Search results

The purpose of this paper is to examine the existence of the day-of-the-week effect in the Indian stock market.

Generalized Autoregressive Conditional Heteroskedasticity (GARCH) (1, 1), Exponential GARCH (EGARCH) (1, 1) and Threshold GARCH (TGARCH) (1, 1) models are employed to examine the day-of-the-week effect in the Indian stock market for the period of 28 years from 3rd July, 1990 to 31st March, 2022.

The empirical results derived from the GARCH models indicate the existence of day-of-the-week effects on stock returns and volatility of the Indian stock market. The study reveals that all the days of the week are positive and significant in National Stock Exchange (NSE)-Nifty market returns. The findings confirm the persistence of ARCH and GARCH effects in the daily return series. Moreover, the asymmetric GARCH models show that the daily stock returns exhibit significant asymmetric (leverage) effects.

The results of this study established that the Indian stock market is not efficient and there exists an opportunity to the traders for predicting the future prices and earning abnormal profits in the Indian stock market. The findings of the study are important for traders, investors and portfolio managers to earn abnormal returns by cross-border diversification.

First, to the best of the authors' knowledge, this paper is the first to study the day-of-the-week effect in Indian stock market considering the most recent and longer time period (1990–2022). Second, unlike previous research, this study used GARCH models (GARCH, EGARCH and TGARCH) to capture the volatility clustering in the data.

The authors analyze the relationship between exchange rate fluctuations of a number of major currencies and its impact on US stock market returns, as proxied by the S&P 500. Many studies have explored this topic since the early 1970s with varied results and with no evidence that clearly explains the relationship between exchange rates and stock market returns. This study takes a different look at this hypothesis and investigates the pairwise relationship between various exchange rates and the United States stock market returns (S&P 500 INDEX) from January 2000 to December 2019.

The authors test the data for unit roots using Phillip-Perron method. They use Johansen cointegration model to determine whether returns on S&P 500 are integrated with S&P 500. They use the VAR/VECM analysis to test whether there are any interdependencies between exchange rates and stock market return. Finally, they use various GARCH models, including the EGARCH and TGARCH models, to determine whether there exist volatility spillovers from exchange rate fluctuations in various markets to the volatility in the US stock market.

Using GARCH modeling, the authors find volatility in Australian dollar, Canadian dollar and the euro impact market return, and the volatility of Australian dollars and euro spills over to the volatility of S&P 500. They also find that the spillover is asymmetric for Australian dollars.

One of the limitations could be that the authors use different bivariate GARCH models rather than the MV-GARCH models. For future project(s), they plan to do this analysis from the perspective of a European Union or a British investor and use returns in those markets to see the impact of exchange rates on those markets. It would be interesting to know how the relationship will change during periods of financial crises. This could be achieved by employing structural break methodology.

Many studies have explored the relation between stock market returns and exchange rates since the early 1970s with varied results and with no evidence that clearly explains the relationship between exchange rates and stock market returns. This paper contributes by adding to the existing literature on impact of exchange rate on stock returns and by providing a detailed and different empirical analysis to support the results.

This paper aims to analyze and give directions for advancing research in stock market volatility highlighting its features, structural breaks and emerging developments. This study offers a platform to research the benchmark studies to know the research gap and give directions for extending future research.

The author has performed the literature review, and, reference checking as per the snowballing approach. Firstly, the author has started with outlining and simplifying the significance of the subject area, the review illustrating the various elements along with the research gaps and emphasizing the finding.

This work summarizes the studies covering the volatility, its properties and structural breaks on various aspects such as techniques applied, subareas and the markets. From the review’s analysis, no study has clarified the supremacy of any model because of the different market conditions, nature of data and methodological aspects. The outcome of this research work has delivered further magnitude to research the benchmark studies for the upcoming work on stock market volatility. This paper has also proposed the hybrid volatility models combining artificial intelligence with econometric techniques to detect noise, sudden changes and chaotic information easily.

The author has taken the research papers from the scholarly journal published in the English language only and the author may also consider other nonscholarly or other language journals.

To the best of the author’s knowledge, this research work highlights an updated and more comprehensive framework examining the properties and demonstrating the contemporary developments in the field of stock market volatility.

According to the Government Response tracker (oxCGRT) index, the strictest policy responses to the coronavirus pandemic from January 2020 to May 2022 belong to Italy, China, Hong Kong, Greece, Austria, Peru, Singapore and Malaysia. The main question is: “this level of strictness has been able to reduce the uncertainty of the stock market?”

To achieve this goal, the authors investigated the effect of oxCGRT index, and the growth rate of COVID-19 confirms cases on stock market uncertainty from January 2020 to May 2022 in the GARCH, EGARCH and TGARCH models.

Among these countries, the oxCGRT index has reduced uncertainty in the stock market only in Malaysia and Singapore. This result says an appropriate pattern of applying government policy responses is more important than the degree of stringency.

The study will contribute to the existing literature by examining the impact of the comprehensive oxCGRT index on the uncertainty of the stock market.

The purpose of this study is to investigate the impact of terrorist attacks on the volatility and returns of the stock market in Tunisia.

The employed sample comprises 1250 trading day from the Tunisian stock index (Tunindex) and stock closing prices of 64 firms listed on the Tunisian stock market (TSM) from January 2011 to October 2015. The research opts for the general autoregressive conditional heteroscedasticity (GARCH) and exponential generalized conditional heteroscedasticity (EGARCH) models framework in addition to the event study method to further assess the effect of terrorism on the Tunisian equity market.

The baseline results document a substantive impact of terrorism on the returns and volatility of the TSM index. In more details, the findings of the event study method show negative significant effects on mean abnormal returns with different magnitudes over the events dates. The outcomes propose that terrorism profoundly altered the behavior of the stock market and must receive sufficient attention in order to protect the financial market in Tunisia.

Very few evidence is found on the financial effects of terrorism over transition to democracy cases. This paper determines the salient reaction of the stock market to terrorism during democratic transition. The findings of this study shall have relevant implications for stock market participants and policymakers.

This paper aims to test for volatility spillovers among Islamic stock markets with the exogenous impact of geopolitical risk (GPR) to check the risk transmission among Saudi Arabia, Malaysia, Indonesia and Turkey. Researchers test for both the symmetric and asymmetric risk transmission.

For the symmetric response of volatility, the study uses simple generalized autoregressive conditional heteroscedastic (GARCH) and for the asymmetric response of volatility with the exogenous impact of GPR, the exponential GARCH models have been adopted.

The results suggest spillover effects exist from Turkey to Saudi Arabia, Indonesia to Malaysia and Saudi Arabia and Malaysia to Indonesia. The findings of volatility spillover from GPR to sample countries suggest that only Malaysia and Indonesia experience volatility spillovers from GPR.

The present study is limited to the context of four countries and Islamic equities; the study contributes to the literature on volatility spillover, Islamic finance, GPR and asset pricing.

This study contributes to individual, institutional investors’ policymakers’ knowledge in determining security prices, trading plans, investment hedging and policy regulation.

The extant literature disregards the GPR index to examine the volatility spillover effects among Islamic stock markets, which allow researchers to justify the mechanism of risk transmission due to GPR across the Islamic stock market.

To the best of the authors’ knowledge, this is the first research of its type to look at volatility spillover and GPR transmission in Islamic stock markets.

Start-ups are successful in receiving valuation in billions of US dollars prior to initial public offering (IPO). However, to sustain higher valuation, the stocks need to perform consistently after the IPO. Short-run stock performance of India-based start-ups during the first year of IPO listing from March 2021 to March 2022 is analysed.

The paper deals with the new generation start-ups' stock performance in emerging market in terms of total and abnormal return generated in comparison to the market (NIFTY-200). Further, the volatility of returns during bear and bull regimes is analysed through a family of Markov-switching GARCH models using both normal and skewed distributions.

The results suggest that start-up stocks are more volatile during bear regime than in the bull run in market-based economies where price limit policy does not apply. Besides, the cumulative abnormal return over the market return was lower for majority of start-up IPO stocks.

Though negative returns of the start-up stocks during the first year of IPO need not be surprising, higher volatility during bear regime is a matter of concern as it could severely impact retail investors and founders. The results hold implication for IPO regulation in emerging markets and for retail investors desirous of investing in start-up stocks.

Volatility of return is examined using a state-space model during the first year of the start-up IPO listing. The study contributes to the emerging market IPO literature by examining IPO performance in market-based economy. Previous IPO performance studies in emerging markets are predominantly based on ecosystems where start-ups are subjected to price limit policy, and it does not reflect the true nature of IPO performance across emerging markets.

This paper attempts to investigate the impact of the Russia–Ukraine war on the returns and volatility of the United States (US) natural gas futures market.

The study uses secondary data of 996 trading day provided by the US Department of Energy and investing.com websites and applies the event study methodology in addition to the generalized autoregressive conditional heteroscedastic (GARCH) family models.

The findings from the exponential EGARCH (1,1) estimate are the best indication of a significant positive effects of the Ukraine–Russia war on the returns and volatility of the US natural gas futures prices. The cumulative abnormal returns (CARs) of the event study show that the natural gas futures prices reacted negatively but not significantly to the Russian–Ukraine war at the event date window [−1,1] and the [−15, −4] event window. CARs for the longer pre and post-event window display significant positive values and coincides with the standard finance theory for the case of the US natural gas futures over the Russia–Ukraine conflict.

This is the first study to examine the impact of the Russia–Ukraine war on natural gas futures prices in the United States. Thus, it provides indications on the behavior of investors in this market and proposes new empirical evidence that help in investment analyses and decisions.

This study investigates the effect of unproven energy reserve news on the volatility of energy firms' stocks. Thus, investors' perception of unproven energy reserves is revealed. Additionally, the study aims to determine whether the effect of the news changes according to time and volatility level.

The general autoregressive conditional heteroskedasticity (GARCH) and exponential generalized autoregressive conditional heteroskedasticity (EGARCH) models consist of the energy reserve exploration news in Turkey for the period 2009–2022 and the volatility of 14 energy stocks.

The results indicate energy exploration news's negative and significant effect on volatility. According to empirical results, energy stock volatility is most affected in the first ten days. Besides, the results show that the significant models of energy reserve news in low-volatility stocks are proportionally higher than in high-volatility stocks.

Only unproved reserve news is included in the analysis, as sufficient confirmed reserves could not be reached during the sampling period. Further studies can compare proven and unproved reserve news effects. Additionally, a similar analysis can be conducted between Turkey and another country with a similar socio-economic character to examine different investor behaviors.

This research includes indications on managing investors' reactions to unproven energy reserve news.

This study contributes to the literature by analyzing unproven reserves. Contrary to previous studies, examining stock volatility also makes the study unique.

This study examines the impact of the Russo-Ukrainian War on the commodity markets of oil, wheat, and natural gas, in which these two countries play/have a dominant role. The author examines if during these extreme events an anti-leverage effect emerges and indicates the abnormal conditions of the markets.

The author uses daily returns from the future prices of brent oil, wheat, and natural gas for the period 31.3.2020–31.3.2022 and applies the exponential and the threshold asymmetry GARCH models.

The empirical findings confirm the existence of anti-leverage effect in the wheat and natural gas commodity markets and point to the existence of the leverage effect in the Brent market.

The existence of the anti-leverage effect means that stock prices and volatility present a positive relationship which is in contrast to the normal/conventional stylized facts which suggest the opposite. These findings could be useful for scholars and practitioners because they enable them to examine market abnormalities using the anti-leverage effect as a criterion and explore its relationship with extreme conditions and strategies that lead to skyrocketing increases in prices.

This study investigates the anti-leverage effect in commodity markets under extreme conditions, which has received little attention in the literature. Moreover, this paper links the existence of the anti-leverage effect with abnormal growth in asset prices, which shows a new direction for the behavior of assets when extreme conditions emerge.