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The purpose of this paper is to examine the relation between gold return and stock market return and whether its relation changes in times of consecutive negative market returns for an emerging market, Malaysia.

The paper applies the autoregressive distributed model to link gold returns to stock returns with TGARCH/EGARCH error specification using daily data from August 1, 2001 to March 31, 2010, a total of 2,261 observations.

A significant positive but low correlation is found between gold and once‐lagged stock returns. Moreover, consecutive negative market returns do not seem to intensify the co‐movement between the gold and stock markets as normally documented among national stock markets in times of financial turbulences. Indeed, there is some evidence that the gold market surges when faced with consecutive market declines.

Based on these results, there are potential benefits of gold investment during periods of stock market slumps. The findings should prove useful for designing financial investment portfolios.

The paper evaluates the role of gold from a domestic perspective, which should be more relevant to domestic investors in guarding against recurring heightened stock market risk.

The aim of this paper is to examine the relationship between weather (temperature) and stock market returns using daily data from Portugal; also, to examine whether the temperature is driven by calendar‐related anomalies such as the January and trading month effects.

Daily financial and weather data from Lisbon Stock Exchange (PSI 20 index) and Lisbon capital for the period 1995‐2007 are considered. The paper employs an AR(1)‐TGARCH(1,1) model under several distributional assumptions (Normal, Student's‐t and GED) for the errors.

Empirical results show that temperature affects negatively the PSI20 stock returns in Portugal. Moreover, temperature is dependent of both January and trading month effects. Stock returns were found to be positive in January and higher over the first fortnight of the month. Lower temperature in January leads to higher stock returns due to investors' aggressive risk taking.

Further research should investigate the impact of other meteorological variables (humidity, amount of sunshine) and other calendar anomalies on the course and behaviour of major international stock indices using data before and after the recent crisis.

The findings are helpful to financial managers, investors and traders dealing with the Portuguese stock market.

The contribution of this paper is to provide evidence on the empirical linkages between temperature and stock market returns using GARCH models. To better understand the relationship between the temperature and stock market returns, the paper also examines whether the returns are higher in winter (January effect) and during the first or second fortnight of the month (trading month effect). To the best of the author's knowledge, this is the first empirical investigation on weather and stock market returns relationship for Portugal.

The purpose of this paper is to investigate the spillover effect of the US macroeconomic news on the first two moments of the Vietnamese stock market returns.

The author collected market expectation and actual announcements data for 12 key US macroeconomic announcements for the period from August 2000 to September 2009 from Bloomberg. The dataset consists of monthly Non‐farm payroll (NFPM), Unemployment level (UNEMP), Gross Domestic Product percentage level (GDP), Housing statistics (HOMEST), Industrial production (INDP), Leading Indicator (LEAD), Retail Sales (SALES), Consumer Price Index (CPI), Producer Index (PPI), Current Account (CA, quarterly), Trade Balance (BOT), and the Federal Reserve's target rates (FOMC, 8 times a year and ad hoc meetings if needed). The MA‐EGARCH (1,1) model is used for the empirical test of the US macroeconomic news spillover effects on the VNI index.

In general, the US real economic news has the strongest effect on the first two moments of the Vietnamese stock returns. This can be interpreted as evidence that Vietnamese market participants believe that the USA is targeting real economic activities other than other variables. It is also shown that even though the US stock market (proxied by S&P500 index) significantly affects the Vietnamese stock market returns, the spillover effect of the US macroeconomic news is still significant.

The author does not explore further on the transmission channels of the spillover effects of the US news on the Vietnamese stock market, reserving this task for future research.

The paper contributes to the extant literature in several ways. First, to the author's knowledge, the current literature lacks empirical evidence for the impact of the US macroeconomic news on the first two moments of the Vietnamese stock markets. Given the growing integration between the two economies, evidenced by the fact that the USA is Vietnam's largest foreign direct investor and importer, the US macroeconomic news is very important, not only for Vietnamese policy makers but also for market participants. Furthermore, the choice of a small and open market with increasing exposure to the world economy and vulnerable to the US news (i.e. Vietnam) would help in reducing the problem of endogeneity bias in previous studies employing large economy pairs, as the US news might affect the Vietnamese stock market but not the reverse. Finally, previous studies tend to investigate the impact of macro news only on conditional returns. In this study, both conditional returns and the conditional variance of returns are modelled simultaneously in a time‐varying framework (MA‐GARCH) to better capture the impact of macroeconomic news on stock returns and stock market volatility.

In this paper, we provide new evidence to strengthen the stock market overreaction hypothesis by examining a new context that has not been explored before. Our research is inspired by the widely held belief that investor sentiment experiences abrupt changes from optimism to pessimism as the market switches between bull and bear states.

If the stock market overreaction hypothesis is correct, it implies that investors are inclined to become excessively optimistic during bull markets and overly pessimistic during bear markets, resulting in overreaction and subsequent market correction. Consequently, the study first develops two testable hypotheses that can be used to uncover the presence of stock market overreaction with subsequent correction. These hypotheses are then tested using long-term data from the US market.

The study's findings support the hypothesis while also revealing a significant asymmetry in investor overreaction between bull and bear markets. Specifically, our results indicate that investors tend to overreact towards the end of a bear market, and the subsequent bull market starts with a prompt and robust correction. Conversely, investors appear to overreact only towards the end of a prolonged bull market. The correction during a bear market is not confined to its initial phase but extends across its entire duration.

Our study has some limitations related to its focus on investigating stock market overreaction in the US market and analyzing the pattern of mean returns during bull and bear market states. Expanding our study to different global markets would be necessary to understand whether the same stock market overreaction effect exists universally. Furthermore, exploring the relationship between volatility and overreaction during different market phases would be an exciting direction for future research, as it could provide a more complete picture of market dynamics.

Our study confirms the presence of the stock market overreaction effect, which contradicts the efficient market hypothesis. We have observed specific price patterns during bull and bear markets that investors can potentially exploit. However, successfully capitalizing on these patterns depends on accurately predicting the turning points between bull and bear market states.

The results of our study have significant implications for market regulators. Stock market overreactions resulting in market corrections can severely disrupt the market, leading to significant financial losses for investors and undermining investor confidence in the overall market. Further, the existence of overreactions suggests that the stock market may not always be efficient, raising regulatory concerns. Policymakers and regulators may need to implement policies and regulations to mitigate the effects of overreactions and subsequent market corrections.

This paper aims to provide additional support for the stock market overreaction hypothesis using a new setting in which this hypothesis has not been previously investigated.

This study aims to determine the role of gold as a safe haven, hedge and asset diversification for Shariah stock in conditions of extreme stock market declines.

Quantitative approach is used by applying the threshold generalized autoregressive conditional heteroskedasticity (TGARCH) model to capture bad or good news in the market condition and quantile regression method to obtain the extreme values of stock returns in several market conditions. The data used were the daily closing price of gold and the Jakarta Islamic Index from January 2011 to October 2022.

The average conditions show gold does not have a hedge property and only acts as an asset diversification. Second, gold has a substantial, safe haven property in every economic condition. However, the safe-haven property of gold seemed to weaken during the most extreme stock market decline. Thus, although gold appears as a safe haven and asset diversification, it remains a risky investment and only provides a minor role in the face of the extreme stock market period.

This research provides a discourse and literature for Islamic investors and investor managers to choose the right investment instrument in various economic conditions where gold has a function as diversification and safe haven in their asset portfolio under any other asset portfolio conditions which is also in line with modern portfolio theory. For policymakers, the study can be used as material for consideration in making policies related to the accessibility of gold as an investment instrument.

This study presents the originality by using the price of Antam gold as a proxy for gold investment during the latest research year data and focusing on case studies in Islamic capital market in Indonesia. Moreover, this research provides quantile regression that sharply discussion in various economics condition.

This paper investigates the generalized Fisher hypothesis for nine equity markets in the Asian countries. It states that the real rates of return on common stocks and the expected inflation rate are independent and that nominal stock returns vary in a one‐to‐one correspondence with the expected inflation rate. The regression results indicate that stock returns in general are negatively correlated to both expected and unexpected inflation, and that common stocks provide a poor hedge against inflation. However, the results of the VAR model indicate the lack of a unidirectional causality between stock returns and inflation. It also fails to find a consistent negative response neither of inflation to shocks in stock returns nor of stock returns to shocks in inflation in all countries. It appears that the generalized Fisher hypothesis in the Asian markets is as puzzling as in the developed markets.

This study aims to evaluate the structural oil shocks effect on stock returns of Indian renewable energy companies across market conditions.

This study applies the structural vector autoregression model to estimate sources of oil shocks such as oil supply shock, aggregate demand shock and oil price-specific demand shock. In the next step, the panel quantile regression model estimates the effect of these oil shocks on stock return across market conditions. Monthly data are collected from January 2009 to December 2019. All renewable energy companies listed on the National Stock Exchange of India are considered for the analysis.

In the whole sample analysis, this study finds that oil shocks negatively affect stock returns in most of the market conditions except oil price-specific demand shock. In sub-groups, oil shocks driven by supply and aggregate demand also negatively affect stock return in most market conditions. This study finds the positive interaction of oil price-specific demand shock. A majority of these positive interactions happen in bearish market conditions. In the whole sample, the asymmetric effects of shocks driven from oil supply and oil price-specific demand are seen in most quantiles or market conditions. At the same time, aggregate demand shock does not affect asymmetrically. In the sub-group analysis, standalone renewable energy companies stock returns are least asymmetrically affected by these oil shocks. The asymmetries of oil supply-driven shock on stock returns of the renewable energy sub-group companies are found in most quantiles.

First, this is a company-level study of the stock returns response to the structural oil shocks in the renewable energy sector. Second, to the best of the authors’ knowledge, this type of study is the first in the Indian context. Third using panel quantile regression model along with capital asset pricing model framework, the authors investigate these effects across market conditions.

This paper aims to analyze the downside risk for the stock indices of BRICS countries. The study also aimed to study the interrelationship, directional influence and interdependence among the stock exchanges of BRICS economies to provide insights for policymakers, fund managers, investors and other stakeholders.

The authors used Value at Risk (VaR) as an indicator of downside risk and time series econometrics for measuring the long run relationship, directional influence and interdependence.

The calculated VaR estimates, long-run linkages and strong interdependence among these indices especially with the returns of Brazil exerting a notable impact on the returns of other BRICS nations. These results emphasize the significance of taking into account cross-country spillover effects and domestic market dynamics in the context of portfolio management and risk assessment strategies. Further, from the extended results of variance decomposition analysis, the authors find that Brazil’s, China’s and South African stock market returns have a significantly lagged impact on their own stock market, while Russia’s and India stock market returns do not have a significantly lagged impact on their own stock markets.

To the best of the authors’ knowledge, this is the first study comprehensively analyzing the BRICS indices downside risk through the historical simulation method of VaR estimation, which is an unexplored area of risk management.

The present study reviews the literature on the history and evolution of investment strategies in the stock market for the period from 1900 to 2022. Conflicts and relationships arising from such diverse seminal studies have been identified to address the research gaps.

The studies for this review were identified and screened from electronic databases to compile a comprehensive list of 200 relevant studies for inclusion in this review and summarized for the cognizance of researchers.

The study finds a coherence to complex theoretical documentation of more than a century of evolution on investment strategy in stock markets, capturing the characteristics of time with a chronological study of events.

There were complications in locating unpublished studies leading to biases like publication bias, the reluctance of editors to publish studies, which do not reveal statistically significant differences, and English language bias.

Practitioners can refine investment strategies by incorporating behavioral finance insights and recognizing the influence of psychological biases. Strategies span value, growth, contrarian, or momentum indicators. Mitigating overconfidence bias supports effective risk management. Social media sentiment analysis facilitates real-time decision-making. Adapting to evolving market liquidity curbs volatility risks. Identifying biases guides investor education initiatives.

This paper is an original attempt to pictorially depict the seminal works in stock market investment strategies of more than a hundred years.

This study aims to investigate the conditional volatility of the Asian stock market concerning Bitcoin and global crude oil price movement.

This study uses the newest Dynamic Conditional Correlation (DCC)-Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to examine the conditional volatility of the stock market for Bitcoin and crude oil prices in the Asian perspective. The sample stock market includes Chinese, Indian, Japanese, Malaysian, Pakistani, Singaporean, South Korean and Turkish stock exchanges, with daily time series data ranging from 4 April 2015−31 July 2023.

The outcome reveals the presence of volatility clustering on the return series of crude oil, Bitcoin and all selected stock exchanges of the current study. Secondly, the outcome of DCC, manifests that there is no short-run volatility spillover from crude oil to the Malaysian, Pakistani and South Korean and Turkish stock markets, whereas Chinese, Indian, Japanese, Singapore stock exchanges show the short-run volatility spillover from crude oil in the short run. On the other hand, in the long run, there is a volatility spillover effect from crude oil to all the stock exchanges. Thirdly, the findings suggest that there is no immediate spillover of volatility from Bitcoin to the stock markets return volatility of China, India, Malaysia, Pakistan, South Korea and Singapore. In contrast, both the Japanese and Turkish stock exchanges exhibit a short-term volatility spillover from Bitcoin. In the long term, a volatility spillover effect from Bitcoin is observed in all stock exchanges except for Malaysia. Lastly, based on the outcome of conditional variance, it can be concluded that there was increase in the return volatility of stock exchanges during the period of the COVID-19 pandemic.

The analysis below does not account for the bias induced due to certain small sample properties of DCC-GARCH model. There exists a huge literature that suggests other methodologies for small sample corrections such as the DCC connectedness approach. On the other hand, decisive corollaries of the conclusions drawn above have been made purely based on a comprehensive investigation of eight Asian stock exchange economies. However, there is scope for inclusive examination by considering other Nordic and Western financial markets with panel data approach to get more robust inferences about the reality.

Most of the empirical analysis in this perspective skewed towards the Nordic and Western countries. In addition to that many empirical investigations examine either the impact of crude oil price movement or Bitcoin performance on the stock market return volatility. However, none of the examinations quests the crude oil and Bitcoin together to unearth their implication on the stock market return volatility in a single study, especially in the Asian context. Hence, current investigation endeavours to examine the ramifications of Bitcoin and crude oil price movement on the stock market return volatility from an Asian perspective, which has significant implications for the investors of the Asian financial market.