Gold Price Research Articles

Global impact of geopolitical oil price uncertainty and associated commodity prices on clean energy stocks

Theoretically, geopolitical risk and policy uncertainties can directly affect energy markets. Since fluctuations in it lead to cost the of clean energy sources as they compete with traditional energy. Regarding this, our study aims to scrutinize the impact of geopolitical oil price uncertainty on clean energy stocks by controlling the influences of economic policy uncertainty, gold, natural gas, and coal prices. For that purpose, the study utilized monthly data from July 2007 to September 2020 and employed a machine learning method, namely kernel-based regularized least squares approach. Empirical analysis reveals that geopolitical oil price uncertainty and coal prices have a nonlinear positive effect on clean energy stock prices. It is also found that the impact of global economic policy uncertainty, gold, and natural gas prices on clean energy stock prices is nonlinear and negative. The implication signifies that clean energy stock prices are hampered by economic policy uncertainty, and gold, and natural gas prices, thus hindering the development of clean energy sources. Similarly, for the robustness of the study, the quantile regression approach and findings reveal similar outcomes to that of the KRLS model. Based on these findings, policy implications that potentially aid renewable energy investments are put forward. The study also guides investors, financial advisors, and portfolio managers for better decision-making in consideration of uncertainties and associated fluctuations in energy markets and commodity prices.

The Bitcoin price and Bitcoin price uncertainty: Evidence of Bitcoin price volatility

AbstractThis study examines the Bitcoin price by taking into account global factors, including the Chicago Board Options Exchange's Market Volatility Index (VIX), the US dollar index, the gold price, the oil price, and Bitcoin price volatility. The analysis is conducted using the structural vector autoregression (SVAR) model. The variance decomposition findings revealed that the influence of the VIX on the Bitcoin price was initially restricted, but progressively intensified over time. Among the indicators, Bitcoin price volatility had the highest explanatory share in both daily and weekly data analysis. The impulse response functions demonstrated a statistically significant inverse relationship between the VIX and the Bitcoin price. Furthermore, the analysis revealed that the Bitcoin price was mostly impacted by its own volatility. This implies that investing in Bitcoin requires a certain level of risk‐taking.

Security issues of the gold industry chain based on smart blockchain in the context of the Internet of Things

The purpose is to solve the safety production and management problems of the gold Industrial Chain and give early warning of the safety situation of the gold Industrial Chain. According to the theory of industrial chain security governance and the basic situation of the gold Industrial Chain, this work establishes a gold Industrial Chain model based on smart blockchain and system dynamics (SD), and discusses the application of the gold Industrial Chain in the Internet of Things (IoT) environment. The overall goal of the application of IoT technology to the safety management of intelligent gold mines is to take the gold mine production demand as the driving force. The digitalization of production, electromechanical, safety, dispatching, and other information realizes intelligent digital perception, assists decision-making, guides the safety management of gold mining operations, continuously improves the operation efficiency of the gold mining industry, and drives the development of the industry. Finally, it takes the resource reserve of China’s gold industry from 2011 to 2021 as the research data introduces the weighting method to assess the security situation of China’s gold Industrial Chain from 2011 to 2021. The safety performance of China's environmental industry chain is evaluated through the detailed introduction of the basic information of the gold Industrial Chain. The result shows that the security situation of China’s gold Industrial Chain from 2011 to 2021 shows an overall growth trend, 88.42% higher than in 2014. The security situation of China’s gold Industrial Chain from 2011 to 2021 positively impacted the opening of the domestic gold market and entering the international gold market, improving the security level of China’s gold Industrial Chain. In this work, a gold Industrial Chain security model based on smart blockchain and SD is established to solve the safety problem of the gold Industrial Chain, which can improve the safety level of the gold industry and promote its sustainable development.

The Bricoleur Economy

This article uses the concept ‘Bricoleurs’ to analyse the different categories of indigenous small- scale miners in Zimbabwe. Indigenous citizens constitute the bulk of the small and medium scale gold miners who continue to use antiquated methods of extraction and processing and they market their gold through illegal networks managed by middlemen. The study highlights the challenges Bricoleurs encounter in forcing inclusion into the mainstream mining economy, and the government’s failure to capture them into the formal gold market. The indigenous gold miners’ experiences reveal the trials posed by fragmented and incoherent legal and institutional policy frameworks that militate against the Bricoleur miners’ productivity. With gold deposits found all over the country, and in the absence of supporting organisational structures, the Bricoleurs’ self-empowerment through devious means has become accepted by mining authorities. Data for this article was collected mostly through interviews with different stakeholders in the gold mining industry in Harare, Shurugwi and Chakari in Zimbabwe.

Forecasting the Nexus and Impact of News Sentiment on NYSE, Gold Prices, and WTI Oil Using The Neural Network Approach

The study aims to determine the impact of news sentiment during COVID-19 and the nexus between the NYSE, Gold prices, and WTI oil prices. For this purpose, we use hourly data of news sentiment and commodity prices hourly data from February 10, 2020, hours 1000 to March 06, 2020 hours 1600 hours, with the help of a multilayer artificial neural network. Further, We use the connection weight approach to observe the relative importance of input variables that help predict output variables. The results suggest that all the indexes are interconnected, where the increase/decrease of any index impacts the other commodity index. Further, the news index remains the second highest predictor for gold price and WTI oil price indexes. In addition, the news index also seems to be an essential predictor of these commodities.
 Keywords: NYSE, WTI Oil, Gold, Covid-19, Neural Network, Connection Weight

A hybrid econometrics and machine learning based modeling of realized volatility of natural gas

Determining which variables affect price realized volatility has always been challenging. This paper proposes to explain how financial assets influence realized volatility by developing an optimal day-to-day forecast. The methodological proposal is based on using the best econometric and machine learning models to forecast realized volatility. In particular, the best forecasting from heterogeneous autoregressive and long short-term memory models are used to determine the influence of the Standard and Poor’s 500 index, euro–US dollar exchange rate, price of gold, and price of Brent crude oil on the realized volatility of natural gas. These financial assets influenced the realized volatility of natural gas in 87.4% of the days analyzed; the euro–US dollar exchange rate was the primary financial asset and explained 40.1% of the influence. The results of the proposed daily analysis differed from those of the methodology used to study the entire period. The traditional model, which studies the entire period, cannot determine temporal effects, whereas the proposed methodology can. The proposed methodology allows us to distinguish the effects for each day, week, or month rather than averages for entire periods, with the flexibility to analyze different frequencies and periods. This methodological capability is key to analyzing influences and making decisions about realized volatility.

Asymmetric dynamics between cryptocurrency uncertainty and the oil and gold markets: evidence from Granger causality in quantiles

ABSTRACT This research examines the causal relationships between cryptocurrency uncertainty, the price of crude oil, and the price of gold using weekly data from 30 December 2013, to 21 February 2021, applying Granger-causality analysis on each quantile. Under this approach, we are able to distinguish between median and tail relationships for conditional quantiles. We find a bidirectional causal relationship between cryptocurrency uncertainty and crude oil prices, implying that crude oil price volatility is one source of cryptocurrency uncertainty, whereas a causal relationship from cryptocurrency uncertainty or crude oil prices to gold suggests that gold hedges cryptocurrency uncertainty and crude oil price shocks. Our research calls on governments to maintain cryptocurrency market stability to reduce market volatility in crude oil prices. Investors and fund managers can consider adding gold assets to portfolios that contain cryptocurrencies or crude oil in order to hedge against the risks of cryptocurrency uncertainty and crude oil price volatility.

Efektivitas Pemasaran Tabungan Emas dalam Meningkatkan Minat Berinvestasi Nasabah di Pegadaian Unit Pembantu Cabang Pemogan

Pegadaian Gold Savings is a gold balance depository service that facilitates public gold investment, as well as a gold savings product that makes gold investment simple, safe, affordable and reliable. The purpose of this service activity is to increase customer interest in investing in the UPC Pemogan Pawnshop. The method used is observation and evaluation. The results of this activity indicate that the marketing strategy for Gold Savings at UPC Pemogan Pawnshop uses a marketing mix strategy, namely product, price, location, and promotion. Promotions are used with brochures, personal selling, sales promotions by giving free administration fees, and advertisements on Pawnshop TV. The most effective promotion strategy is personal selling. The advice that the author can convey to Pegadaian UPC Pemogan is to provide special sales for Gold Savings products so that it is easier to market Gold Savings products.Â

Analisis Perbandingan Metode Peramalan Single Exponential Smoothing dan Double Exponential Smoothing pada Harga Pembukaan Harian XAU/IDR

The widespread availability of information in the digital age has made gold investment more accessible to a wider audience. In the Forex market, the world's largest foreign exchange market, gold is traded under the code XAU and is considered a major, stable commodity. Despite the ease of gold investment, fluctuating gold prices pose a significant challenge, making price prediction difficult. This research employs Single Exponential Smoothing and Double Exponential Smoothing methods to determine the most optimal forecasting approach based on the lowest Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) values. The study also utilizes Solver for parameter optimization to achieve the most optimal MAPE and RMSE values. Findings indicate that Single Exponential Smoothing is more optimal for gold price prediction, with a MAPE value of 0.63% and an RMSE value of 2518.38604

The relationship between cryptocurrencies and convention financial market: Dynamic causality test and time-varying influence

This paper examines the dynamic causal effect of financial markets on cryptocurrencies from a return perspective by applying the dynamic asymmetric causality tests. Applying daily data from February 1, 2018, to August 31, 2023, this paper also investigates whether the major events, such as COVID-19 or the categories of cryptocurrency, will alter or intensify the existing relationship. The empirical result shows that the causal relationship for both symmetric and asymmetric, between traditional financial markets and cryptocurrency is cyclical and only significant in the short term; such a result is robust with the examination of the VAR-based Granger causality test in the presence of instabilities. The pandemic does not influence the causal relationship, and the gold price had the most significant causal impact on cryptocurrency portfolio returns, while the fluctuations in the stock market had a negligible influence and the two indices did not have different causal impacts on the different types of cryptocurrencies. Adding cryptocurrencies to portfolios with only traditional financial assets can significantly reduce risk.

The Linkage Between International Gold Price and Chinese Stock market

Based on the related theory of stock market linkage, this paper uses the Copula model to analyze the correlation between international gold market and the Chinese stock market. The three important nodes of the process of financial and economic internationalization in China are analyzed in stages. According to the results, the correlation between the international gold market and the Chinese stock market is weak in general, when China does not join the WTO, the Chinese stock market and the international gold market are asymptotically independent; with the gradual deepening of China's internationalization process, the tail correlation between the two is gradually increasing.

Research on Gold Price Changes and Factors Under the Background of Fed Interest Rate Hike

With the change of international form, the gold market is changing rapidly. In 2021, the U.S. stagflation was serious, so in 2022, the Federal Reserve adopted a series of interest rate hikes, coupled with the impact of the conflict between Russia and Ukraine. As a safe haven product, the price of gold fluctuated greatly in the short term. As an important commodity, gold is crucial to judge its price change trend. This paper mainly analyzes the U.S. monetary policy from 2022 to 2023. By studying the reasons and background of the promulgation of monetary policy, it judges the causes of the Federal Reserve's interest rate increase, and judges the background of joint inflation and regional conflict according to the international form in 2022. Combined with the change trend of gold price, it makes a joint analysis, and gets the impact trend of the Federal Reserve's interest rate increase on gold price from 2022 to 2023. Finally, it comes to the conclusion that the increase of interest rate will lead to the decline of gold price. In the early stage of interest rate increase and a large number of interest rate increases, the gold price is more affected by the increase of interest rate, so it is suitable to short gold at this time, while in the late stage of interest rate increase and the slowdown of interest rate increase policy, the gold price is more affected by other factors, so it is suitable to long gold at this time.

A Comparison of Home Purchase and Liquid Lazy Portfolio Returns in Turkey

This study presents a comprehensive comparison between the effectiveness of home purchase and liquid Lazy portfolio strategies for generating historical returns in the Turkish market. The primary aim is to develop a liquid Lazy portfolio that outperforms residential property investments. The study covers the period from January 2010 to June 2023, focusing on high-liquidity assets including the Borsa Istanbul 100 Index, currency exchange rates, gold prices, real estate investment trusts, and major stock market indices. Methodologically, the research involves data pre-processing, logarithmic transformations, and cumulative time series creation. Portfolio optimization centers around maximizing the Sharpe ratio with three test portfolios developed. Findings indicate that all portfolios consistently outperform the benchmark Residential Property Price Index, displaying higher returns and Sharpe ratios despite increased volatility. These insights are relevant for both academic researchers and investors seeking practical applications for portfolio management. It's important to note that historical performance offers insights but not future guarantees. In conclusion, the study highlights the potential benefits of constructing scalable, liquid, and high-return Lazy portfolios as alternatives to traditional home purchases

The Effects of Macroeconomic Variables on the BIST 100 Index: ARDL and NARDL Approaches

The objective of this research is to analyse the signal, magnitude, and significance of both symmetric and asymmetric effects of interest rate, taxes, exchange rate, oil price, and gold price on the Turkish stock market (BIST100). The autoregressive distributed lag (ARDL) technique was used in both linear and non-linear formats. The F-Bounds test of the linear ARDL test suggests that the variables do not exhibit long-term integration. Nevertheless, the F-bounds test of the nonlinear ARDL (NARDL) test confirms the presence of cointegration among the variables. Therefore, the research heavily relies on the NARDL model. The empirical evidence indicates the long-term influence of the exchange rates rate, gold price, and interest rate on the BIST100 index is asymmetric. Additionally, the asymmetrical effects of interest rates, taxes, exchange rates, oil prices, and gold prices in the short term have an impact on the BIST100.

Behavioral Finance In The Context Of India's Gold Market

Rationale: The primary goal of this paper is to assess gold investor activity in terms of gold demand generators, rationale for gold purchases, and the motives of gold buying. 
 Research Design: The research was created using a combination of secondary data analysis and a large primary survey with a sample of 600 gold investors’ selected by using convenience sampling technique and tried to take opinions through online questionnaire. Finally, 449 investors responded after a prolonged persuasion and efforts.
 Findings: According to the survey, Indian households purchase gold for a variety of purposes, despite the fact that gold is regarded as a key cost in both good and bad times. India’s people desire to invest in gold to protect themselves against market volatility and uncertainty.
 This survey reveals that uncertainty is the most significant aspect to consider when it comes to the impact of stock market circumstances on gold. Factors such as income tax, retail investors' decision-making is influenced by the intrinsic worth of properties, future opportunities, and profitability, and gold is the most sought-after commodity due to its high liquidity, conventional value, and cultural value features.

The nexus between the volatility of Bitcoin, gold, and American stock markets during the COVID-19 pandemic: evidence from VAR-DCC-EGARCH and ANN models

The spread of the coronavirus has reduced the value of stock indexes, depressed energy and metals commodities prices including oil, and caused instability in financial markets around the world. Due to this situation, investors should consider investing in more secure assets, such as real estate property, cash, gold, and crypto assets. In recent years, among secure assets, cryptoassets are gaining more attention than traditional investments. This study compares the Bitcoin market, the gold market, and American stock indexes (S&P500, Nasdaq, and Dow Jones) before and during the COVID-19 pandemic. For this purpose, the dynamic conditional correlation exponential generalized autoregressive conditional heteroskedasticity model was used to estimate the DCC coefficient and compare this model with the artificial neural network approach to predict volatility of these markets. Our empirical findings showed a substantial dynamic conditional correlation between Bitcoin, gold, and stock markets. In particular, we observed that Bitcoin offered better diversification opportunities to reduce risks in key stock markets during the COVID-19 period. This paper provides practical impacts on risk management and portfolio diversification.

Comparative Analysis of the Volatility Structures of the Stock Prices of Energy Companies Traded on the Kazakhstan Stock Exchange and International Gold and Oil Prices

The return of its stock exchange and the companies traded within are one of the important indicators for a national economy. Due to the global structure of stock markets, returns are closely related to both national and international market variables. This study makes a comparative analysis of the volatility structures of the energy companies traded in the Kazakhstan Stock Exchange (KASE) and the combined stock market index and gold and oil prices in international markets for the period between January 01, 2021, and June 31, 2023. The research focused on two issues. The first is the analysis of the volatility structure of the six series examined. For this purpose, four different models were examined. The second focus is to determine whether the returns in international indices have a causal effect on the Kazakhstan stock market (composite stock market index) and the returns of oil and energy companies traded in the stock market. The results revealed that other indices and returns have a similar variable variance structure, except for the KASE. The relevant coefficient estimation was found to be significant in both conditional standard deviation models for the KASE index. The coefficient estimate of the GARCH-M(1,1) model in the OIL index was significant, whereas conditional standard deviation models and the relevant coefficients of both conditional standard deviation models were found to be statistically insignificant in the other returns. This is an indication of the structural compatibility of Kazakhstan's stock market composite index and energy and oil companies with international markets. Furthermore, the causality analysis results showing that international indices have a causal effect on KASE and KZAP is another indicator that the Kazakhstan market works in harmony with the international markets.

The potency of time series outliers in volatile models: An empirical analysis of fintech, and mineral resources

Understanding the importance of sustainability, the increasing ecological concerns need resource management under the cumulative mineral dependency. In this vein, prices of financial technology and mineral resources influence environmental sustainability; hence, sudden price variations must be evaluated carefully. For this, detecting outliers in financial and economic variables is gaining attention as economies are regionally integrated and influenced by external factors. Such peripheral events highly influence the statistical properties of model parameters and error distributions. In this vein, the current study proposed the method of outlier detection in various time series volatile models by extending the procedure of Frances and Ghijselse (1999) based on the framework of Chen and Liu (1993). The method is based on three phases: First, the outliers are detected, then the outliers are removed and estimated using the linear interpolation method, and third, the data values are forecasted by re-estimating the model with a corrected series. Forecasting accuracy has also been compared with and without outlier series to observe the impact of outlier presence in the series. For empirical analysis, the S&P Kensho Democratized Banking Index (USD), S&P 500 Environmental and Socially Responsible Index, and Gold price per Troy Ounce from July 15, 2013, to July 14, 2023. The outcomes retrieved from the proposed method suggest that the error distribution of volatile models is affected by outliers and manifestly forecasting performance is better with outlier corrected series. The diagnostic of the model is also analyzed. The study presents robust policy implications for outlier detection procedures in volatile models.

What Determines the Interest in Investing to Gold Savings at Pegadaian Syariah?

Sharia pawnshops are a financial institution that plays an important role in society. One of the products offered is gold investment. This study examines the effect of knowledge and promotions mediated by motivation on interest in investing in gold in sharia pawnshops. The object of the study was carried out in Banda Aceh City with 100 respondents spread across 9 districts. Determination of respondents using purposive sampling technique and analyzed by path analysis model. The results found that there was a positive effect of knowledge and promotion on the motivation to invest in gold. Promotion and investment also have a positive effect on interest in investing in gold. Meanwhile, knowledge does not have a positive effect on interest in gold investment. Other results found that motivation is not able to mediate knowledge of interest in investing in gold. However, knowledge can be mediated by the motivation to invest gold in sharia pawnshops. So, sharia pawnshops must increase promotion and outreach to the community so that the gold investment products offered are increasingly in demand.

Time-varying effects of the gold price and the oil price on imports in Turkey

ABSTRACT The impacts of the gold price, the oil price and the exchange rate on imports are analyzed using a time-varying parameter vector autoregressive with stochastic volatility (TVP-VAR-SV) model. The impulse response functions showed that the impact of oil price shocks on imports continued for a short period of time, whereas that of the gold price became more significant and gave rise to long term effects in later periods. The results reveal important implications for policy makers reducing imports, which stimulates a trade deficit in Turkey.