NONLINEARITIES AND GARCH INADEQUACY FOR MODELING STOCK MARKET RETURNS: EMPIRICAL EVIDENCE FROM LATIN AMERICA

2010 ◽  
Vol 15 (5) ◽  
pp. 713-724 ◽  
Author(s):  
Claudio A. Bonilla ◽  
Rafael Romero-Meza ◽  
Carlos Maquieira

In this paper, we analyze the adequacy of using GARCH as the data-generating process to model conditional volatility of stock market index rates-of-return series. Using the Hinich portmanteau bicorrelation test, we find that a GARCH formulation or any of its variants fail to provide an adequate characterization for the underlying process of the main Latin American stock market indices. Policymakers need to be careful when using autoregressive models for policy analysis and forecast because the inadequacy of GARCH models has strong implications for the pricing of stock index options, portfolio selection, and risk management. In particular, measures of spillover effects and output volatility may not be correct when GARCH-type models are used to evaluate economic policy.

Author(s):  
Robert D. Gay, Jr.

The relationship between share prices and macroeconomic variables is well documented for the United States and other major economies. However, what is the relationship between share prices and economic activity in emerging economies? The goal of this study is to investigate the time-series relationship between stock market index prices and the macroeconomic variables of exchange rate and oil price for Brazil, Russia, India, and China (BRIC) using the Box-Jenkins ARIMA model. Although no significant relationship was found between respective exchange rate and oil price on the stock market index prices of either BRIC country, this may be due to the influence other domestic and international macroeconomic factors on stock market returns, warranting further research. Also, there was no significant relationship found between present and past stock market returns, suggesting the markets of Brazil, Russia, India, and China exhibit the weak-form of market efficiency.


2020 ◽  
Vol 13 (11) ◽  
pp. 16
Author(s):  
Nader Alber ◽  
Amr Saleh

This paper attempts to investigate the effects of 2020 Covid-19 world-wide spread on stock markets of GCC countries. Coronavirus spread has been measured by cumulative cases, new cases, cumulative deaths and new deaths. Coronavirus spread has been measured by numbers per million of population, while stock market return is measured by Δ in stock market index. Papers conducted in this topic tend to analyze Coronavirus spread in the highly infected countries and focus on the developed stock markets. Countries with low level of infection that have emerging financial markets seem to be less attractive to scholars concerning with Coronavirus spread on stock markets. This is why we try to investigate the GCC stock markets reaction to Covid-19 spread.   Findings show that there are significant differences among stock market indices during the research period. Besides, stock market returns seem to be sensitive to Coronavirus new deaths. Moreover, this has been confirmed for March without any evidence about these effects during April and May 2020.


Author(s):  
Katrakilidis Constantinos ◽  
Lake Andreas Ektor ◽  
Mardas Dimitrios

<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt; mso-pagination: none;"><span style="font-family: Times New Roman;"><span style="color: black; font-size: 10pt; mso-ansi-language: EN-US; mso-themecolor: text1;">We </span><span style="color: black; font-size: 10pt; mso-ansi-language: EN-GB; mso-themecolor: text1;" lang="EN-GB">investigate the dynamic linkages between oil prices and the stock market behaviour in a small and oil dependent economy. Particularly, we analyse empirically the relationships among stock market returns, the volatility of the stock market index, the oil price and the volatility of oil price in Greece. We employ VAR modelling in conjunction with Granger-causality tests. Contrary to the majority of the internationally reported evidence, our findings show the existence of significant positive causal effects from oil price changes on the stock market.</span></span><strong style="mso-bidi-font-weight: normal;"><span style="color: black; font-size: 10pt; mso-ansi-language: EN-US; mso-themecolor: text1;"></span></strong></p>


2016 ◽  
Vol 15 (3) ◽  
pp. 119-126 ◽  
Author(s):  
Robert D. Gay

The relationship between share prices and macroeconomic variables is well documented for the United States and other major economies.  However, what is the relationship between share prices and economic activity in emerging economies?  The goal of this study is to investigate the time-series relationship between stock market index prices and the macroeconomic variables of exchange rate and oil price for Brazil, Russia, India, and China (BRIC) using the Box-Jenkins ARIMA model.  Although no significant relationship was found between respective exchange rate and oil price on the stock market index prices of either BRIC country, this may be due to the influence other domestic and international macroeconomic factors on stock market returns, warranting further research.  Also, there was no significant relationship found between present and past stock market returns, suggesting the markets of Brazil, Russia, India, and China exhibit the weak-form of market efficiency.


2016 ◽  
Vol 9 (2) ◽  
pp. 123-146 ◽  
Author(s):  
Kim Hiang Liow

Purpose This research aims to investigate whether and to what extent the co-movements of cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles are linked across G7 from February 1990 to June 2014. Design/methodology/approach The empirical approaches include correlation analysis on Hodrick–Prescott (HP) cycles, HP cycle return spillovers effects using Diebold and Yilmaz’s (2012) spillover index methodology, as well as Croux et al.’s (2001) dynamic correlation and cohesion methodology. Findings There are fairly strong cycle-return spillover effects between the cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles. The interactions among the cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles in G7 are less positively pronounced or exhibit counter-cyclical behavior at the traditional business cycle (medium-term) frequency band when “pure” stock market cycles are considered. Research limitations/implications The research is subject to the usual limitations concerning empirical research. Practical implications This study finds that real estate is an important factor in influencing the degree and behavior of the relationship between cross-country business cycles and cross-country stock market cycles in G7. It provides important empirical insights for portfolio investors to understand and forecast the differential benefits and pitfalls of portfolio diversification in the long-, medium- and short-cycle horizons, as well as for research studying the linkages between the real economy and financial sectors. Originality/value In adding to the existing body of knowledge concerning economic globalization and financial market interdependence, this study evaluates the linkages between business cycles, stock market cycles and public real estate market cycles cross G7 and adds to the academic real estate literature. Because public real estate market is a subset of stock market, our approach is to use an original stock market index, as well as a “pure” stock market index (with the influence of real estate market removed) to offer additional empirical insights from two key complementary perspectives.


2021 ◽  
Vol 22 (1) ◽  
pp. 41-59
Author(s):  
Dinesh Gajurel

This paper investigates the asymmetric volatility behavior of the Nepalese stock market including spillover effects from the US and Indian equity markets. I modeled asymmetric volatility within a generalized autoregressive conditional heteroskdasticy framework using comprehensive data for the Nepal stock market index. The results reveal a very different asymmetry compared to the results in other international equity markets: positive shocks increase volatility by more than negative shocks. The results further suggest that uninformed investors play a significant role in the Nepalese stock market. The spillover effect from the Indian stock market to the Nepalese stock market is negative. Overall, I conclude that a “fear of missing out” (FOMO) of noise traders as well as the deployment of pump and dump schemes are inherent features of the Nepalese stock market. The findings are very useful to policy makers and investors alike.


2015 ◽  
Vol 6 (1) ◽  
pp. 93-106
Author(s):  
Tamara Mariničevaitė ◽  
Jovita Ražauskaitė

We examine the capability of CBOE S&P500 Volatility index (VIX) to determine returns of emerging stock market indices as compared to local stock markets volatility indicators. Our study considers CBOE S&P500 VIX, local BRIC stock market volatility indices and BRIC stock market MSCI indices daily returns in the period from January 1, 2009 to September 30, 2014. Research is conducted in two steps. First, we perform Spearman correlation analysis between daily changes in CBOE S&P500 VIX, local BRIC stock market VIX and MSCI BRIC stock market indices returns. Second, we perform multiple regression analysis with ARCH effects to estimate the relevance of CBOE S&P500 VIX and local VIX in determining BRIC stock market returns. Research reports weak correlation between CBOE S&P500 VIX and local VIX (except for Brazil). Furthermore, results challenge the assumption of CBOE S&P500 VIX being an indicator of global risk aversion. We conclude that commonly documented trends of rising globalization and stock markets co-integration are not yet present in emerging economies, therefore the usage of CBOE S&P500 VIX alone in determining BRIC stock market returns should be considered cautiously, and local volatility indices should be accounted for in analysis. Furthermore, the data confirms the presence of safe haven properties in Chinese stock market index.


Author(s):  
M. Rodríguez-Achach ◽  
A. Suárez-Solís ◽  
A. R. Hernández Montoya ◽  
J. E. Escalante-Martínez ◽  
C. Calderón-Ramón

The objective of this work is to analyze the Indice de Precios y Cotizaciones (IPC), which is the Mexican stock market index, by using several statistical tools in order to study the tendencies that can shed light on the evolution of the IPC towards a more efficient market. The methodology used is to apply the statistical tools to the Mexican index and compare the results with a mature and well-known market index such as the Dow Jones Industrial Average (DJIA). We employ an autocorrelation analysis, and the volatility of the indexes, applied to the daily returns of the closing price on a moving time window during the studied period (1980–2018). Additionally, we perform an order three permutation entropy analysis, which can quantify the disorder present in the time series. Our results show that there is evidence that the IPC has become more mature since its creation and that it can be considered an efficient market since around year 2000. The behavior of the several techniques used shows a similar behavior to the DJIA which is not observed before that year. There are some limitations mainly because there is no high frequency data that would permit a more detailed analysis, specifically in the periods before and after a crisis is located. Our conclusion is that since around the year 2000, the Mexican stock index displays the typical behavior of other mature markets and can be considered as one.


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