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The objective of this article is to examine the volatility spillover effect between the foreign exchange market and the stock market of Brazil, Russia, India, China and South Africa (BRICS) countries along with Japan as the developed country in the region, affecting the BRICS countries. Generalized Autoregressive Conditionally Heteroscedastic (GARCH) (1,1) method is used to study the volatility between the stock market and the foreign exchange market in selected countries, and asymmetric model, that is, Exponential Generalized Autoregressive Conditional Heteroscedasticity—EGARCH (1,1) is also used to investigate the presence of leverage effects in both stock market and foreign exchange market in selected countries. GARCH findings suggest a two-way volatility spillover between the stock market and foreign exchange markets for India, China and South Africa. In BRICS countries, volatility spillover from the currency market to the stock market is seen as more evident and robust as compared to spillover from the stock market to the currency market. A positive asymmetry in spillover is also observed from the foreign exchange market to the stock market. The findings of the study may provide valuable information to investors for decision-making in international portfolio investment and also for economic policymakers for their financial stability perspective. [ABSTRACT FROM AUTHOR]

This research examines the correlations between the return volatility of cryptocurrencies, global stock market indices, and the spillover effects of the COVID-19 pandemic. For this purpose, we employed a two-stage multivariate volatility exponential GARCH (EGARCH) model with an integrated dynamic conditional correlation (DCC) approach to measure the impact on the financial portfolio returns from 2019 to 2020. Moreover, we used value-at-risk (VaR) and value-at-risk measurements based on the Cornish–Fisher expansion (CFVaR). The empirical results show significant long- and short-term spillover effects. The two-stage multivariate EGARCH model's results show that the conditional volatilities of both asset portfolios surge more after positive news and respond well to previous shocks. As a result, financial assets have low unconditional volatility and the lowest risk when there are no external interruptions. Despite the financial assets' sensitivity to shocks, they exhibit some resistance to fluctuations in market confidence. The VaR performance comparison results with the assets portfolios differ. During the COVID-19 outbreak, the Dow (DJI) index reports VaR's highest loss, followed by the S&P500. Conversely, the CFVaR reports negative risk results for the entire cryptocurrency portfolio during the pandemic, except for the Ethereum (ETH). [ABSTRACT FROM AUTHOR]

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This paper aims to examine the co-movement between the two economic powers, namely the USA and China. The authors are mainly interested in examining the dynamics of co-movements during, and in the pre-covid periods. Additionally, they have aimed to examine the volatility spillover between USA and China, during and in the pre-covid periods. In order to achieve the research-based objectives, advanced econometrics models have been applied to the data from July1, 2010, to April 30, 2021. The results show that the sample market is integrated in the long run. The results also indicate that the behaviour of the Chinese market is same as the US market, and offers negligible opportunities for investors for diversification during this time. The findings indicate that the Ganger Causality between the stock markets during crisis is significantly higher than the pre-crisis period. The results of EGARCH model confirm the presence of asymmetric volatility spillover effects between the US and Chinese markets, during the considered time periods. This study also examines the co-movement in China, grounded upon the robust approach that facilitates examining the dependence structure between the sample variables. The findings offer valuable understanding for investors who are looking for investment diversification opportunities worldwide. [ABSTRACT FROM AUTHOR]

We examined volatility spillover effects from five prominent global stock markets to India's stock market during the pre-and-post COVID-19 outbreak using daily adjusted closing prices between January 2019 and September 2021 from six capital markets. The structural breakpoint was identified as 23 March 2020, as per the breakpoint unit root test, to examine and compare the results pre-and-post COVID-19. Results show that previous period news and volatility feeds the next period's volatility significantly and the volatility is found to be persistent. The analysis also shows that during the pre-COVID period there is a negative significant volatility spillover from four of the five selected stock markets (Australia, China, Japan, and Germany) to the Indian stock market, and that spillover continues in the post-COVID period. There is a positive significant return and volatility spillover from the US market to the Indian stock market in the post-COVID-19 period. The results of our study will be useful for retail investors and portfolio managers in understanding the portfolio allocation methods in case of volatility spillover arising due to the crisis caused by the COVID-19 outbreak. [ABSTRACT FROM AUTHOR]

Shanghai's lockdown from April to May 2022 attracted worldwide attention. While the rest of the world has generally chosen to live with Covid-19, China still sticks to its elimination strategy, i.e. the dynamic Covid-zero policy. This paper considers this policy and its economic implications. First, this study describes the policy and provides a quantitative description of its development based on Google Trends data and the Baidu index. Second, we explore the economic impacts of the March – May 2022 lockdown and concludes that they were less severe – and the policy responses were also smaller – than those in early 2020. However, one major difference is that Chinese household and corporate sectors have much weaker expectations than in early 2020, and as a consequence, policy responses may also be less effective. Third, from the perspective of stock markets, which can be seen as an expected value of all possible scenarios in the future, this study finds that China's Covid-zero policy is considered to be detrimental to the economy. [ABSTRACT FROM AUTHOR]

For economists and investors, it is necessary to understand the random and nonlinear pattern of the stock market volatility. High volatility directly affects the financial market that leads to unpredictability. China–Pakistan Economic Corridor attracts economists and investors worldwide. Therefore, predicting the volatility of the stock markets related to CPEC is important. In this study we consider the most important stock markets lying on the route of CPEC, namely KSE 100 (Pakistan), SSE 100 (China), TADAWUL (Kingdom of Saudi Arabia), KASE (Kazakhstan), KLSE (Malaysia), BIST (Turkey), MOEX (Russia), FTSE (United Kingdom) and CAC40 (France). The daily returns of stock market indices consist of 1706 observations from December 2014 to July 2021. After the confirmation from the ARCH effect test, family GARCH models are employed, among them, based on AIC and BIC criteria, GARCH (1,1), EGARCH (1,1), and GARCH-M (1,1) are found suitable to forecast the volatility. The empirical study also suggests that the out-of-sample forecast GARCH-M (1,1) model is more appropriate as it has a minimum value of MAE, MSE, RMSE, MAPE, TheilU1, and Theil U2 among all the studied GARCH models. Furthermore, it is also found that the KSE-100 and SSE-100 have moderate and slow market average returns even though both stock markets are found to be the least risk-returns markets. [ABSTRACT FROM AUTHOR]

The purpose of this study to investigate the dynamics of return linkages and volatility spillovers between Asian emerging stock markets (China, Hong Kong, Japan, Malaysia, Pakistan, and South Korea). To achieve this task, we used bivariate EGARCH (1) model. We used daily closing stock prices from January 01, 2010, to December 31, 2018. The findings revealed that the own lagged spillovers are statistically significant in all cases at one percent level. Our findings also show that the asymmetric volatility spillovers are significant in all sampled stock markets except China. We find unidirectional volatility spillovers from the markets of China toward Hong Kong, Malaysia toward South Korea, Hong Kong toward South Korea, Pakistan toward Hong Kong, and Japan toward South Korea. Moreover, the volatility spillovers in the majority stock markets are significant and bidirectional. Therefore, these markets are interrelated, and the spillover effect should be taken into consideration by policymakers who are responsible for economic decision making as they can save the financial sector from unexpected financial shockwaves. [ABSTRACT FROM AUTHOR]

Stock liquidity plays important role in investors’ participation in any nation’s stock market. The global pandemic shock created market illiquidity especially among developing stock market like Nigerian stock market. However, the emergence of global pandemic via COVID-19 pandemic triggered declined market turnover (stock liquidity) which in turn created lack of confidence among stock investors in Nigeria. This study therefore examined the effects of Global pandemic on stock liquidity in the Nigerian stock market using stock turnover and COVID-19 pandemic as measure for stock market liquidity and global pandemic. The study employed expost facto research design using weekly data of both corona-virus pandemic and stock market turnover within the period of March, 2019 to February, 2022. The study employed Exponential GARCH (EGARCH) model and found a considerable negative consequence of Global Pandemic (Covid-19) on stock liquidity, implying that corona-virus pandemic has brought bad information (bad news) which deteriorate the liquidity in the stock exchange market. The study concluded that COVID-19 pandemic shock reduces stock liquidity in Nigerian stock exchange market. The study however recommended that government should put in place more palliative policies such as tax incentive and lowest interest rate on loan to individual and institutional investors which will cushion effect of COVID-19 pandemic and increase investors’ participation in the Nigerian stock market. Also, Nigeria stock market regulators should put in place sound measures that will enhance availability of stock information so as to arouse the interest more and new investors to the Nigerian Stock Market. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to investigate the risk-return and volatility spillover within the Tunisian stock market during the COVID-19 pandemic analyzing both the Islamic and conventional stocks' performance. Design/methodology/approach: Both symmetric (GARCH and GARCH-M) and asymmetric (Threshold GARCH and Exponential GARCH) models are used to analyze the market returns and volatility response. Standard and Poor's (S&P) index has been used to test both the Islamic and conventional stocks within the Tunisian stock market. Findings: The findings suggest that both Tunisia Islamic and conventional stock markets are highly persistent; however, the conventional stock index showed a negative return spillover on the Islamic stocks during the pandemic. The conventional stock index has also shown a higher exposure to risk for a lower amount of return, and evidence of potential diversification benefit between both indexes was found during the pandemic, whereas the Islamic market showed a positive leverage effect, indicating a positive correlation between past return and future return; the conventional index implied a negative leverage effect. Originality/value: The value of this paper emerges in studying three main aspects that are specific to the Tunisian stock market. This includes COVID-19 effect of return spillovers, volatility transmission across both conventional and Islamic stock market within the local financial market. [ABSTRACT FROM AUTHOR]

Purpose: In Ghana, even though scholars and experts in the field of economics and finance have expressed their opinions and perceptions on the effect of the pandemic on the Ghana Stock Exchange, there has been no study conducted to that effect. This study, therefore, aimed at examining the impact of COVID-19 on the stock returns on the Ghana stock exchange. This would help policy makers and investors in making efficient decisions. Design/methodology/approach: The outbreak of the novel COVID-19 has been a thorn in the flesh of the world in its entirety, affecting many aspects of life including the stock market. This study, therefore, examined the impact of the outbreak on the stock returns of the Ghana Stock Exchange. The study utilized data from the All Share Prices of the Ghana stock exchange, commonly known as the Ghana stoke exchange composite index (GSECI) for analysis. The data covered the period before the outbreak of COVID-19 and during the outbreak. It was revealed that the Ghana stock exchange experienced better returns on the market before the outbreak of the virus. The outbreak of COVID-19 has led to wide variations in the market increasing the risk of investments. The exponential General Autoregressive Conditional Heteroscedasticity (EGARCH) (1, 1) model also reveals that the outbreak of COVID-19 has a significant negative effect on the returns in the market. The market in these periods of COVID-19 is highly volatile. It is recommended that investors should carefully consider risk mitigation strategies to enable them diversify their investments effectively and efficiently against the high risk associated with the market in this COVID-19 era. Findings: It was revealed that the Ghana stock exchange experienced better returns on the market before the outbreak of the virus. The outbreak of COVID-19 has led to wide variations in the market increasing the risk of investments. The EGARCH (1, 1) model also revealed that the outbreak of COVID-19 had a significant negative effect on stock returns in the market. The market during these periods of COVID-19 was viewed as highly volatile. Research limitations/implications: The outbreak of COVID-19 is hence deduced to have a negative impact on the Ghana stock exchange. However, the knowledge of how the market has been affected by the disease, it is important that financial risk mitigation studies be undertaken. This goes beyond what this study has done. The study can further be expanded to include other important economic variables such as GDP, inflation, exchange rates and the likes in to the model. Practical implications: Investors should carefully consider risk mitigation strategies to enable them diversify their investments effectively and efficiently against the high risk associated with the market in this COVID-19 era. Social implications: It is also important that investors consider diversification of their investments in order to reduce the risk in their investments. It will be more appropriate for most investors to invest with companies such as banks and the telecommunications companies listed on the on the market. This is because most of the telecommunication companies in these times have taken advantage and are making good profit on their businesses. Likewise, some of the financial institutions are considered essential institution in these times. Investing in industries such as manufacturing and the oil and gas sector may be more risky. Originality/value: The decline in economic and financial market indicators could be credited to the failure of most business entities, organizations and firms which are struggling to sustain their operations in these times of COVID-19. These also include firms listed on the Ghana stock exchange with whom investors transact their daily businesses. However, about 70% of the Ghanaian economy heavily depends on these business and firms found in the private and informal sector. According to the Ghana Statistics Service COVID-19 Business Tracker Survey, about 131,000 businesses expressed their uncertainties with the business environment and also faced the challenge of financial accessibility. The study is appropriate to unearth the true effect and offer policy interventions. [ABSTRACT FROM AUTHOR]

Copyright of Ekonomika is the property of Society of Economists 'Ekonomika' and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The January effect, and its impact in the financial world, is one of the most researched calendar irregularities. The purpose of this study is to examine if there is a January influence on the South African stock market. Aggregate and sectorial indices of Johannesburg Stock Exchange (JSE) were examined. We analyse the January effect by Generalized Auto Regressive Conditional Heteroskedasticity Model (GARCH), exponential GARCH (EGARCH) and threshold GARCH (TGARCH) models. Findings from the mean equation showed a positive January effect for the Top 40 and Basic materials, whilst for the variance equation, a negative January anomaly was found in the Top 40, Health care, Telecommunications, and Technology indices. The January seasonal investment style is recommended for improving returns in Basic materials sector. Investing in the Telecommunications sector in January will assist an investor in portfolio diversification and reduce risk. The findings show that the January effect has shifted to other months. Given the limits of previous research, this study adds to the body of knowledge on calendar anomalies by bringing a South African viewpoint to the debate of the January anomaly and extending the analytic period to 1995-2018. [ABSTRACT FROM AUTHOR]

Understanding calendar trends may aid in the identification of stock market return drivers and the making of smarter investment selections. The study's goal was to see if there is a turn of the month influence on the South African equity market. We analyse Johannesburg Stock Exchange (JSE) indices covering the period 1995 to 2018. The Generalized Auto Regressive Conditional Heteroskedasticity Model (GARCH), exponential GARCH (EGARCH) and threshold GARCH (TGARCH) models are used to model turn of the month anomaly. The mean equation results of the turn of the month displayed a positive effect for the aggregate and sectorial indices. The variance equation showed no turn of the month effect in the Top 40 and All Shares indices, though the Basic materials sector indicated a positive turn of the month effect. Investing in the telecommunications industry provides the best returns for the turn of the month method. Basic materials should be avoided by investors since it increases their exposure. In the South African equities market, the occurrence of the turn of the month impact invalidates the efficient market theory. We offer value by analysing turn of the month influence sectorial indices for Africa's largest stock market, in contrast to earlier research. [ABSTRACT FROM AUTHOR]

This study investigates the impact of index futures trading on the spot market volatility for Ho Chi Minh Stock Exchange (HOSE). The data used in this study are daily VN30-Index, future trading volume and open interests covering the period from March 18th, 2015 to January 2nd, 2020. In order to capture the asymmetric effect, the EGARCH(1,1) model is employed in this study. It is found that the introduction of index future trading leads to the increase the spot market volatility. In addition, our empirical findings reveal that the impact of recent news on spot market volatility in the post-index future period is greater that than the pre-index future period; and the market volatility in the post-futures period is more persistent than in the pre-futures period. Moreover, the level of asymmetric effect on the market volatility in the post-index future period is significantly lower than that for the pre-index futures period. Finally, the results derived from the Granger causality test confirm that the bi-directional causality relation between the spot market volatility and the future trading activity exists in HOSE. [ABSTRACT FROM AUTHOR]

The holiday effect is one of the most noticeable seasonal anomalies in financial markets, and it appeals to technical traders who use past data from trading activities to devise profitable strategies. The purpose of this article is to assess the South African equity market's holiday anomaly. The financial data employed consists of market and sectorial indices of the Johannesburg Stock Exchange (JSE) spanning from 1995 to 2018. The holiday effect was modelled by Generalized Auto Regressive Conditional Heteroskedasticity Model (GARCH), exponential GARCH (EGARCH) and threshold GARCH (TGARCH) models. Negative pre-holiday effect was found in aggregate and sectorial indices for the variance equation. The mean and variance equations unveiled a post-holiday effect in market and sectorial indices. Basic materials should be avoided by investors since it increases their exposure. By investing in the Basic Materials sector, the pre-holiday trading strategy can help investors reduce their risk exposure. When it comes to post-holiday seasonal trading, investors should concentrate on the Telecommunications sector to generate higher profits. Investors can minimize losses by avoiding the Industrials sector, which increases risk exposure. In contrast to previous empirical research that focused on aggregate indices, our analysis delineates holiday anomaly for sectorial indices in South African equity. [ABSTRACT FROM AUTHOR]

This paper studies the effect of COVID-19 on the volatility of Australian stock returns and the effect of negative and positive news (shocks) by investigating the asymmetric nature of the shocks and leverage impact on volatility. We employ a generalised autoregressive conditional heteroskedasticity (GARCH) model and extend the analysis using the exponential GARCH (EGARCH) model to capture asymmetry and allegedly leverage. We proxy the news related to the negative effect of COVID-19 on the Australian health system and its economy as bad news, and on the other hand, measures taken by government economic stimulus packages through their monetary and fiscal policies as good news. The S&P ASX200 (ASX-200) index is used as a proxy to the Australian stock market, and we use value-weighted returns of the stocks listed on ASX-200 for the period 27 January 2020 to 29 December 2020. The empirical results suggest the EGARCH model fits better in capturing asymmetry and leverage than the GARCH model in estimating the volatility of the Australian stock returns. However, another interesting finding is that the EGARCH model with volatility equation without news demonstrates a larger (smaller) leverage effect of the negative (positive) shocks on the conditional volatility compared to its variant with the news. [ABSTRACT FROM AUTHOR]

We examine the impact of crude oil price fluctuations on equity markets for four emerging Latin American markets, namely, Argentina, Brazil, Chile, and Mexico. We adopt an approach that examines this relationship in both a time and frequency domains. The co‐spectral analysis confirmed that most of the observable coherence between crude oil and equity returns occurred at relatively short frequencies. The structural vector autoregression (SVAR) results suggest that shocks to crude oil price directed all equity markets into negative territory, though they typically reversed course after approximately twenty‐four months. Although the decomposition of the prediction error variance showed that crude oil prices were weakly exogenous in the SVAR model, in most cases Brazil's equity market may have been responsible for the higher percentage of variations in the remaining indices. The nonlinear Granger causality tests reveal, with the exception of the Merval index, the equity markets under study were responsive to crude oil price shocks. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19), the disease caused by the novel coronavirus SARS-CoV-2, has greatly affected financial markets, economies and societies worldwide. This study focusses on the Chinese stock markets. Based on Google Trends data during the period from 1 January 2020 to 12 April 2020, and using the exponential generalised autoregressive conditional heteroskedastic (EGARCH) model, this study finds that the higher uncertainty resulting from the COVID-19 pandemic is significantly associated with the drop in China's composite index, but this impact varies by sectors. Simultaneously, the higher uncertainty due to COVID-19 is significantly associated with greater volatility in stock returns for both the composite index and sector indices. [ABSTRACT FROM AUTHOR]

Australia—China relations, and especially Chinese influence in Australia, have been the subject of heated debate in Australia since 2016. The central issue is, how to balance concerns over Chinese influence in Australia with the economic benefits of Chinese trade and investment? This study—arguably the first of its kind—answers this question using rigorous empirical modelling. First, it uses Google Trends search results to measure Chinese influence in Australia. Second, it connects Chinese influence, as reflected in Google Trends search results, to financial markets, including stock markets, government bond markets and foreign exchange markets. Weekly data for January 2016–December 2019 are entered into an exponential generalised autoregressive conditional heteroskedastic model. The study finds that the effects of concerns over Chinese influence relate mainly to increased volatility of stock market indices and government bond yields, and downward pressure on the share prices of individual firms that are heavily exposed to Chinese markets. However, the overall effects appear to be minor or insignificant. The implications of these results are that China's economic coercion (if any) may not be effective, and Australia's responses to Chinese influence and interference (if any) may generate insignificant costs. Finally, this study makes original and significant academic contributions to academia by providing a novel framework for exploring international relations. [ABSTRACT FROM AUTHOR]

Copyright of Semestre Económico is the property of Sello Editorial de la Universidad de Medellin and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The characteristics of understanding the asset's behavior is examined in terms of influence of its past information or shock on its return behavior on the different broad market indices from NSE (National Stock Exchange). The GARCH family models were used to find best model fit based on the Akaike Info Criteria and Schwarz Info Criteria. From the empirical results, it is found that all the characteristics in regard to the spillover, persistence of volatility and leverage effect are persuading the variance on the selected index spot return during the selected sample periods. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to investigate the cointegration and volatility spillover dynamics between the USA and South Asian stock markets, namely, India, Pakistan and Sri Lanka. The main objective of this study is to provide the knowledge about integration of financial market and volatility spillovers before, during and after global financial crisis to investors, fund managers and policy-makers. Design/methodology/approach: The Johansen and Juselius cointegration test, Granger Causality test and bivaraite EGARCH model have been applied in this study to examine integration and volatility spillovers between selected stock markets. Findings: The findings show that long-term integration between the USA market and South Asian emerging stock markets. It is found that USA stock market has causal relationship with emerging stock markets in short-term. The findings of EGARCH model reveal that asymmetric volatility spillover effects significant in all selected stock markets in pre, during and post-crisis periods. Furthermore, significant volatility spillover is found from stock markets of USA to all selected South Asian markets during and post-crisis periods. However, volatility spillovers from USA to India and Sri-Lanka markets are significant, while insignificant in case of Pakistani market in pre-crisis period. Overall, we find that returns and volatility spillover effects are higher in financial crisis period as compared to non-financial crisis period. Practical implications: The findings of this paper have important implications for investors, portfolio managers and policy-makers. They can take potential benefits from international portfolio diversification by considering all these facts. The understanding and knowledge of across volatility transmission help them to maximize the gains from diversification and minimize the risk. Policy-makers can develop such strategies which protect the markets of these economies from future financial crisis. Originality/value: Although in finance literature numerous studies have been conducted on integration between different stock markets, most of the studies investigated the integration and volatility spillovers between developed stock markets. However, many studies also analyzed the integration among emerging stock markets in literature review but it is hard to find studies in the context of South Asian stock markets on the effect of global financial crisis on stock markets. The main contribution of this study is to investigate the stock markets integration and volatility transmission between the USA and South Asia by considering the effect of recent 2007 US subprime financial crisis. [ABSTRACT FROM AUTHOR]

This study aims to investigate the potential effects of structural breaks on volatility permanence and asymmetry in stock exchanges of fragile five countries. The study covers the stock market index of 12 countries that were evaluated as fragile fives by various investment institutions on different dates between January 2013 and November 2019. The GARCH and EGARCH models are used for volatility estimates, and ICSS iteration algorithm is used to detect structural breaks. Results of the study reveals that among the 12 stock exchanges Indonesia, India, Brazil, Russia and Turkey are the top five countries with persistent volatility in their stock market indices. According to the empirical results from the study, volatility models in which structural breaks were not included depicts that the permanence effect is high in Indonesia and India, however, it is relatively lower in Argentina and Egypt. In addition, asymmetric volatility and leverage effect was observed in all country indices except Argentina. While where the response to negative shocks are strongest the indices of Pakistan, Qatar, South Africa and India, the response in Russia is lower. No structural breaks were observed in South Africa, Mexico, Argentina and Qatar exchanges during the period considered in study. In addition, it was found that using structural breaks in volatility estimates increased the predictive performance of the models. [ABSTRACT FROM AUTHOR]

This paper investigates the domestic stock market reaction to the announcement of South Africa winning the bid to host the 1995 Rugby World Cup, 2003 Cricket World Cup, and 2010 FIFA World Cup as well as Morocco concurrently losing the hosting competition for the 2010 FIFA World Cup. We used Event Study and EGARCH models. For Event Study, we evaluated normal market performance using 250 daily stock returns, while abnormal returns were tested within a 41-day (-20, +20) event window. The test was replicated using 2,227 daily compounded stock returns for the EGARCH model. Based on both the Event Study and EGARCH models, our findings show that the stock market responded positively to the hosting of mega-sport events for the bid winner (South Africa) and reacted negatively to the bid loser (Morocco). The results are statistically significant at conventional test levels. The findings support policy decisions that welcome mega-sport events. [ABSTRACT FROM AUTHOR]

This paper disentangles oil volatility risk to two components. The first component is attributed to crude oil, while the second is related to gasoline. This disentanglement serves the purpose of investigating the extent to which crude oil and gasoline are complementary in impacting return and variance residuals. The Realized-EGARCH model of Hansen et al. (J Appl Econom 29(5):774–799, 2014) is used to test the hypothesis that stock markets show some delay in incorporating oil information. This study shows that both crude oil- and gasoline-based information impact stock markets contemporaneously in a complementary fashion. Unlike the underreaction hypothesis, which is suggested as an explanation to the negative lagged effect of crude oil price change on return, the sequential information hypothesis explains better the ways information about oil is disseminated among U.S. industry portfolios. [ABSTRACT FROM AUTHOR]

The paper seeks to investigate the effect of both internal and external macroeconomic on stock market return volatility in Ghana and Nigeria over 16 year period of January 2000 to December 2016. The study employs time series approach to investigate the impact of lag of stock market return, consumer price index, 91 days Treasury bill rate exchange rate between domestic currency and US dollar, real domestic product, international crude oil prices, London Stock Exchange all share index and political cycle (independent variables) on stock market volatility of Ghana and Nigeria (dependent variables). It uses Exponential Generalised Autoregressive Conditional Heteroskedascity (EGARCH) as the main model. The results from the study indicate that macroeconomic/political factors affect stock market volatility. This is one of the few studies on Ghana and Nigeria and probably on Africa which tests for stock market volatility as a result of internal and external macroeconomic variable fluctuations. [ABSTRACT FROM AUTHOR]

The paper analysed the asymmetric effect of monetary policy to stock market in Nigeria. The study is conducted by using an EGARCH(X) model. The exogenous variable is a dummy variable which account for the monetary policy committee meetings of the central bank of Nigeria. All the parameters of the estimated model are statistically significant. The significance of the dummy variable in the mean and variance equation, couple with the significance of the asymmetric parameter provides empirical evidence that investors react to monetary policy innovation in Nigeria. The paper recommends for sound monetary policy that will develop and stabilize the stock market. [ABSTRACT FROM AUTHOR]

Forecasting the volatility of stock return plays an important role in the financial markets. The Generalized Autoregressive Conditional Heterscedasticity (GARCH) model is one of the most common models used for predicting asset price volatility from the return time series. In this study, we have considered quantified news sentiment and its impact on the movement of asset prices as a second source of information, which is used together with the asset time series data to predict the volatility of asset price returns. We call this news augmented GARCH (NA-GARCH) model. Our empirical investigation compares volatility prediction of returns of 12 different stocks (from two different stock markets), with nine datasets for each stock. Our results demonstrate that NA-GARCH provides a superior prediction of volatility than the 'plain vanilla' GARCH and exponential GARCH models. These results vindicate some recent findings regarding the utility of news sentiment as a predictor of volatility and also vindicate the utility of our novel model structure combining the proxies for past news sentiments and the past asset price returns. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of the European Central Bank's unconventional monetary surprises on major European stock markets. Three measures for surprises are used: (a) the change in domestic 10‐year government bond yields, (b) the change in the spread between German and Italian (Spanish) 10‐year bond yields, and (c) the change in yields of a safe euro‐denominated asset, such as German bonds. I show that unconventional monetary policy surprises significantly influence stock returns. For instance, monetary decisions that cause a decrease in Italian (Spanish) sovereign spread led to an increase in the stock returns. In addition, I find that a positively surprising shock—a fall in the domestic bond yield and an increase in German interest rates—leads to higher stock returns. Finally, sovereign spreads seemed to have larger effects on stock returns both during crisis and postcrisis years. [ABSTRACT FROM AUTHOR]

Vietnam is one of the countries in Asia with the highest nonperforming loans (NPL) ratio, which has affected the operations of the bank and further, to the development of the Vietnamese economy. The State Bank of Vietnam has decided to establish the Vietnam Asset Management Company. This is a special tool of the State Bank for handling nonperforming loans, making healthy financials, minimizing risk for financial institutions and enterprises, and promoting credit growth of the economy. The purpose of this study is to investigate the impact of the Vietnam Asset Management Company as a political event on stock market return and volatility in the Vietnam stock exchange. We collected VN-index data in the Ho Chi Minh stock exchange from 2008 to the third quarter of 2014 as sample data. Using the Exponential General Autoregressive Conditional Heteroscedasticity (EGARCH) model, we found some evidence that the VAMC performances have a positive significant effect on stock market return and volatilities. [ABSTRACT FROM AUTHOR]

Copyright of Financing is the property of Financing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Terrorism, political system instability and currency rate fluctuations are the three most evident issues of 21st century. In this study, comparative analysis is performed to check the impact of all these issues on PSX Volatility. EGARCH (1,1) approach is used on four different kinds of data collected from 1st January 2000 to 31st December 2015. Terrorist events, FX return fluctuations with restoration of democratic political system in Pakistan are considered in this study. Results confirm that democratic political government reduces PSX volatility while terrorism increases it. Terrorist attacks are categorized into various categories. Event day analysis confirms that Pakistan stock market (PSX) is efficient enough to absorb the effects of terrorist attack within a day. Holding portfolios and performing arbitrage activit ies by the investors diversify the risks due to foreign exchange (FX) fluctuations which show no significant impact on PSX volatility. [ABSTRACT FROM AUTHOR]

The central theme of this research paper is about the role of idiosyncratic risk in stock returns of non-financial sector of Pakistan Stock Exchange. In the framework of asset pricing model, literature suggests that idiosyncratic risk is independent to the specific assets therefore it has no role in explaining the returns. However, modern portfolio theory suggests that in an under diversified portfolio, idiosyncratic risk has positive relationship with stock returns, while the negative association of idiosyncratic risk has also been reported by different scholars. To settle this issue in the context of Pakistan, the present study investigates the role of idiosyncratic risk empirically in non-financial sector of Pakistan. The daily and monthly data are taken from January 2005 to 2016 for analysis. Various types of statistical tools are applied to examine the association between idiosyncratic risk and stocks returns. Cross sectional regression is used for testing the association between expected conditional idiosyncratic risk and returns. Conditional idiosyncratic risk is estimated through EGARCH model. The empirical results showed that conditional idiosyncratic risk and return of non-financial, firms has significant positive relationship after controlling different factors such as value, momentum and size, whereas the lag idiosyncratic risk has no relationship with stock returns. The empirical evidence confirms the prediction of previous studies. At the end it is suggested that investors can develop profitable portfolio after considering the idiosyncratic risk. [ABSTRACT FROM AUTHOR]

This study investigates the incremental information content of implied volatility index relative to the GARCH family models in forecasting volatility of the three Asia-Pacific stock markets, namely India, Australia and Hong Kong. To examine the in-sample information content, the conditional variance equations of GARCH family models are augmented by incorporating implied volatility index as an explanatory variable. The return-based realized variance and the range-based realized variance constructed from 5-min data are used as proxy for latent volatility. To assess the out-of-sample forecast performance, we generate one-day-ahead rolling forecasts and employ the Mincer–Zarnowitz regression and encompassing regression. We find that the inclusion of implied volatility index in the conditional variance equation of GARCH family model reduces volatility persistence and improves model fitness. The significant and positive coefficient of implied volatility index in the augmented GARCH family models suggests that it contains relevant information in describing the volatility process. The study finds that volatility index is a biased forecast but possesses relevant information in explaining future realized volatility. The results of encompassing regression suggest that implied volatility index contains additional information relevant for forecasting stock market volatility beyond the information contained in the GARCH family model forecasts. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to investigate the volatility spillover from crude oil and gold to the BRICS stock markets, after removing the effect of co-movement of prices of crude oil and gold.Design/methodology/approach Three multivariate GARCH models (dynamic conditional correlation, constant conditional correlation, and Baba, Engle, Kraft and Kroner) are used to capture the dynamic relationship between the crude oil and gold returns. The innovations from gold and oil are orthogonalized, and the EGARCH model is employed for the spillover analysis. The influences of oil price shocks and gold price shocks are tested on the returns of each of the BRICS equity markets.Findings There is evidence of volatility spillover from both the crude oil and gold to the BRICS stock markets. A sub-sample analysis suggests that the volatility spillover from gold was not significant before the financial crisis of 2008, but became significant post-crisis. The volatility asymmetry, which was not significant before the crisis, also became significant after it.Originality/value This study examines the volatility spillover to the BRICS stock markets from crude oil and gold, after accounting for the co-movement in their prices. It can help equity investors to judge whether gold can provide incremental diversification benefit, if used in conjunction with crude oil. The study also provides insights into the changes caused by the 2008 financial crisis on this volatility spillover mechanism. [ABSTRACT FROM AUTHOR]

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The rate of information flow into the market in generating market volatility has been a much debated issue in the finance research. Moreover, since the rate of information cannot be directly observable and quantifiable, trading volume has been considered to be a good proxy for incorporating such information. The mixture of distribution hypothesis (MDH) and the sequential information hypothesis (SIAH) provide the theoretical justification for the relationship between trading volume and market volatility. This paper revisits the relationship between equity trading volume and returns volatility for the Johannesburg Stock Exchange (JSE) of South Africa using daily data over the period of 6th July 2006 to 31st August 2016. Further, it analyzed an after-crisis period, i.e., 1/04/2008 to 8/31/2016, in order to verify the findings. EGARCH and Granger causality models are employed to analyze the volume-volatility relationship. Also the level of volatility persistence has been compared before and after the inclusion of trading volume in the volatility model as an exogenous variable. The analysis shows that the JSE exhibits volatility asymmetry implying that the return volatility responds more to the bad news than to the good news. The relationship between trading volume and market volatility is found to be positive and contemporaneous supporting the MDH. This study also uncover that the volatility persistence remains high even after the inclusion of trading volume as an explanatory variable in the volatility model. The above set of results also holds for the post-crisis sub-sample. Furthermore, the pairwise Granger causality tests indicate a feedback relationship between volume and volatility only in the case of the sub-sample. But for the full sample, a unidirectional causality between volume and volatility, with trading volume Granger causes market volatility was observed. As it was observed that there is a positive and contemporaneous relationship between volatility, and also that the trading volumes cannot attenuate the level of volatility persistence, findings advise the equity market participants to be cautious in their trading behavior; and through messages to the regulators that risk management practice should be strengthened in order to control for market volatility that associated with increasing trading volume. [ABSTRACT FROM AUTHOR]

In this paper, we check for existence of multifractal in volatility of Moroccan family business stock returns and in volatility of Casablanca market index returns based on multifractal detrended fluctuation analysis (MF-DFA) technique. Empirical results show strong evidence of multifractal characteristics in volatility series of both family business stocks and market index. In addition, it is found that small variations in volatility of family business stocks are persistent, whilst small variations in volatility of market index are anti-persistent. However, large variations in family business volatility and market index volatility are both anti-persistent. Furthermore, multifractal spectral analysis based results show strong evidence that volatility in Moroccan family business companies exhibits more multifractality than volatility in the main stock market. These results may provide insightful information for risk managers concerned with family business stocks. [ABSTRACT FROM AUTHOR]

Background: The aim of this study is to investigate the effect of the oil price and its volatility on the stock market of Pakistan before and after the 2007 financial crisis period. Methods: The analyses are carried out on daily data for the period from July 31, 2000 to July 31, 2014. This study uses several econometric techniques for the analyses, namely, the Johansen-Juselius cointegration test, generalized autoregressive conditional heteroskedasticity (GARCH) model, exponential generalized autoregressive conditional heteroskedasticity (EGARCH) model, variance decomposition method, and impulse response function. Results: The results of the cointegration method indicate a significant long-run association between stock market and oil prices in the pre-crisis period. The EGARCH model shows that oil price returns have a significant effect on stock market returns in both sub-periods, while the result for the GARCH model is significant only in the post-crisis period. We find a significant effect of oil price volatility on the stock market in both sub-periods from the GARCH model. Furthermore, the EGARCH model shows an asymmetric effect of oil price volatility on the stock market in the pre-crisis period. Variance decomposition shows that stock market variations are mostly explained by self-innovation. Moreover, the impulse response function results show that oil price shocks affected the stock market adversely in the pre-crisis period but positively in the post-crisis period. Conclusions: This study suggests that economic policymakers and investors should consider the oil price as an important factor affecting stock market returns. [ABSTRACT FROM AUTHOR]

The study analyzes the beta-return characteristic, considering the asymmetric beta behavior in the up market versus the down market for the Bursa Malaysia (BM). This study uses a sample period from 2001-2015 with two dual-beta models, the capital asset pricing model (CAPM), and the Fama- French, three-factor (FF3F) model, to examine 60 stocks listed on the bourse. The estimated return and beta indicate that most stocks have experienced an increasing (decreasing) beta in the downtrend (uptrend) period. It is inferred that investors are rewarded with a positive risk premium for holding an asset in the down market, while the upside beta carries a negative premium. If news asymmetry captures a significant part of investors' risk perception in the market, there is evidence that a conditional FF3F model is more useful than a conditional CAPM, which is likened to both the dual-beta FF3F and the CAPM in an unconditional context. [ABSTRACT FROM AUTHOR]

This article examines feedback trading and autocorrelation pattern of stock returns in the equity markets of Ghana, Kenya, Nigeria, and South Africa. We find evidence that positive feedback trading induces negative autocorrelation in the stock returns of Ghana, Kenya, Nigeria, and South Africa. The negative autocorrelation occurs during periods of increasing volatility, and all the four equity markets exhibit volatility asymmetry. We also find that Ghana, Nigeria, and South Africa were influenced by the 2008–2009 global financial crisis, and South Africa experienced the largest impact. These findings may have implications for risk management and price discovery in these equity exchanges. [ABSTRACT FROM AUTHOR]

Investors step into the stock market with the objective of earning smart returns on their investments. The stock market can help in realising these goals of the investors, however, all investments are subject to risks. The origin of the risk is the uncertainty of realising the desired returns on the investment. This aspect is known as risk of the investment. This paper aims to search the best model to estimate and forecast volatility of Indian and Chinese stock market. The data for the paper is related to the two main indices of Indian Stock Market namely, SENSEX and NIFTY and two indices of Chinese stock market, namely, Shenzhen composite index and Shanghai composite index for the period July 2003 to June 2013. We applied symmetrical as well as asymmetrical GARCH models to the data. Among all the three models i.e. GARCH, EGARCH and TARCH, we found the GARCH (1,1) model as the best model to estimate and forecast the volatility of Chinese stock market for both the daily and weekly return series. For the Indian stock market, the recommended volatility estimation and forecasting model is EGARCH model that captures the leverage effect. We did not find volatility clustering and leverage effect for the monthly return series for both Indian and Chinese stock market. Thus, it is suggested to use the traditional time invariant volatility models for the monthly return series. [ABSTRACT FROM AUTHOR]

In this paper the conditional dependence of stock market in Mexico and the United States is studied. Symmetric Joe-Clayton copula is used and conditional probabilities of increases (decreases) in Mexico stock index when there are increases (decreases) in the U.S. stock index are estimated. For the marginal distributions, AR-TGARCH and AR-EGARCH models with a standardized Student's t distribution for innovations are proposed. Empirical results suggest that there is a high degree of conditional dependence in the tails, presenting higher volatility on the upper (right) tail throughout the period. [ABSTRACT FROM AUTHOR]

This study examines whether there exists the congressional effect of NPC and CPPCC on Shanghai and Shenzhen stock market. Empirical result found that the NPC sessions have significant influence on the risk of B shares on the Shenzhen Stock market, but not on other indices before the global financial crisis. The CPPCC sessions have significant influence on the risks associated with returns of composite indices and B shares in Shanghai before 2008 financial crisis, but only on B shares in Shanghai post-2008. Correlation with the returns of B shares remain significant, but not with risks post-2008. In sum, both the NPC and CPPCC sessions are negatively correlated with stock returns volatilities pre- and post the financial crisis. [ABSTRACT FROM AUTHOR]

I test Black's leverage effect hypothesis on a panel of U.S. stocks from 1997 to 2012. I find that negative stock return innovations increase the future volatility of equity returns by about 36% more than positive ones. There is a strong and positive relation between variation in the size of these leverage effects and variation in the firm's use of debt. I uncover this relation by applying the Fama/French/Carhart 4-factor asset pricing model in the exponential generalized autoregressive conditional heteroskedasticity mean equation and by using panel data to control for firm- and time-invariant unobservables via first differences and two-way fixed effects. [ABSTRACT FROM AUTHOR]

This paper uses daily data to investigate the behavior of institutional investors in Taiwan's stock market. We adopted TGARCH and EGARCH models to test various news. We found that, for the entire sample, a significant clustering phenomenon exists in the investment behavior of three institutional investors, and the impact due to a change of news content shows significant asymmetry and leverage effects. That is, the impact of bad news from the market is stronger than that of good news. In addition, an asymmetric phenomenon can also be seen for the international news aspect as responded to by foreign institutional investors. This phenomenon is more significant than those of the dealers and institutional trust investors. Moreover, the asymmetric phenomenon as responded to by the dealers for domestic news is more significant than those of foreign investors and institutional trust investors. [ABSTRACT FROM AUTHOR]

Purpose - This study aims to link the financial cooperation in the Nordic region and the interdependence between the stock markets in this area. The main emphasis is placed on the evolution of this interdependence as the financial integration was proceeding. Design/methodology/approach - Johansen's cointegration technique and the exponential generalized autoregressive conditionally heteroskedastic model are applied to test the long-run and short-run interdependences, respectively, among Nordic stock markets. In particular, the recursive estimation approach is used to reveal the evolution of the interdependence between those markets. Findings - The existence of two cointegrations over the sample period indicates that the markets depend on each other to some extent. The recursive estimation of Johansen's model further reveals that the interdependence had been greatly improving until late 2008. The interdependence between those markets is also confirmed convincingly by the short-term dynamics, noting that the spillover effects between most pairs of stock volatilities are witnessed in the empirical results. Practical implications - The findings show the dynamics of the long-run correlations between the Nordic stock markets, which imply the intrinsic response to the process of financial market reforms, the 2008 global financial crisis and the period after the crisis. The evidenced information about determinants of the interdependence between Nordic stock markets is sending strong signals to investors to enhance their investment strategies. Originality/value - Most of the existing studies have been restricted to the static long-run and/or short-run interdependence among those markets. However, this study contributes to the literature by investigating the dynamics of interdependence among the Nordic stock markets over time; moreover, the evolution of the market interdependence is sketched closely to the process of the regional financial market reforms. [ABSTRACT FROM AUTHOR]

Accurate forecasting of stock market volatility is an important issue in portfolio risk management. In this paper, an ensemble system for stock market volatility is presented. It is composed of three different models that hybridize the exponential generalized autoregressive conditional heteroscedasticity (GARCH) process and the artificial neural network trained with the backpropagation algorithm (BPNN) to forecast stock market volatility under normal, t-Student, and generalized error distribution (GED) assumption separately. The goal is to design an ensemble system where each single hybrid model is capable to capture normality, excess skewness, or excess kurtosis in the data to achieve complementarity. The performance of each EGARCH-BPNN and the ensemble system is evaluated by the closeness of the volatility forecasts to realized volatility. Based on mean absolute error and mean of squared errors, the experimental results show that proposed ensemble model used to capture normality, skewness, and kurtosis in data is more accurate than the individual EGARCH-BPNN models in forecasting the S&P 500 intra-day volatility based on one and five-minute time horizons data. [ABSTRACT FROM AUTHOR]

This article aims to implement a portfolio optimization strategy considering two fundamental aspects: the empirical regularities observed in the time series of stock returns, and the views of portfolio managers about these regularities. From an analytical point of view, all the results are examined through an application of the approach of Black and Litterman (1992). In particular, our innovative contribution to the extant literature is the use of the EGARCH-M (exponential GARCH-in-mean) model to formulate a volatility forecast of returns used as an input for determining some subjective views to be included in the Black–Litterman model. The bets of the portfolio manager thus enter into the mechanism of generating expectations about the vector of returns, revealing information about investment opportunities. The results show that the Black–Litterman (BL) model using the EGARCH inputs produces allocations with potentially sizeable benefits. Greater reliance on the implied BL excess returns, in setting the allocations, result in higher risk-return ratio. [ABSTRACT FROM AUTHOR]