scholarly journals Analysis of stock market returns of American and European stock market from the view of an American and a European investor

2005 ◽  
Vol 53 (6) ◽  
pp. 189-200
Author(s):  
Oldřich Šoba
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Stock Markets ◽  
Research Paper ◽  
Variation Coefficient ◽  
Investment Horizon ◽  
Market Returns ◽  
Stock Market Returns ◽  
Stock Indexes ◽  
Simple Average

The paper is focused on the analysis of stock market returns of American and European stock market for different investment horizon from the view of an American and European investor. The paper also partly resumes, in the part of analysis of USD/EUR exchange rate influence on market returns of mentioned stock market, research paper REJNUŠ, O., ŠOBA, O.: Changes in the USD/EUR exchange rate and their impact on the return of stock indexes from the viewpoint of a European and of an American investor. ACTA UNIVERSITATIS AGRICULTURAE ET SILVICULTURAE MENDELIANAE BRU- NENSIS, Vol. LII, No. 6, 2004, pg. 145–159, ISSN 1211-8516.The development of both American and European stock market is put on the development of two, structure-similar Standard & Poor’s exchange indexes, particularly S&P 500 and S&P Europe 350. According to the USD/EUR exchange rate, there were used the values published by FED, with the oldest data there were accepted the count ECU to EUR. The data were taken both from the weekly closing values of mentioned stock indexes and weekly closing values of USD/EUR exchange rate.The analysis was done with using the methods of quantification of „running market returns“ (recount to the average annual values) of indexes from the view of both investors within the set investment horizon. The elemental statistical level characteristic – simple average, median and statistical characteristic of variability – standard deviation and variation coefficient were quantified from this time series of annual running market returns. The analysis, which was purposely oriented to six basic different long investment horizon (1 year, 2 years, 3 years, 5 years, 7 years, 10 years), has approved that in focused term of 1980–2004 the market returns of picked stock market from the view of both investors (American and European) was generally higher in longer investment horizon than in the shorter investment horizon. The values of variation coefficient in particular investment horizon indicated the decreasing riskiness of investments in analyzed markets with elongating length of investment horizon, from view of both investors on both stock markets. The influence of the exchange rates changes on the values of quantified characteristic of indexes market returns (stock markets) was relatively insignificant, so the conclusions of the mentioned research paper, which resumes partly this paper, where in practice verified.

scholarly journals The The Impact of the Exchange Rate Volatility on Stock Markets Dynamics in Tunisia and Turkey: An Artificial Neural Network Analysis

2021 ◽  
pp. 1-21
Author(s):  
Nesrine Mechri ◽  
Christian De Peretti ◽  
Salah BEN HAMAD
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Exchange Rate ◽  
Stock Market ◽  
Multiple Regression ◽  
Stock Markets ◽  
Exchange Rate Volatility ◽  
Market Returns ◽  
Stock Market Returns ◽  
The Impact

The present research provides an overview of links between exchange rate volatility and the dynamics of stock market returns in order to identify the influence of several macroeconomic variables on the volatility of stock markets, useful for political decision makers as well as investors to better control the portfolio risk level. More precisely, this research aims to identify the impact of exchange rate volatility on the fluctuations of stock market returns, considering two countries that belong to the Middle East and North Africa (MENA) zone: Tunisia and Turkey. Previous works in the literature used very specified and short periods of study, many important variables were neglected, and most of the earlier research was concentrated on the developed countries. In this research, we integrate several control variables of stock market returns that have not been simultaneously studied before. In addition, we spread out our research period up to 15 years including many events and dynamics. Generalized Autoregressive Conditional Heteroskedasticity (GARCH) and multiple regression models are first employed. Then, an Artificial Neural Network (ANN) is used and compared with the results of the multiple regression. Hence, the results show that for both Tunisia and Turkey, exchange rate volatility has a significant effect on stock market fluctuations.

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.

scholarly journals Effects of Exchange Rate and Inflation Rate on Stock Market Returns Volatility in India.

2020 ◽  
Author(s):  
Nenavath Sre ◽  
Suresh Naik
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Error Correction ◽  
Inflation Rate ◽  
Market Returns ◽  
Stock Market Returns ◽  
Positive Effects ◽  
Distributed Lag ◽  
Long Run ◽  
Short Run

Abstract The paper investigates the effect of exchange and inflation rate on stock market returns in India. The study uses monthly, quarterly and annual inflation and exchange rate data obtained from the RBI and market returns computed from the Indian share market index from January, 2000 to June, 2020.The paper uses the autoregressive distributed lag (ARDL) co-integration technique and the error correction parametization of the ARDL model for investigating the effect on Indian Stock markets. The GARCH and its corresponding Error Correction Model (ECM) were used to explore the long- and short-run relationship between the India Stock market returns, inflation, and exchange rate. The paper shows that there exists a long term relationship but there is no short-run relationship between Indian market returns and inflation. But, there is periodicity of inflation monthly considerable long run and short-run relationship between them existed. The outcome also illustrates a significant short-run relationship between NSE market returns and exchange rate. The variables were tested for short run and it was significantly shown the positive effects on the stock market returns and making it a desirable attribute of which investors can take advantage of. This is due to the establishment of long-run effect of inflation and exchange rate on stock market returns.

scholarly journals Financial contagion and 2016 oil crisis: a factor analysis

2020 ◽  
Author(s):  
Turki Maya
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Principal Component ◽  
Financial Contagion ◽  
Market Returns ◽  
Component Structure ◽  
Stock Market Returns ◽  
Oil Crisis ◽  
Market Indexes ◽  
Variance Explained

<p>The paper tries to answer the following question: could the 2016 oil price crisis generate financial contagion among stock markets? </p> <p>The study period is composed of two sub-periods; a quiet one from 3/01/2012 to 01/08/2014 and turbulent one from 04/08/2014 to 25/05/2016. Raw data consists of daily international stock market indexes prices. The co-movements of the stock market returns are analyzed through a principal component analysis (PCA).</p> <p>The results revealed that the <em>KMO</em> index (Kaiser-Mayer-Olkin) is higher during the turbulent period than during the quiet one and that the proportion of variance explained by the first component during the turbulent period reached 35% while during the quiet one it represented only 26,7%.Regarding the component structure, for the turbulent period, three factors are able to explain the stock markets indexes movements while for the quiet period four factors are required. </p> <p>The findings give more credit to the thesis supporting the linkage between cross correlation and financial contagion and classify the 2016 oil crisis, as just a coupling episode and not an extreme one.</p>

Effects of the COVID-19 pandemic on stock market returns and volatilities: evidence from selected emerging economies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bijoy Rakshit ◽  
Yadawananda Neog
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Emerging Economies ◽  
Market Performance ◽  
Exchange Rate Volatility ◽  
Oil Price ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
Stock Market Performance

Purpose The purpose of this paper is to investigate the effects of exchange rate volatility, oil price return and COVID-19 cases on the stock market returns and volatility for selected emerging market economies. Additionally, this study compares the market performance in the emerging economies during the COVID-19 pandemic with the pre-COVID and global financial crisis (GFC) period. Design/methodology/approach The authors apply the arbitrage pricing theory to model the risk-return relationship between the risk-based factors (exchange rate volatility and COVID-19 cases) and stock market returns. By applying the exponential generalized autoregressive conditional heteroskedasticity model, the study captures the asymmetric volatility spillover from the stock markets to foreign exchange markets and vice versa. Findings Findings reveal that exchange rate volatility exerts a negative and significant effect on the market returns in Brazil (BOVESPA), Chile (S&P CLX IPSA), India (SENSEX), Mexico (S&P BMV IPC) and Russia (MOEX) during the coronavirus pandemic. Regarding the effect of oil price returns, the authors find a positive relationship between oil price and stock market returns across all the economies in the study. The market returns of Russia, India, Brazil and Peru appeared more volatile during the pandemic than the GFC period. Practical implications As the exchange rate volatility is causing higher risk and uncertainty in the stock market’s performance, the central bank’s effort to maintain a stabilizing effect on the exchange rate sale can be proven crucial for the economies under consideration. Emphasized should also be given to boost investors’ confidence in the stock market, and for this, the government policy actions in reducing the transmission of the disease are the need of the hour. Originality/value While a large volume of literature on stock market performance in times of COVID-19 has emerged from developed economies, this study adds to the literature by exploring the emerging economies’ stock market performance during the COVID-19 pandemic. Unlike previous literature, this study examines the volatility spillover between stock and exchange rate markets in the worst affected emerging economies during the crisis.

A GARCH Modelling of Volatility and M-GARCH Approach of Stock Market Linkages of North America

2018 ◽  
Vol 19 (6) ◽  
pp. 1538-1553 ◽  
Author(s):  
Ajaya Kumar Panda ◽  
Swagatika Nanda
Keyword(s):  
North America ◽  
Stock Market ◽  
Stock Markets ◽  
Market Integration ◽  
Return Volatility ◽  
Sample Period ◽  
Market Returns ◽  
Stock Market Returns ◽  
Current Period ◽  
Highly Sensitive

The present study attempts to capture the return volatility and the extent of dynamic conditional correlation between the stock markets of North America region. The data contain weekly stock market returns spanning from the second week of 1995 to the fourth week of June 2016. Using univariate ARCH and GARCH approaches, the study finds evidence of return volatility and its persistence within the region. Mexican stock market neither reacts intensely to immediate market fluctuations nor the part of the realized past volatility spill over to the current period, whereas the stock markets of Canada and USA experience high persistence of return volatility and Bermuda stock market returns are highly sensitive to the immediate market fluctuations. Using MGARCH-DCC, this article finds that emerging markets are less linked to the developed market in terms of return and that there also exists a weak co-movement between the stock markets. There is no evidence of market integration throughout the sample period. Correlations tend to spread out equally throughout the sample period, but the co-variances were found to be more volatile during 2008–2010. This article reveals that changes in co-movement are not due to a change in the correlations between markets but is simply due to volatility.

scholarly journals Opportunity or Crisis? Volatility and Leverage Effect in the World’s Largest Economies

2019 ◽  
Vol 9 (4) ◽  
pp. 1
Author(s):  
Amalendu Bhunia ◽  
Devrim Yaman
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Market Volatility ◽  
Future Market ◽  
Market Returns ◽  
Stock Market Returns ◽  
The Us ◽  
The World ◽  
The Impact ◽  
The Relationship

This paper examines the relationship between asset volatility and leverage for the three largest economies (based on purchasing power parity) in the world; US, China, and India. Collectively, these economies represent Int$56,269 billion of economic power, making it important to understand the relationship among these economies that provide valuable investment opportunities for investors. We focus on a volatile period in economic history starting in 1997 when the Asian financial crisis began. Using autoregressive models, we find that Chinese stock markets have the highest volatility among the three stock markets while the US stock market has the highest average returns. The Chinese market is less efficient than the US and Indian stock markets since the impact of new information takes longer to be reflected in stock prices. Our results show that the unconditional correlation among these stock markets is significant and positive although the correlation values are low in magnitude. We also find that past market volatility is a good indicator of future market volatility in our sample. The results show that positive stock market returns result in lower volatility compared to negative stock market returns. These results demonstrate that the largest economies of the world are highly integrated and investors should consider volatility and leverage besides returns when investing in these countries.

DCC Analysis of the Two Stock Market Returns by a Threshold Model: Empirical Study of the Stock Markets in Japan and Canada

2012 ◽  
Vol 468-471 ◽  
pp. 181-185
Author(s):  
Wann Jyi Horng ◽  
Tien Chung Hu ◽  
Ming Chi Huang
Keyword(s):  
Stock Market ◽  
Empirical Result ◽  
Stock Markets ◽  
Threshold Model ◽  
Conditional Correlation ◽  
Market Returns ◽  
Stock Market Returns ◽  
Asymmetrical Effect ◽  
Relationship Of ◽  
The Relationship

The empirical results show that the dynamic conditional correlation (DCC) and the bivariate asymmetric-IGARCH (1, 2) model is appropriate in evaluating the relationship of the Japan’s and the Canada’s stock markets. The empirical result also indicates that the Japan and the Canada’s stock markets is a positive relation. The average estimation value of correlation coefficient equals to 0.2514, which implies that the two stock markets is synchronized influence. Besides, the empirical result also shows that the Japan’s and the Canada’s stock markets have an asymmetrical effect, and the variation risks of the Japan’s and the Canada’s stock market returns also receives the influence of the good and bad news, respectively.

scholarly journals The Relevance of Cboe Volatility Index to Stock Markets in Emerging Economies

2015 ◽  
Vol 6 (1) ◽  
pp. 93-106
Author(s):  
Tamara Mariničevaitė ◽  
Jovita Ražauskaitė
Keyword(s):  
Stock Market ◽  
Emerging Economies ◽  
Stock Markets ◽  
Chinese Stock Market ◽  
Stock Market Volatility ◽  
Global Risk ◽  
Stock Market Index ◽  
Market Returns ◽  
Stock Market Returns ◽  
Volatility Index

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.

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