to financial development. The results highlight that economic growth exerts a positive and significant influence on financial development, validating the demand following hypothesis in Eswatini.Practical implicationsPolicymakers should formulate policies that aims to engineer more economic growth. The policies should strike a balance between deploying funds necessary to stimulate investment and enhancing productivity in order to enliven economic growth in Eswatini.Originality/valueThe study investigates the finance-growth linkage using time series analysis. It determines the long-run and short-run dynamics of this relationship and examines the Granger causality outcomes.

scholarly journals Forecasting stock returns on the Amman Stock Exchange: Do neural networks outperform linear regressions?

2021 ◽  
Vol 18 (4) ◽  
pp. 280-296
Author(s):  
Abdel Razzaq Al Rababa’a ◽  
Zaid Saidat ◽  
Raed Hendawi
Keyword(s):  
Stock Market ◽  
Regression Models ◽  
Linear Models ◽  
Stock Exchange ◽  
Market Returns ◽  
Stock Market Returns ◽  
Statistical Measures ◽  
Amman Stock Exchange ◽  
Non Linear ◽  
Ann Models

Different models have been used in the finance literature to predict the stock market returns. However, it remains an open question whether non-linear models can outperform linear models while providing accurate predictions for future returns. This study examines the prediction of the non-linear artificial neural network (ANN) models against the baseline linear regression models. This study aims specifically to compare the prediction performance of regression models with different specifications and static and dynamic ANN models. Thus, the analysis was conducted on a growing market, namely the Amman Stock Exchange. The results show that the trading volume and interest rates on loans tend to explain the monthly returns the most, compared to other predictors in the regressions. Moreover, incorporating more variables is not found to help in explaining the fluctuations in the stock market returns. More importantly, using the root mean square error (RMSE), as well as the mean absolute error statistical measures, the static ANN becomes the most preferred model for forecasting. The associated forecasting errors from these metrics become equal to 0.0021 and 0.0005, respectively. Lastly, the analysis conducted with the dynamic ANN model produced the highest RMSE value of 0.0067 since November 2018 following the amendment to the Jordanian income tax law. The same observation is also seen since the emerging of the COVID-19 outbreak (RMSE = 0.0042).

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