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Understanding which market to invest in for a well-diversified portfolio is fundamental in economies that are highly vulnerable to fluctuations in exchange rates. Extant literature that has considered phenomenon hardly juxtapose the markets. The purpose of this study is to examine the effects of exchange rate volatility on the Stock and Real Estate market of South Africa. The essence is to determine whether the fluctuations in the exchange rate influence the markets prices differently.

The Generalised Autoregressive Conditional Heteroskedasticity [GARCH (1.1)] model was used in establishing the effect of exchange rate volatility on both markets. This study used monthly South African data between 2000 and 2020.

The results of this study showed that increased exchange rate volatility increases stock market volatility but decreases real-estate market volatility, both of which revealed weak influences from the exchange rates volatility.

This study has implication for policy in using the exchange rate as a policy tool to attract foreign portfolio investment. The weak volatility transmission from the exchange rate market to the stock and real estate market indicates that there is prospect for foreign investors to diversify their investments in these two markets.

This study investigated which of the assets market, stock or housing market do better in volatile exchange rate conditions in South Africa.

This study investigates the asymmetric effects of exchange rate and investors' sentiments simultaneously on stock market performance in the United States context. In addition, we have also considered the potential effect of the global financial crisis of 2008 on this nexus.

We have employed the NARDL (nonlinear autoregressive distributed lag) model on monthly data ranging from January-1999 to December-2018 to investigate the asymmetric (short- and long-run) effects of exchange rate and investors' sentiments on stock market performance. We have also broken down the data into two segments, pre and post-crisis periods to capture the effect of the global financial crisis of 2008.

The findings of the study reveal that exchange rate and investors' sentiments simultaneously affect stock market performance and omitting any of these variables can produce misleading results. Results also show that the effect of sentiments is stronger than the exchange rate. There is significant evidence of asymmetric short-run and long-run effects of both explanatory variables. Moreover, we have found different outcomes for pre and post-crisis periods. Specifically, the impact of macroeconomic variables on the stock market has been substantiated in the post-crisis period.

Several studies are available which separately evidence the effects of investors' sentiments and exchange rate on performance of the stock market but they can suffer from the problem of omitted variable bias. This study is conducted to test the said effect simultaneously in a single model. Moreover, this study is considering short-run and long-run asymmetry in analyzing the effects of explanatory variables along with the inclusion of the global financial crisis of 2008.

This paper contributes to the literature on exchange rate exposure by assessing the extent to which exchange rate risk is priced in both African emerging and developed equity markets. It examines whether this risk leads to a premium or discount in market returns. The study uses the United States and South Africa as representatives for developed and emerging economies, respectively.

The paper employs two-factor and three-factor conditional CAPM approaches with a two-stage estimation process. In the first stage, time-varying risk exposures are derived using the ICAPM model estimated through rolling regression. In the second stage, the impact of these risk exposures, particularly exchange rate risk exposure, is assessed on stock market returns using Generalized Linear Model (GLM) regression.

Unlike previous studies that suggest exchange rate risk is not necessarily priced in the equity market due to hedging, this paper finds that exchange rate risk is indeed priced in both African and developed equity markets, albeit to different extents. The African equity market demands a higher premium compared to the developed equity market.

The findings of this paper have significant implications for policymakers, asset managers, and investors. They provide insights for making more informed decisions, implementing effective risk management strategies, and fostering a more stable and appealing investment environment.

To the best of our knowledge, this is the first study to evaluate the degree of exchange rate exposure in environments characterized by high currency volatility versus those with low volatility, all within the context of the conditional ICAPM model.

As the onset of the Russia–Ukraine military conflict on February 24, 2022, individuals from Ukraine have been relocating in search of safety and refuge. This study aims to investigate how the influx of Ukrainian refugees has impacted the stock markets and exchange rates of Ukraine's neighboring states.

The authors focused on the neighboring countries that share a western border with Ukraine and have received the highest number of refugees: Hungary, Poland, Romania and Slovakia. The analysis covered the period from April 24 to December 31, 2022. After this period, the influence of the refugees is small, insignificant. Wavelet coherence, wavelet power spectrum and the time-varying parameter vector autoregressions method were used for data processing.

The key finding are as follows: a link exists between the dynamics of refugees from Ukraine and volatility of the stock indices and exchange rate of the host countries; volatility was significant in the first weeks after the start of the conflict in all the analyzed states; and the highest volatility was recorded in Hungary and Poland; the effect of refugees was stronger on stock indices than that on exchange rates.

To the best of the authors’ knowledge, it is the first research that presents the impact of refugees from Ukraine on stock markets and exchange rates volatility in the countries analyzed.

This research paper aims to analyze the stock exchanges of developed, emerging and developing countries to investigate the volatility in stock markets and to evaluate the rate of mean reversion.

The stock exchanges included in the research are NASDAQ, Tokyo stock exchange, Shanghai stock exchange, Bombay stock exchange, Karachi stock exchange and Jakarta stock exchange. Secondary daily data from Bloomberg are used to conduct the research for the period from January 2011 to December 2018. Generalized autoregressive conditional heteroskedasticity (GARCH) (1,1) model was applied to examine volatility and the half-life formula was used to calculate mean reversion in days.

The research concluded that all the stock exchanges included in the research satisfy the assumptions of mean reversion. Developing countries have the lowest volatility while emerging countries have the highest volatility which means that the rate of mean reversion is fastest in developing countries and slowest in emerging countries.

Future studies can determine the reasons for fastest rate of mean reversion in developing countries and slowest rate of mean reversion in emerging countries.

Developing countries show the lowest mean reversion in days while the emerging countries show the highest mean reversion in days indicating that developing countries take less time to revert to their mean position.

The majority of previous studies on univariate volatility models are mostly on applications of the models. Only a few researchers have taken the robustness of the models into account when applying them in emerging countries and not in developed, developing and emerging countries in one place. This makes the current study unique and more rigorous.

The current study immerses itself in the realm of diversification prospects within a select group of preeminent global stock exchanges. Specifically, the study casts its discerning gaze upon the financial hubs of the United States, Hong Kong, Germany, France, Amsterdam and India. In this expansive vista of international financial markets, the present analytical study aims to unravel the multifaceted opportunities that lie therein for astute portfolio management and strategic investment decisions.

The study encompasses daily time series data spanning from 2019 to 2022. To assess the interconnectedness among these stock indices, advanced statistical techniques, including Johansen cointegration methods and vector autoregressive (VAR) models, have been applied.

The research outcomes reveal both unidirectional and bidirectional relationships between the Indian, Hong Kong and US stock exchanges, encompassing both short-term and long-term time frames. Interestingly, the empirical findings indicate the presence of diversification opportunities between the Indian stock exchange and the stock exchanges of Germany, France and Amsterdam.

These insights hold significant value for both Indian and international investors, including foreign institutional investors (FIIs), domestic institutional investors (DIIs) and retail investors, as they can utilize this knowledge to construct more effective and diversified investment portfolios by understanding the intricate interconnections between these prominent global stock exchanges.

This research undertaking aspires to bring coherence to a landscape rife with divergent interpretations and methodological divergences. We are poised to offer a comprehensive analysis, a beacon of clarity amidst the murkiness, to shed light on the intricate web of interconnections that underpin the world's stock exchanges. In so doing, we seek to contribute a seminal piece of scholarship that transcends the existing ambiguities and thus empowers the field with a deeper understanding of the multifaceted dynamics governing international stock markets.

It has been argued in the literature that structural changes in the financial markets, such as integration, have the potential to cause herding behavior or correlated behavioral patterns in traders. The purpose of this study is to investigate whether there is any financial herding behavior in the Latin American Integrated Market (MILA), a transnational stock market composed of Chile, Peru, Colombia and Mexico stock exchanges and whether there is any ARCH or GARCH effect in the herding behavior models.

This study uses the modified return dispersion approach on daily index return data. The sample period is from January 03, 2002 to May 07, 2019. The data are obtained from the MILA database. To count time-varying volatilities in herding models, the authors run ARCH family regression with GARCH (1,1) settings. Hwang and Salmon (2004) model is used as a robustness test.

The authors found strong herding behavior under the general market conditions and moderate and partial herding behavior under some specified markets circumstances, such as bull and bear markets and high-low volatility states. Moreover, the pre-MILA period exhibits more herding behavior than the post-MILA period. The empirical results show that most of the ARCH and GARCH effects are statistically significant, implying that the past information of stock returns and market volatility significantly affect the volatility of following periods, which can also explain the formation of herding tendency among investors. Finally, the results of the robustness tests (Hwang and Salmon, 2004) confirm herding in all periods, except full sample period for Mexico and post-MILA period for Mexico and Colombia.

This study investigates the herding behavior in the MILA market in terms of market return, volatility and timing. A limitation of the paper is that the authors have not included other factors on the formation of herding behavior, such as macroeconomic factors, effects of regional or international markets and policy influences. The authors will explore the issue in the extension of the paper.

As MILA is the first virtual integration of stock exchanges without merging, the study provides useful findings and draws good inferences of herding behavior in the MILA market in terms of market return, volatility and timing which are useful for academics, investors and policymakers in their investment and decision makings.

The paper provides useful findings and draws good inferences of herding behavior in the MILA market in terms of market return, volatility and timing which are not only useful in practical implications, but also in social implications.

This study contributes to the herding literature by examining four different hypotheses in respect of the unique case of transnational stock exchange without fusions or corporate mergers, where each market maintains its independence and regulatory autonomy. The authors also contribute to the literature by including both ARCH and GARCH effects in the herding behavioral models along the Hwang and Salmon (2004) approach.

This paper aims to investigate the impact of geopolitical events of the Russia–Ukraine conflict on the stock market volatility of G20 countries. Furthermore, the paper also investigates the possible reasons for any similarities or differences in the results of the three sectors.

This paper measures the impact of the stock market sectoral index price (SIP) by using the daily closing price as a dependent variable. In addition, this study uses three independent variables: geopolitical risk (GPR), commodity price (CP) and foreign exchange rate (FER). Seventeen countries from the G20 are analyzed using a daily timeframe from September 2021 to August 2022 (before and during the Russian invasion).

The results revealed that FER, CP and GPR all affect SIP, but the level of significance and positive/negative signs vary in all three sectors. The positive FER affects SIP in all sectors, while the negative CP and GPR significantly impact SIP in the energy and transportation sectors.

This study’s research model is more suited for transportation and energy than consumer goods. Future researchers can enhance the research model for the consumer goods sector by incorporating additional variables to understand their relationship with SIP better.

This study explores the impact of the Russia–Ukraine conflict on the stock market in G20 countries, focusing on the top three most affected sectors.

BRICS (Brazil, Russia, India, China, and South Africa) a group of five emerging nations that are expected to lead the global economy by the year 2050. The growth potential of these nations attracts investors from all over the world who are in search of maximizing the return on their investments and limiting the losses to the lowest possible level. The purpose of this research study is to determine whether or not Indian stock market investors can diversify their stock market portfolios into other BRICS economies.

A daily frequency of stock market closing data for the BRICS nations over a period of 2013–2021 has been considered and several econometric techniques have been applied. Starting with the Granger causality test for checking the direction of causality. The VAR technique is applied to find out whether the movement in the Indian stock market is influenced by its own past values or the past values of the other BRICS nations, and lastly, the DCC-MGARCH technique is applied to check the degree of integration or the volatility spillover from the Indian stock market to the stock markets of other BRICS nations.

The results of the study indicated that in both the short term and long term, stock market volatility is spilling over from the Indian stock market to the stock markets of other BRICS nations. Hence, the study suggests that BRICS nations cannot be a destination for portfolio diversification for Indian stock market investors.

The stock markets of emerging nations experience high volatility, which creates confusion for investors as to whether to invest or to abstain from portfolio diversification. At present, there is a gap in the existing literature to capture the stock market volatility of BRICS nations. This research study fills this research gap and confirms that BRICS nations cannot be a destination for portfolio diversification. Moreover, equity market experts, portfolio managers and researchers can all take advantage of this study.

This study aims to determine experimentally factors affecting the satisfaction of retail stock investors with various investor protection regulatory measures implemented by the Government of India and Securities and Exchange Board of India (SEBI). Also, an effort has been made to gauge the level of satisfaction of retail equities investors with the laws and guidelines developed by the Indian Government and SEBI for their invested funds.

To accomplish the study’s goals, a well-structured questionnaire was created with the help of a literature review, and copies of it were filled by Punjabi retail equities investors with the aid of stockbrokers, i.e. intermediaries. Amritsar, Jalandhar, Ludhiana and Mohali-area intermediaries were chosen using a random selection procedure. Xerox copies of the questionnaire were given to the intermediaries, who were then asked to collect responses from their clients. Some intermediaries requested the researcher to sit in their offices to collect responses from their clients. Only 373 questionnaires out of 1,000 questionnaires that were provided had been received back. Only 328 copies were correctly filled by the equity investors. To conduct the analysis, 328 copies, which were fully completed, were used as data. The appropriate approaches, such as descriptives, factor analysis and ordinal regression analysis, were used to study the data.

With the aid of factor analysis, four factors have been identified that influence investors’ satisfaction with various investor protection regulatory measures implemented by government and SEBI regulations, including regulations addressing primary and secondary market dealings, rules for investor awareness and protection, rules to prevent company malpractices and laws for corporate governance and investor protection. The impact of these four components on investor satisfaction has been investigated using ordinal regression analysis. The pseudo-R-square statistics for the ordinal regression model demonstrated the model’s capacity for the explanation. The findings suggested that a significant amount of the overall satisfaction score about the various investor protection measures implemented by the government/SEBI has been explained by the regression model.

A study could be conducted to analyse the perspective of various stakeholders towards the disclosures made and norms followed by corporate houses. The current study may be expanded to cover the entire nation because it is only at the state level currently. It might be conceivable to examine how investments made in the retail capital market affect investors in rural areas. The influence of reforms on the functioning of stock markets could potentially be examined through another study. It could be possible to undertake a study on female investors’ knowledge about retail investment trends. The effect of digital stock trading could be examined in India. The effect of technological innovations on capital markets can be studied.

This research would be extremely useful to regulators in developing policies to protect retail equities investors. Investors are required to be safeguarded and protected to deal freely in the securities market, so they should be given more freedom in terms of investor protection measures. Stock exchanges should have the potential to bring about technological advancements in trading to protect investors from any kind of financial loss. Since the government has the power to create rules and regulations to strengthen investor protection. So, this research will be extremely useful to the government.

This work has societal ramifications. Because when adequate rules and regulations are in place to safeguard investors, they will be able to invest freely. Companies will use capital wisely and profitably. Companies should undertake tasks towards corporate social responsibility out of profits because corporate houses are part and parcel of society only.

Many investors may lack the necessary expertise to make sound financial judgments. They might not be aware of the entire risk-reward profile of various investment options. However, they must know various investor protection measures taken by the Government of India & Securities and Exchange Board of India (SEBI) to safeguard their interests. Investors must be well-informed on the precautions to take while dealing with market intermediaries, as well as in the stock market.