Gold Volatility Research Articles

Dynamic co-movement in major commodity markets during crisis periods: A wavelet local multiple correlation analysis

We study time-scale co-movement of returns and implied volatilities of oil, gold, wheat, and copper in a multivariate setting using the wavelet local multiple correlation (WLMC) approach. Daily data cover January 03, 2007 – August 08, 2022, including the global financial crisis, COVID-19 pandemic, and Russia-Ukraine war. The results show that the correlations across the commodities are heterogeneous, less stable in the short-term, and more pronounced in the long-term, and vary in sign and magnitude. Despite market instability, contagion is not clearly seen in either return or volatility, reflecting noise trading and the importance of the individual characteristics of commodities.

Impact of geopolitical risk on the volatility of natural resource commodity futures prices in China

Volatile natural resource prices greatly affect economic growth, economic volatility, and financial market. Analyzing the factors affecting price volatility is of great significance for policymakers to formulate regulations, for financial institutions to control financial risks and for investors to improve their investment returns. We study the impact of geopolitical risk on the price volatility of coal, copper, crude oil, gold, and iron ore in the Chinese futures market. The paper uses the Geopolitical Risk (GPR) index, the Geopolitical Threat (GPT) sub-index and the Geopolitical Action (GPA) sub-index developed by Caldara and Iacoviello to measure geopolitical risk in broader sense. We utilize the closing prices of the most recently expired futures contracts from their starting trading date to 1 August 2022 to determine volatility represented by conditional variance. The GARCH and CGARCH models are built with the help of the Kalman filtering method and a TVP-VAR-SV model. The results of GARCH model show that geopolitical risk significantly increases the price volatility of coal, iron ore, and crude oil futures; significantly decreases the price volatility of gold; and has no significant effect on the price volatility of copper futures. By CGARCH model, we illustrate that geopolitical risk significantly increases the overall volatility, persistent volatility, and temporary volatility of crude oil; significantly increases the overall volatility and temporary volatility of coal and iron ore futures; significantly decreases the overall volatility and persistent volatility of gold futures; and has no significant impact on all three types of volatility of copper futures prices. The results of the Kalman filter analysis uncover that the response of each commodity volatility to changes in geopolitical risk increases when geopolitical risk is high. Additionally, geopolitical risk has the most effect on the price volatility of copper and crude oil with high external dependence. Estimates from the TVP-VAR-SV model reveal that the short-term impact of geopolitical risk shocks on the volatility of each the futures prices of each commodity is large and of long duration, and the response of commodity futures volatility to the same level of geopolitical risk shocks is higher and longer when major geopolitical events occur such as Paris Terrorist Attack, USA/Iran Tension Escalation, Syria Missile Attack, and Russian-Ukraine War. Moreover, geopolitical shocks have the most effect on the energy commodities of crude oil and coal.

Asymmetric volatility spillover among global oil, gold, and Chinese sectors in the presence of major emergencies

The volatility of international crude oil and gold markets has affected stock markets through several economic channels, and the impact tends to be more evident with the appearance of emergencies. However, the volatility linkages between commodities and Chinese sector stocks in the presence of emergencies are understudied. To examine the asymmetric relationship and time-varying connectedness between commodities and Chinese sector stocks, this paper first employs GJR-GARCH to capture the realized volatility of international oil, gold, and Chinese sector stocks. Secondly, we decompose the realized volatility of international oil and gold into bad and good volatility and then employ the TVP-VAR-DY approach to obtain the connectedness index. The final result shows asymmetric volatility spillover among oil, gold, and Chinese sector stocks. During the COVID-19 outbreak, the gold good volatility transmission is intenser than bad volatility. Thirdly, the analysis is also carried out under different subperiods. They include three international events: the global financial crisis and the European debt crisis, the oil crisis, and COVID-19. The result reveals heterogeneity exists in the impact of international oil and gold on the Chinese sector stocks under different emergencies. These findings are of great significance for policymakers to improve the sector management under the impact of different emergencies and for investors to design diversified portfolios according to the commodity-sector risk spillover effects.

Can COVID-19 deaths and confirmed cases predict the uncertainty indexes? A multiscale analysis

Purpose This study aims to examine the multiscale predictability power of COVID-19 deaths and confirmed cases on the S&P 500 index (USA), CAC30 index (France), BSE index (India), two strategic commodity futures (West Texas intermediate [WTI] crude oil and Gold) and five main uncertainty indices Equity Market Volatility Ticker (EMV), CBOE Volatility Index (VIX), US Economic Policy Uncertainty (EPU), CBOE Crude Oil Volatility Index (OVX) and CBOE ETF Gold Volatility Index (GVZ). Furthermore, the authors analyze the impact of uncertainty indices and COVID-19 deaths and confirmed cases on the price returns of stocks (S&P500, CAC300 and BSE), crude oil and gold. Design/methodology/approach The authors used the wavelet coherency method and quantile regression approach to achieve the objectives. Findings The results show strong multiscale comovements between the variables under investigation. Lead-lag relationships vary across frequencies. Finally, COVID-19 news is a powerful predictor of the uncertainty indices at intermediate (4–16 days) and low (32–64 days) frequencies for EPU and at low frequency for EMV, VIX, OVX and GVZ indices from January to April 2020. The S&P500, CAC30 and BSE indexes and gold prices comove with COVID-19 news at low frequencies during the sample period. By contrast, COVID-19 news and WTI oil moderately correlated at low frequencies. Finally, the returns on equity and commodity assets are influenced by uncertainty indices and are sensitive to market conditions. Originality/value This study contributes to the literature by exploring the time and frequency dependence between COVID-19 news (confirmed and death cases) on the returns of financial and commodity markets and uncertainty indexes. The findings can assist market participants and policymakers in considering the predictability of future prices and uncertainty over time and across frequencies when setting up regulations that aim to enhance market efficiency.

Obtaining green environmental revival through natural resources price variations: Estimations through GARCH technique.

The study aims to determine how price fluctuations in metallic resource supplies impact China's environmental performance. Thisresearch evaluates the impact of the price volatility of nickel, aluminum, gold, and aluminum on environmental performance in China from 2001 to 2019 to provide an answer to this topic. By examining the robustness of outcomes, the conventional DCC-GARCH approach clarifies the study findings and offers wide policy implications for the most recent topicality CS-ARDL. According to the study, the fluctuation in metal prices significantly influences the nation's GDP. The research's findings show that over the sample period, the price volatility of metallic resources was 23%, and this shift implied a 17.24% change in environmental performance. The findings of the study so ensure that every effort will be made to prevent environmental instability by supporting financial resource volatility recovery via governmental agencies, environmental ministries, and departments. The research has several policy implications, including the necessity for different government aid programs and financial agreements that guarantee environmental growth and resilience. The research's policy recommendations are intended to lessen the impact of structural events and increase environmental effectiveness. Research on financial resource recovery is dispersed and understudied despite the issue having a growing corpus of literature.

Uncovering risk transmission between socially responsible investments, alternative energy investments and the implied volatility of major commodities

The interconnectedness and high integration among the global markets have reduced the portfolio diversification opportunities of international investors. In view of this, considering the rise of Socially Responsible Investments (SRI) and the Clean-Renewable energy & Clean-Technology energy (C&RTE) asset classes, the objective of this research is to examine risk transmission and the portfolio diversification prospects across the SRI, C&RTE, and the implied volatility indices (VIX) of major commodities (oil, silver, and the gold). To uncover the spillover and the risk transmission, we employ the approach of Dynamic conditional correlation (DCC-GARCH) along with the Asymmetric DCC-GARCH and VAR-GARCH. The findings exhibit a strong ability of volatility indices to hedge risks associated with SRIs and C&RTE investments as asymmetric-GARCH confirms that volatility indices have a negative correlation with most of the socially responsible and clean energy and technology equity indices. The findings confirm that the implied volatility indices of gold and silver exhibit the best hedging tool against SRIs while oil is the best hedging tool for C&RTE. During Covid-19, generally oil price volatility index is positively correlated with SRI indices whereas the silver and the gold volatility indices are negatively correlated with the C&RTE. More importantly, we find that hedging effectiveness and risk diversification are facilitated by the adaptive behavior of commodities, confirmed by the Adaptive Market Hypothesis (AMH) through the Generalized Spectral (GS) test. Moreover, we also find some evidence of a time-varying pattern in the hedging ratio and the hedging effectiveness. Finally, we show utility gains from hedging to be positive irrespective of whether we consider transaction costs or not. The findings of the study could be helpful for portfolio managers, brokers, and market participants to draw the role of implied volatilities of commodities in hedging the risk associated with SRIs and C&RTE investments.

Climate risk and gold

In this paper, we examine the predictive content of both transition and physical risks for the volatility of gold return as well as the utility gains of observing these risks. Our results offer the following distinct contributions to the literature. One, we show that the return volatility of gold has a positively significant relationship with transition risk and a negatively significant relationship with physical risk. Given some salient features of gold, its safe-haven property, and its rarity in nature, our result appears very plausible. Two, we find evidence for out-of-sample predictability between the return volatility of gold and both transition and physical risks although with greater predictive prowess from the former. Lastly, we confirm that accounting for both transition and physical risks guarantees higher economic gains for a utility-maximizing investor that observes these risks in the gold market. We further demonstrate the robustness of our findings to multiple forecast horizons and alternative commodities.

Forecasting the volatility of precious metals prices with global economic policy uncertainty in pre and during the COVID-19 period: Novel evidence from the GARCH-MIDAS approach

Economic policy is a major determinant of investment and financial decisions; Moreover, prices of precious metals are highly influenced by any uncertainty recorded in the global economic policy. Therefore, the prime consideration of the authors is to assess how global economic policy uncertainty influences the volatility of precious metals prices; particularly “gold, palladium, platinum, and silver” in the pre and during the COVID-19 pandemic. This research analyzed the full sample period (the 1997–2022), pre-COVID period (1997–2019), and during the COVID period (2020−2022) to evaluate the impact during different sample periods. Therefore, the GARCH-MIDAS approach is employed at the data set of different frequencies, i.e., monthly data of GEPU and daily data of precious metals. The results reveal a significant nexus between global GEPU and precious metals price volatility. The findings infer that any uncertainty recorded in global economic policy escalate the price volatility of gold, palladium, platinum, and silver prices. The present study increments the existing literature and provides insights for future scholars, investors, and policymakers.

Performance Analysis of Gold- and Fiat-Backed Cryptocurrencies: Risk-Based Choice for a Portfolio

This study aims to investigate the performance and behavior of fiat- and gold-backed cryptocurrencies to support stakeholders through the preparation of a portfolio from 1 January 2021 to 30 June 2022. Moreover, while searching for a hedge or a diversifier to construct a less risky portfolio with handsome returns, the prices of fiat-backed cryptocurrencies report high fluctuation during the sample period. ARIMA-EGARCH models have been employed to examine the volatile behavior of these cryptocurrencies. The empirical results are mixed as Bitcoin has been highly volatile during the economic recession. Due to its volatility, investors seek a safe haven. Ripple, on the other hand, shows low risk compared to Bitcoin. The results further reveal that PAX gold is more volatile than PM gold, while Bitcoin, being a highly traded cryptocurrency, is significantly correlated to other cryptocurrencies. The implications of this research showing the volatility of gold- and fiat-backed cryptocurrencies are equally important to stakeholders, such as investors, and policymakers.

Zakat Payment by Metal Backed Cryptocurrencies: Are They Allowed?

This study aims to provide a scientific contribution to the feasibility of metal backed cryptocurrencies as a medium of exchange to pay zakat. To understand the dynamics and mechanisms of metal backed cryptocurrencies, the autoregressive conditional heteroscedasticity and generalized conditional heteroscedasticity (Arch Garch) methods were used. The metal backed cryptocurrencies used for this research are Bitcoin Gold, GoldFinch, Gold Coin, Digix Gold Token, E-Dinar Coin, Gold-Money, and E-Gold. Our analysis finds that even though these are metal backed cryptocurrencies, the volatility is high. Gold-Money has a long-term volatility 67 times higher than the volatility of gold, while E-Gold has eight times the volatility of gold. As a result, due to high levels of volatility, metal backed cryptocurrencies are not suitable as a medium for zakat payment.

Forecasting gold volatility with geopolitical risk indices

This paper tries to forecast gold volatility with multiple country-specific (GPR) indices and compares the role of combined prediction models and dimension reduction methods regarding the improvement of gold volatility prediction accuracy. For this purpose, GARCH-MIDAS model’s several extensions are used. We find firstly that most country-specific GPR indices have driving effects on gold volatility, and it makes sense to take forecast information from multiple country-specific GPR indices into account when forecasting gold volatility. The out-of-sample empirical results also indicate that the dimension reduction methods yield better predictions compared to the combined prediction models. In addition, dimension reduction technologies have excellent forecasting performance mainly during low gold volatility periods. Finally, our empirical findings are robust after changing the evaluation method, model settings, in-sample length and gold market.

The interconnectedness across risk appetite of distinct investor types in Borsa Istanbul

Purpose This study aims to investigate the interconnectedness across the risk appetite of distinct investor types in Borsa Istanbul. This study also examines the causal impact of global implied volatility indices on the risk appetite of these investor groups. Design/methodology/approach The authors use a novel time-varying frequency connectedness framework of Chatziantoniou et al. and a new time-varying Granger causality test with a recursive evolving procedure by Shi et al. over June 2008 and July 2022. Findings The results show a high level of interconnectedness across the risk appetite of different investor types. The sizable spillovers to domestic types of investors either occur from professional or foreign investors, indicating the long-term dominant effect of foreign and more qualified investors on the domestic investors in Borsa Istanbul. The authors provide significant evidence of causality from the global implied volatility to the Borsa Istanbul risk appetite indices, which are getting stronger after the COVID-19 outbreak. Originality/value Unlike the previous studies, the authors analyze the risk appetite sub-indices of various types of investors to reveal behavioral distinctions and interconnectedness across them. The authors use a novel econometric framework to assess investors’ risk appetite in different investment horizons in a time-varying system. Together with volatility index (VIX), the authors also use volatilities of oil (OVX), gold (GVZ) and currency (EVZ), considering the information transmission not only from stock markets but also energy, metals and currency markets. The present data set covers significant financial crises, socioeconomic events and the COVID-19 outbreak.

Mathematical processing of trading strategy based on long short-term memory neural network model.

At present, gold and bitcoin have become mainstream assets in market transactions. Due to the volatility of gold and bitcoin prices, we can buy and sell assets like gold and bitcoin the same way we buy and sell stocks. The research goal of this article is to develop an optimal trading strategy that maximizes our post-trade returns. By studying the relationship between the two, on the one hand, it supplements and enriches the theoretical research on the rate of return of gold and Bitcoin, on the other hand, it provides a certain reference for investors to construct investment strategies. The research on the cointegration relationship between them has important practical significance. At the same time, it has important practical significance for the research on the cointegration relationship between bitcoin and gold.

Covid-19 and oil and gold price volatilities: Evidence from China market

Gold and crude oil are the influential commodities of the stock markets and real economy of the world in financial crises as well as in COVID-19 periods. However literature mainly focused on the effects of these commodities' prices only, and the volatilities in the prices of these commodities altogether with the prices got little attention. To fill in a major research gap, our study intends to estimate the dynamic relationship between oil prices, gold prices, oil prices volatilities and gold prices volatilities on the stock market of China. Using daily data over the period from 2009 to 2021, the study applied Autoregressive Distributed Lag (ARDL) bound test approach for the purpose of empirical estimation. Moreover, Non linear ARDL and asymmetric Causality analysis has also been applied for more comprehensive asymmetric estimation. The findings of our study indicated that gold prices and oil prices negatively affect stock market of China in the long run. In terms of implied volatility index of these commodities, study finds negative impact of price volatility of oil but positive impact of the price volatility of gold on the country's stock market in the long run. However, in the short run, only oil price and gold prices have significant effect on the China's stock market. On the basis of our findings, we recommend the investors to make rational decisions in response to the uncertainties in these markets and should consider gold as a safe haven to hedge themselves in times of uncertainty. Policymakers should take appropriate actions and adopt proper mechanisms for dealing with the quick uncertainty flow of information from the oil to the stock market.

Assessing the influence of news indicator on volatility of precious metals prices through GARCH-MIDAS model: A comparative study of pre and during COVID-19 period

The research aims to discover the influence of news indicator on the volatility of precious metals prices. It highlights an essential aspect by focusing on comparing pre and during COVID-19 period. For this purpose, an advanced econometric technique, i.e., Generalized Autoregressive Conditional Heteroskedasticity variant of Mixed Data Sampling (GARCH MIDAS), has been employed. The full sample results demonstrate that news relating to any of the precious metals is likely to affect their volatilities, except palladium. In the case of during the COVID-19 sample, the outcomes reveal that fear-induced news raises the return volatilities of gold and palladium; thereby, both are highly sensitive to the recent pandemic. In contrast, silver and platinum are found to have less impact.

A Comparative Analysis on the Role and Market Linkages of Gold Backed Assets During COVID-19 Pandemic

Gold is a traditional favorite investment avenue for investors all over the globe, particularly during the crisis period. Irrespective of the nature of the crisis, investors are allocating their funds to different gold-backed assets. This paper uses various globally traded gold-backed assets to identify its role and market linkages during the Covid 19 pandemic. Daily prices of assets from March 2020 to January 2022 were employed. DCC GARCH model is used to ascertain time-varying correlations and quantile regression was employed to examine the relationship between assets in different quantiles. Based on the analysis, safe haven property of all the assets is revealed and it is associated with the severity of the stock market crash as specified by the quantiles. Moreover, double exposure of gold mining stock results in different flights to quality. Co-movement of gold bullion, gold futures, and gold volatility index is visible during this crisis. Gold Exchange Traded Funds and gold-backed cryptocurrency offer diversification by decoupling with gold bullion in the portfolio. The paper highlights the importance of the choice of gold-backed assets along with gold bullion in the investment portfolio based on its role and market linkages.

Volatility spillover effects of oil, gold and bulk shipping prices on financial markets

Abstract The volatility spillover effect plays an increasingly important role in the transmission of shocks mainly in recent periods, with the further advance of globalization and the rapid development in international linkages. This analysis of the interconnections between economic and financial markets has particular importance for investors in risk hedging strategies and portfolio diversification. Moreover, current turbulent periods, characterized by a volatile oil price, instability of gold price and supply bottlenecks caused by the outbreak of the COVID-19 pandemic impose the necessity to study this effect. The novelty brought by this paper is related to the analysis of the spillover effect coming from oil, commodity and bulk shipping markets to financial markets of Eastern-Europe emerging markets, namely Czech Republic, Hungary, Poland and Romania. To assess this effect, in this study it was implemented a widely used model in research papers model, more exactly the bivariate GARCH-BEKK (1,1) from the period July 2012 – February 2022. The results suggest the long-term memory of volatility in these markets, while direct interconnection and unidirectional spillovers effects are expected to be underlined by the volatility of gold returns on the stock markets returns.

Dynamic connectedness between COVID-19 news sentiment, capital and commodity markets

ABSTRACT This study investigates the dynamic transmission mechanism between COVID-19 news sentiment (Google Trends Index), and S&P100, crude oil and gold volatility indices using the recently developed time-varying parameter vector autoregressive (TVP-VAR)-based extended joint connectedness approach. This framework corrects for the Generalized Forecast Error Variance Decomposition (GFEVD) normalization problem. The obtained empirical results suggest that dynamic total connectedness is heterogeneous over time and severely affected by COVID-19. More importantly, we identify COVID-19 news sentiment to be the main driver of spillover shocks indicating that it is indeed an important predictor of the volatility indices employed in our study. Thus, our findings have important implications for policymakers, private investors, as well as for portfolios and risk managers.

Research on the Influence of Whether Rebalance Model on Quantitative Trading Investment Strategy Based on BEKK-MGARCH and Multi-Factor Model

The quantitative strategy of asset pricing risk management is one of the financial theory research hot spots. In this paper, we use the BEKK-GARCH model based on the relative economic theory to predict the daily volatility of gold and bitcoin; Secondly, we establish a multi-factor model with 16 factors to predict the return rate of the two assets; Finally, we establish WR model to determine the optimal position proportion of investors every day. In building the model, we use the data in the previous period to continuously slide and train our model to prevent future information leakage. In data processing, we choose the base point (0.01%) as the measurement unit, and the missing value is filled in by the average of the data of two days before and after it.

Precious Metals Price Forecast with ARCH Family Models in COVID-19 Pandemic Period

The COVID-19 virus, which was detected for the first time in Wuhan, China in December 2019, spread to all countries of the world and, therefore, became a global epidemic. Although more than two years have passed since the outbreak of the COVID-19 pandemic, the economic effects of it continue. One of these is the effect of the pandemic on precious metal prices. Precious metals, which are called safe harbours and used as investment tools, have had a serious volatility in the last century as a result of the economic, political and pandemic factors changing the international balances. From this point of view, in this study, it is aimed to determine the appropriate forecasting model to predict the volatility of gold, silver, platinum and palladium prices, which are called precious metals, during the COVID-19 pandemic period. The econometric analysis covers the period between March 11, 2020, when the global epidemic was declared by the World Health Organization, and September 13, 2021, and includes 326 days of observation. To determine the appropriate forecasting model, ARCH, GARCH, T-GARCH, E-GARCH and PARCH are used as symmetrical and asymmetrical volatility models.