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KRX (Korea Exchange) gold market opened in March 2014 according to the government policy legalizing financial transactions, and traded one-gram unit of the real gold by Korean currency (KRW) in the exchange market. Despite the fact that KRX gold market showed the high efficiency in terms of tax and fee in contrast to the existing gold market, the studies on KRX gold market were scarcely performed until quite recently. This study introduce KRX gold market and shows the price discovery function of KRX gold market. Empirical analyses and the results were as follows. First, the return rate of CME gold futures at the t-1 day had a positive impact of significance on market rate of return of KRX gold market at the t day. Second, the KRX gold market also has price discovery function in global gold market. We analyze the efficiency of the KRX gold market by comparing the dollar spot price of gold in the KRX gold market and the price of CME gold futures. These results support the proper efficiency of the KRX gold market in terms of price discovery.

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.

Using a GED-GARCH model to estimate monthly data from January 1990 to February 2022, we test whether gold acts as a hedge or safe haven asset in 10 countries. With a downturn of the stock market, gold can be viewed as a hedge and safe haven asset in the G7 countries. In the case of inflation, gold acts as a hedge and safe haven asset in the United States, United Kingdom, Canada, China, and Indonesia. For currency depreciation, oil price shock, economic policy uncertainty, and US volatility spillover, evidence finds that gold acts as a hedge and safe haven for all countries.

The purpose of this study is to explore the intricate relationship between oil prices, house prices in the UK and Norway, and the mediating role of gold and stock prices in both the short- and long-term, unraveling these complex linkages by employing an empirical approach.

This study benefits from a comprehensive set of econometric tools, including a multiequation vector autoregressive (VAR) system, Granger causality test, impulse response function, variance decomposition and a single-equation autoregressive distributed lag (ARDL) system. This rigorous approach enables to identify both short- and long-run dynamics to unravel the intricate linkages between Brent oil prices, housing prices, gold prices and stock prices in the UK and Norway over the period from 2005:Q1 to 2022:Q2.

The findings indicate that rising oil prices negatively impact house prices, whereas the positive influence of stock market performance on housing is more pronounced. A two-way causal relationship exists between stock market indices and house prices, whereas a one-way causal relationship exists from crude oil prices to house prices in both countries. The VAR model reveals that past housing prices, stock market indices in each country and Brent oil prices are the primary determinants of current housing prices. The single-equation ARDL results for housing prices demonstrate the existence of a long-run cointegrating relationship between real estate and stock prices. The variance decomposition analysis indicates that oil prices have a more pronounced impact on housing prices compared with stock prices. The findings reveal that shocks in stock markets have a greater influence on housing market prices than those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

This study may have several limitations. First, the model does not include all relevant macroeconomic variables, such as interest rates, unemployment rates and gross domestic product growth. This omission may affect the accuracy of the model’s predictions and lead to inefficiencies in the real estate market. Second, this study does not consider alternative explanations for market inefficiencies, such as behavioral finance factors, information asymmetry or market microstructure effects. Third, the models have limitations in revealing how predictors react to positive and negative shocks. Therefore, the results of this study should be interpreted with caution.

These findings hold significant implications for formulating dynamic policies aimed at stabilizing the housing markets of these two oil-producing nations. The practical implications of this study extend to academics, investors and policymakers, particularly in light of the volatility characterizing both housing and commodity markets. The findings reveal that shocks in stock markets have a more profound impact on housing market prices compared with those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

These findings could also serve as valuable insights for future research endeavors aimed at constructing models that link real estate market dynamics to macroeconomic indicators.

Using a variety of econometric approaches, this paper presents an innovative empirical analysis of the intricate relationship between euro property prices, stock prices, gold prices and oil prices in the UK and Norway from 2005:Q1 to 2022:Q2. Expanding upon the existing literature on housing market price determinants, this study delves into the role of gold and oil prices, considering their impact on industrial production and overall economic growth. This paper provides valuable policy insights for effectively managing the impact of oil price shocks on the housing market.

This study analyzes the static and dynamic risk spillover between US/Chinese stock markets, cryptocurrencies and gold using daily data from August 24, 2018, to January 29, 2021. This study provides practical policy implications for investors and portfolio managers.

The authors use the Diebold and Yilmaz (2012) spillover indices based on the forecast error variance decomposition from vector autoregression framework. This approach allows the authors to examine both return and volatility spillover before and after the COVID-19 pandemic crisis. First, the authors used a static analysis to calculate the return and volatility spillover indices. Second, the authors make a dynamic analysis based on the 30-day moving window spillover index estimation.

Generally, results show evidence of significant spillovers between markets, particularly during the COVID-19 pandemic. In addition, cryptocurrencies and gold markets are net receivers of risk. This study provides also practical policy implications for investors and portfolio managers. The reached findings suggest that the mix of Bitcoin (or Ethereum), gold and equities could offer diversification opportunities for US and Chinese investors. Gold, Bitcoin and Ethereum can be considered as safe havens or as hedging instruments during the COVID-19 crisis. In contrast, Stablecoins (Tether and TrueUSD) do not offer hedging opportunities for US and Chinese investors.

The paper's empirical contribution lies in examining both return and volatility spillover between the US and Chinese stock market indices, gold and cryptocurrencies before and after the COVID-19 pandemic crisis. This contribution goes a long way in helping investors to identify optimal diversification and hedging strategies during a crisis.

The purpose of this study is to present evidence as to whether the use of gold or silver can be justified as an asset to hedge against policy uncertainty and COVID-19 in the Chinese market.

By using a GARCH model with a generalized error distribution (GED), this study specifies that the gold (or silver) return is a function of a set of economic and uncertainty variables, which include volatility from interest rate innovation, a change in economic policy uncertainty (EPU), a change in geopolitical risk (GPR) and volatility due to pandemic diseases, while controlling for stock market returns, inflation rates, economic growth and the Chinese currency value.

This study employs monthly data of gold and silver prices over the period from January 2002 to August 2021 to examine hedging behavior. Estimated results show that the gold return is positively correlated to the stock return and a rise in uncertainty from economic policy innovation, geopolitical risk, volatility due to US interest rate innovation as well as COVID-19 infection. This result suggests that gold cannot be used to hedge against a stock market decline, but can be used to hedge against uncertainty in general. However, the silver return only responds positively to a rise in uncertainty from the inflation rate and geopolitical risk. Evidence shows that silver returns are negatively correlated with stock returns, and display hedging characteristics. However, the evidence lacks statistically significance during the COVID-19 period, suggesting that the role of silver as a safe-haven asset against stock market turmoil is weak for this time period.

More general nonlinear specifications can be developed. The tests may include different measures of uncertainty that interact with each other or with the lagged error terms. An implication of the model is that gold can be used to hedge against a broad range of uncertainties for economic policy change, political risk and/or a pandemic. However, the use of gold as an asset to hedge against a stock downturn in Chinese market should be done with caution.

This study has important policy implications as regards a choice in assets in formatting a portfolio to hedge against uncertainty. Specifically, this study presents empirical evidence on gold and silver return behavior and finds that gold returns respond positively to heightened uncertainty. Thus, gold is a good asset to hedge against uncertainty arising from policy innovations and infectious disease uncertainty.

This paper provides insightful information on the choice of assets toward hedging against risk in the uncertainty market conditions. It provides information to investors and policy makers to use gold price movements as a signal for detecting the arrival of uncertainty. This study also provides information for demanding a risk premium for infectious disease.

This study empirically analyzes and verifies the role that gold serves as a safe haven asset to hedge against uncertainty in the Chinese market. This paper contributes to the literature by presenting evidence of risk/uncertainty premiums for holding gold against various sources of uncertainty such as economic policy uncertainty, geopolitical risk and equity market volatility due to US interest rate innovation and/or COVID-19. This study finds evidence that supports the use of a nonlinear specification, which demonstrates the interaction of uncertainty with the lagged change of infectious disease and helps to explain the gold/silver return behavior. Further, evidence shows that the gold return is positively correlated to the stock return. This finding contrasts with evidence in the US market. However, silver returns are negatively correlated with stock returns, but this correlation becomes insignificant during the period of COVID-19.

Considering the unique data of the gold investor sentiment index in Thailand, the purpose of this paper is to investigate the bivariate dynamic relationship between the gold investor sentiment index and stock market return, as well as that between the gold investor sentiment index and stock market volatility, using the panel vector autoregression (PVAR) methodology. The author presents and discusses the findings both for the full sample and at the industry level. The results support prior literature that stocks in different industries do not react similarly to investor sentiment.

The PVAR methodology with the GMM estimation is found to be superior to other static panel methodologies due to considering both unobservable time-invariant and time-variant factors, as well as being suitable for relatively short time periods. The panel data approach improves the statistical power of the tests and ensures more reliable results.

In general, a negative and unidirectional association from gold investor sentiment to stock returns is observed. However, the gold sentiment-stock realized volatility relationship is negative and bidirectional, and there exists a greater impact of a stock’s realized volatility on gold investor sentiment. Importantly, evidence at the industry level is stronger than that at the aggregate level in both return and volatility cases, confirming the role of gold investor sentiment in the Thai stock market. The capital flow effect and the contagion effect explain the gold sentiment-stock return relationship and the gold sentiment-stock volatility relationship, respectively.

The gold price sentiment index can be used as a factor for stock return predictability and stock realized volatility predictability in the Thai equity market.

Practitioners and traders can employ the gold price sentiment index to make a profit in the stock market in Thailand.

This is the first paper to use panel data to investigate the relationships between the gold investor sentiment and stock returns and between the gold investor sentiment and stocks’ realized volatility, respectively.

This paper investigates the causality among gold prices, crude oil prices, bitcoin and stock prices by using daily data from January 2014 to December 2021. The study also examines the data during the COVID-19 outbreak from January 2020 to December 2021.

To estimate the long- and short-run causality, this study considers the nonlinear autoregressive distributed lag (NARDL) cointegration test.

The analysis found the existence of an asymmetric long-run cointegration among selected assets. Findings indicate that positive changes in bitcoin do not affect stock market in the long term. Changes in crude oil prices have a significant impact on stock prices. Moreover, it is observed that variations in the stock prices trigger a negative impact on gold prices. During the COVID-19 period, the study notices the presence of an asymmetric long-term cointegration between selected assets except bitcoin. Besides, findings revealed that negative price adjustments in gold lead to significant positive shocks in stock market.

These results provide critical information for policy performers and researchers to develop new strategies. Policy regulators can also consider the potential effects of the COVID-19 outbreak while developing strategies for investment decisions.

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.

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.

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.

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.

The purpose of the study is to find out the impact of gold and oil prices on the stock market.

This study uses the data on gold prices, stock exchange and oil prices for the period 1991–2016. This study applied descriptive statistics, augmented Dickey–Fuller test, correlation and autoregressive distributed lag test.

The data analysis results showed that gold and oil prices have a significant impact on the stock market.

Following empirical evidence of this study, the authors recommend that investors should invest in gold because the main reason is that hike in inflation reduces the real value of money, and people seek to invest in alternative investment avenues like gold to preserve the value of their assets and earn additional returns. This suggests that investment in gold can be used as a tool to decline inflation pressure to a sustainable level. This study was restricted to use small sample data owing to the availability of data from 1991 to 2017 and could not use structural break unit root tests with two structural break and structural break cointegration approach, as these tests require high-frequency data set.

This study provides information to the investors who want to get the benefit of diversification by investing in gold, oil and stock market. In the current era, gold prices and oil prices are fluctuating day by day, and investors think that stock returns may or may not be affected by these fluctuations. This study is unique because it focusses on current issues and takes the current data in this research to help investment institutions or portfolio managers.