Gold Price Research Articles

Peran Inflasi Dalam Memoderasi Makro Ekonomi Terhadap Indeks Harga Saham Gabungan (IHSG)

Investors can use the Composite Stock Price Index (IHSG) to see how a country's economy is trending and decide when they will buy and sell shares. However, movements in the Composite Stock Price Index (IHSG) are not only influenced by the macroeconomic situation in the country, but also by the world economy. This research seeks to quantify the influence/impact of the Exchange Rate, Interest (BI Rate), GDP, World Gold Prices and World Oil Prices on the Composite Stock Price Index (IHSG) on the Indonesian Stock Exchange with Inflation as a moderating variable for the period 2020 - 2022. In this research, the research used is quantitative descriptive research. By using documentation techniques and library methods, secondary data was collected for data collection for this research. The research population consisted of 36 data using a sampling method, namely saturated sampling. The data in this study was tested using a program known as SmartPLS 3.2.9. The data analysis technique is using the Partial Least Squares structural equation which is carried out using two-stage modeling and testing procedures. The results of this research explain that the exchange rate, interest (BI Rate), world gold prices and world oil prices do not have a significant impact on the Composite Stock Price Index (IHSG). Meanwhile, GDP has a positive and significant impact on the IHSG. Inflation does not have the capability to moderate the relationship between exchange rates, interest (BI rate), GDP, world gold prices and world oil prices on the Composite Stock Price Index (IHSG)

The Asymmetric Effects of Oil Price Volatility on Stock Returns: Evidence from Ho Chi Minh Stock Exchange

This study is the first to investigate the asymmetric effects of oil price volatility on stock returns for the Ho Chi Minh Stock Exchange (HOSE). We utilized weekly series of VN30-Index, WTI crude oil prices, geopolitical risks (GPR) index, and gold prices spanning from 6 February 2012 to 31 December 2023 as data sources. Using a nonlinear autoregressive distributed lag (NARDL) bounds testing approach, we found that, in the shortterm, oil price volatility has negative asymmetric effects on market returns. Specifically, in the shortterm, a 1 percent increase in oil price volatility immediately leads to a 2.6868 percent decrease in the market returns, while a similar magnitude decrease in oil price volatility is associated with a 6.3180 percent increase in the market returns. In addition, the results obtained from the NARDL model indicated that, in the longterm, the negative and positive changes of oil price volatility have significantly negative effects on the market returns. Finally, the findings derived from the error correction model (ECM) show that a 98.21 percent deviation from the equilibrium level in the previous week is converged and corrected back to the long-term equilibrium in the current week.

Pengaruh Reputasi Perusahaan, Fluktuasi Harga Emas, Kualitas Pelayanan Dan Literasi Keuangan Terhadap Minat Nasabah Berinvestasi Melalui Cicil Emas Di PT. Pegadaian (Persero) Cabang Masbagik

This study aims to determine the influence of Company Reputation, Gold Price Fluctuations, Service Quality and Financial Literacy on Customer Interest in Investing through Gold Installments at PT. Masbagik Branch Pawnshop. The type of research used is associative with a quantitative approach. The sample in this study was 100 respondents. The sampling method used in this study is probability sampling with a simple random sampling method. The data obtained were analyzed using the Structural Equation Model Partial Least Square (SEM-PLS) analysis technique through SmartPLS software version 4. The results of this study show that the Company's Reputation and Gold Price Fluctuations have a positive and significant effect on Customer Interest in Investing through Gold Installments. Meanwhile, Service Quality and Financial Literacy do not affect customer interest in investing through gold installments.

Oil Market Dynamics and US Monetary Policy Uncertainty: Evidence from Explainable Artificial Intelligence Models

We utilize explainable artificial intelligence techniques to examine the main link between oil market dynamics and US monetary policy uncertainty. Our analysis unveils key findings. First, higher oil prices and rising oil market uncertainty are significantly associated with elevated levels of monetary policy uncertainty. Second, option-implied oil market volatility (an indicator of oil market uncertainty) emerges as the most important predictor of monetary policy uncertainty. Third, option-implied oil market volatility frequently interacts with option-implied gold market volatility while oil prices mostly interact with fluctuations in the US dollar. The findings offer valuable insights into the understanding of monetary policy uncertainty.

Predicting monthly gold prices in indian rupees using ARIMA, LSTM, GRU, and Simple Linear Regression models

Predicting monthly gold prices in indian rupees using ARIMA, LSTM, GRU, and Simple Linear Regression models

Metal remobilization at the Nibao gold deposit in Youjiang basin, SW China: Implications from mineral texture, trace element and sulfur isotope compositions of sulfides and TiO2 polymorphs

Multistage mineralization overprinting is important for the formation of giant hydrothermal gold deposits. The Youjiang basin in SW China has undergone at least three major deformation phases in the Mesozoic, but their relationship with the large-scale gold accumulation in the region remains enigmatic. Here, we study the large Nibao gold deposit (reserve > 70 t Au) in the northern part of the basin, which has both fault-controlled and stratabound orebodies. We identified a pre-ore stage and syn-ore stage including four tectono-hydrothermal (T-H) substages (i.e., T-H stage 1, 2, 3 and 4) for the local mineralization at Nibao. The pre-ore stage is dominated by coarse-grained pyrite coexisting with TiO2 polymorphs in the Middle-Late Permian basaltic rocks. The T-H substage 1 is characterized in that the sedimentary pyrites are brecciated in bedding-parallel faults. Fluorination and silicification occur in the T-H substage 2, which is re-brecciated at the T-H substage 3 forming the highest gold grade ore in high-angle thrust fault. The T-H substage 4 presents as fault reactivation within minor calcite and pyrite deposition. Mineralogy and in-situ trace element analyses reveal that mineral dissolution and reprecipitation (incl. dolomite, auriferous pyrite and TiO2 polymorphs) is ubiquitous during the multistage tectono-hydrothermal process, and the continuous alteration overprinting may have promoted gold accumulation. This replacement process of different generations of auriferous pyrite is also recorded by their inherited sulfur isotopes, giving a narrow δ34S (−3.1 to + 2.1 ‰) range. Anatase is the main accessory phase of TiO2 polymorphs, as identified with LA-ICP-MS trace element and laser Raman spectroscopic analyses. Moreover, the anatase can been divided into two types (type-I and II) based on their texture, alteration and chemistry. The type-I anatase commonly occurring in the stratabound ore is characterized by higher Zr (mean 1,730 ppm), V (mean 1,412 ppm), and Cr (mean 110 ppm) contents than type-II that coexists with zoned pyrite in the fault-controlled ore (mean 26 ppm, 187 ppm, and 38 ppm, respectively). Additionally, W (mean 636 ppm) and Mg (10,021 ppm) in type-II are much higher than type-I ones (mean 135 ppm W and 476 Mg). These features show that the sedimentary-stage Zr-V-Cr-rich type-I anatase was dissolved via fluid metasomatism, and reprecipitated as the hydrothermal-stage W-Mg-rich and Zr-poor anatase, with gold gradually enriched. Besides, the anatase phase of TiO2 polymorphs also indicates that the Nibao gold deposit was formed under low pressure–temperature condition. Overall, we propose that the Nibao is a Carlin-type gold deposit, dominated by multistage tectono-hydrothermal events.

Cryptocurrency, Gold, and Stock Exchange Market Performance Correlation: Empirical Evidence

This paper examines the correlation between three prospective investing options: the Bitcoin cryptocurrency price, gold, and the Dow Jones stock index. The main research question is whether there is a causal effect of gold and the DWJ on Bitcoin and how this effect varies on time. The study begins with a background analysis that explains the definitions and operation of cryptocurrencies, followed by a brief overview of gold and its derivatives. In addition, a historical review of stock markets is provided, with a focus on the Dow Jones index. Then, a literature review follows. Daily data from three separate periods are used, each spanning four years. The first period, running from October 2014 to September 2018, provides an overview of the introduction of official cryptocurrency price data. The second period, running from Oct 2018 to Sept 2022, captures more recent trends preceding COVID-19. The third period, from January 2020 to December 2023, is the whole COVID-19 period with the initiation, embedded, and terminal phases. Classical inductive statistical methods (descriptive, correlations, multiple linear regression) as well as time series analysis methods (autocorrelation, cross-correlation, Granger causality tests, and ARIMA modeling) are used to analyze the data. Rigorous testing for autocorrelation, multicollinearity, and homoskedasticity is performed on the estimated models. The results show a correlation of Bitcoin with gold and the DWJ. This correlation varies over time, as in the first period the correlation mainly concerns the DWJ and in the second it mainly concerns gold. By using ARIMA models, it was possible to make a forecast in a time horizon of a few days. In addition, the structure of the forecasting mechanism of gold and DWJ on Bitcoin seems to have changed during the COVID-19 crisis. The findings suggest that future research should encompass a broader dataset, facilitating comprehensive comparisons and enhancing the reliability of the conclusions drawn.

Prediction of values of Borsa Istanbul Forest, Paper, and Printing Index using machine learning methods

It is difficult to predict index values or stock prices with a single financial formula. They are affected by many factors, such as political conditions, global economy, unexpected events, market anomalies, and the characteristics of the relevant companies, and many computer science techniques are being used to make more accurate predictions about them. This study aimed to predict the values of the XKAGT index by using the monthly closing values of the Borsa Istanbul (BIST) Forestry, Paper and Printing (XKAGT) index between 2002 and 2023, and the machine learning techniques artificial neural networks (ANN), random forest (RF), k-nearest neighbor (KNN), and gradient boosting machine (GBM). Furthermore, the performances of four machine learning techniques were compared. Factors affecting stock prices are generally classified as macroeconomic and microeconomic factors. As a result of examining the studies on determining the macroeconomic factors affecting the stock markets, 10 macroeconomic factors were determined as input. The macroeconomic variables used were crude oil price, exchange rate of USD/TRY, dollar index, BIST100 index, gold price, money supply (M2), S&P 500 index, US 10-year bond interest, export-import coverage rate in the forest products sector, and deposits interest rate. It was determined that all machine learning techniques used in the study performed successfully in predicting the index value, but the k-nearest neighbor algorithm showed the best performance with R2=0.996, RMSE=71.36, and a MAE of 40.8. Therefore, in line with the current variables, investors can make analyzes using any of the ANN, RF, KNN, and GBM techniques to predict the future index value, which will lead them to accurate results.

Retraction notice: How macroeconomic indicators influence gold price management

Retraction notice: How macroeconomic indicators influence gold price management

Nexus Between Oil, Gold Price and Dxy Index on Indonesian Stock Market During Geopolitical Events (2022 – 2024)

Objective: The aim of this study is to observe the impact of oil, gold, and the DXY index on the Indonesian stock market during geopolitical events in 2022-2024. Theoretical Framework: Rising political tensions also have a major impact on global currencies, financial market and commodity market. This event lead to uncertainty which increasing the investment risk. Hence, geopolitical events could affect stock return in capital market. Method: The data used consists of daily Jakarta Composite Index (JCI) closing data, WTI daily closing prices, gold daily closing prices, and DXY closing data from 24 February 2022 – 31 December 2022 and 14 April 2024 – 30 April 2024. Data obtained form Bloomberg. The analysis technique used was GARCH (1.1). Results and Discussion: The results showed that WTI oil price changes had significant positive effects on stock return in Indonesia. However, gold price changes had insignificant positive effects on stock returns in Indonesia during geopolitical events, while the DXY Index had insignificant, negative effects. Research Implications: Investors and traders in Indonesia Stock Exchange should consider oil price changes for investing in stocks during geopolitical events. Originality/Value: This study contributes to literatures regarding the stock market turbulence during geopolitical events and its effect toward stock return. The relevance and value of this research are evidenced by the insignificanct effect of gold and DXY toward stock return, while WTI has significant effect toward stock return.

Global economic contraction, climate change and the gold market volatility: A GARCH‐MIDAS approach

AbstractOur paper has two main objectives. First, we aim to investigate the relationship between global economic contraction (GECON) and the return volatility of gold. Second, we examine the role of climate change as a mediator in this connection. To achieve this, we use the GARCH‐MIDAS model, which accommodates data in different frequencies in the same model. This prevents the loss of important information when aggregating high‐frequency data to lower‐frequency data. We also use alternative measures of GECON from Kilian and Zhou (Journal of International Money and Finance, 2018; 88, 54–78) and Baumeister et al. (Review of Economics and Statistics, 2020;104(4), 828–844) to ensure the robustness of our findings. Our results show that global economic contraction positively impacts the return volatility of gold. Additionally, our findings confirm that the increased uncertainty caused by climate change makes gold a safe haven for investors. This means that gold's return volatility is not negatively impacted by the rising level of uncertainty caused by climate‐induced contraction. Moreover, we note that the index of GECON that accommodates more dynamics can produce more accurate predictability for gold market volatility. Our analysis of stock market volatility further confirms that gold has a safe haven potential relative to the stock market.

The Implementation of Gated Recurrent Unit (GRU) for Gold Price Prediction Using Yahoo Finance Data: A Case Study and Analysis

The Implementation of Gated Recurrent Unit (GRU) for Gold Price Prediction Using Yahoo Finance Data: A Case Study and Analysis

Modelling (A)symmetric Nexus Between Macroeconomic Information Sentiment Biases and Stock Market Returns in Case of India: A Bound Test Approach

This research attempts to scrutinise the asymmetric nexus of macroeconomic factors in determining the financial stock market performance using index returns of BSE-SENSEX and NSE-NIFTY as proxies for stock market performance in India. The auto-regressive distributed lag (ARDL) results demonstrate the long-term nexus of money supply, interest rates, gold prices, inflation, exchange rate, oil prices and foreign institutional investment (FII) in the capital market with stock returns. The non-linear ARDL (NARDL) results unequivocally support that the selected macroeconomic factors have an asymmetric nexus with the stock market performance. The study’s empirical findings have significant consequences for policy in designing the asset allocation decisions by the investor, portfolio managers and policymakers in the circumstances of a sudden positive or negative shock in the stock market. JEL Codes: E44, G10, C58

The Influence of Income, Gold Prices and Inflation on Rahn PT's Financing Distribution. Pawnshop with ROA as an Intervening Variable

The Influence of Income, Gold Prices and Inflation on Rahn PT's Financing Distribution. Pawnshop with ROA as an Intervening Variable

Development of complete hydrometallurgical processes for gold recovery from ICs and CPUs using ionic liquids

Integrated circuits (ICs) and central processing units (CPUs), essential components of electrical and electronic equipment (EEE), are complex composite materials rich in recyclable high-value strategic and critical metals, with many in concentrations higher than in their natural ores. With gold the most valuable metal present, increase in demand for gold for EEE and its limited availability have led to a steep rise in the market price of gold, making gold recycling a high priority to meet demand. To overcome the limitations associated with conventional technologies for recycling e-waste, the use of greener technologies (ionic liquids (ILs) as leaching agents), offers greater potential for the recovery of gold from e-waste components. While previous studies have demonstrated the efficiency and feasibility of using ILs for gold recovery, these works predominantly concentrate on the extraction stage and often utilise simulated solutions, lacking the implementation of a complete process validated with real samples to effectively assess its overall effectiveness. In this work, a simulated Model Test System was used to determine the optimal leaching and extraction conditions before application to real samples. With copper being the most abundant metal in the e-waste fractions, to access the gold necessitated a two-stage pre-treatment (nitric acid leaching followed by aqua regia leaching) to ensure complete removal of copper and deliver a gold-enriched leach liquor. Gold extraction from the leach liquor was achieved by liquid-liquid extraction using Cyphos 101 (0.1 M in toluene with an O:A = 1:1, 20 °C, 150 rpm, and 15 min) and as a second process by sorption extraction with loaded resins (Amberlite XAD-7 with 300 mg of Cyphos 101/g of resins at 20 °C, 150 rpm and 3 h). In both processes, complete stripping and desorption of gold was achieved (0.5 M thiourea in 0.5 M HCl) and gold recovered, as nanoparticles of purity ≥95%, via a reduction step using a sodium borohydride solution (0.1 M NaBH4 in 0.1 M NaOH). These two hydrometallurgical processes developed can achieve overall efficiencies of ≥95% for gold recovery from real e-waste components, permit the reuse of the IL and resins up to five consecutive times, and offer a promising approach for recovery from any e-waste stream rich in gold.

The Influence of the Exchange Rate, Money Supply, Exports, Bank Indonesia's Reference Interest Rates and the Price of Gold on Inflation in Indonesia

This research aims to examine and analyze the influence of the exchange rate, money supply, exports, Bank Indonesia reference interest rates, and gold prices on inflation in Indonesia. The data is secondary time series data from 2000Q1 to 2023Q3 obtained from Bank Indonesia, the Central Statistics Agency, and the London Bullion Market Association (LBMA). This research uses a quantitative approach with the Error Correction Model (ECM) research method to determine the long-term and short-term effects between variables. The data processing tool uses the statistical application E Views- 10. The results of data analysis show that in the long term the money supply, exports and the BI reference interest rate have an effect on inflation in Indonesia, while the Rp/USD exchange rate and the price of gold have no effect on inflation in Indonesia. Indonesia in the long term. Then, in the short term, only the money supply and Bank Indonesia's benchmark interest rate have an effect on inflation in Indonesia, while the Rp/USD exchange rate, exports and gold prices have no effect on inflation in Indonesia in the short term.

The Correlation Between Gold Price and Some Macroeconomic Factors in Vietnam Period 2018-2023

The Correlation Between Gold Price and Some Macroeconomic Factors in Vietnam Period 2018-2023

Indonesia Gold Price Forecasting Using ARIMA Model (0,1,1) - GARCH (1,0)

A frequently employed time series model is the Autoregressive Integrated Moving Average (ARIMA) model. In highly volatile data, ARIMA models sometimes produce residual variances that are heteroscedasticity. One method that can overcome the problem of residual variance heteroscedasticity is the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) method. The purpose of this study is to obtain the ARIMA-GARCH model for daily gold price data in Indonesia for the period 1 January 2022 to 31 December 2022, and to obtain daily gold price forecasting results in Indonesia. The daily gold price forecasting model obtained for Indonesia is ARIMA (0,1,1) - GARCH (1,0) with a MAPE value of 0.5745% which shows that the model is very good because the MAPE value is less than 10%. The results of Indonesia's daily gold price forecast from January 1st, 2023 to January 3rd, 2023 remain stable.

THE RELATIONSHIP BETWEEN BIST BANK INDEX AND INFLATION, EXCHANGE RATE, INTEREST RATE, GOLD AND OIL PRICES: EVIDENCE FROM THE ARDL BOUND TEST

The aim of this study is to investigate the effects of inflation, exchange rate, interest rates, gold and oil prices on the BIST bank index between January 2005 - October 2023. For this purpose, firstly, the stationarity levels of the data were tested by the Augmented Dickey-Fuller (ADF) and Phillips- Perron (PP) tests. Then, since the series became stationary at different levels, ARDL bounds test, one of the cointegration tests, was applied. In the study, it is concluded that the BIST bank index and its independent variables are cointegrated in the long-run in the relevant period. According to the short-term asymmetric relationship results, a 1% increase in gold prices by 0.036%, a 1% increase in interest rates by 0.33%, and a 1% increase in the dollar exchange rate by 1.03% decreased the BIST Bank index. On the other hand, a 1% increase in CPI has a positive effect on the BIST Bank Index. No statistical relationship was found between oil prices and BIST Bank Index.

Effects of Gold Nanoparticles on Mentha spicata L., Soil Microbiota, and Human Health Risks: Impact of Exposure Routes.

Nanoparticles, due to their extensive production and application, can have significant consequences for the environment, including soil and plant pollution. Therefore, it is very important to assess how nanoparticles will affect plants depending on the exposure pathways. The effect of gold nanoparticles in a concentration range of 1-100 mg/L on Mentha spicata L. during a 28-day experiment was investigated. Two routes of nanoparticles exposure were applied: root and foliar. Transmission electron microscopy was used to characterize nanoparticles and their effect on plant leaves' ultrastructure. Gold content in soil and plant segments was determined using k0-neutron activation analysis. For root exposure, gold was mainly accumulated in soil (15.2-1769 mg/kg) followed by root systems (2.99-454 mg/kg). The maximum accumulation of gold in leaves (5.49 mg/kg) was attained at a nanoparticle concentration of 100 mg/L. Foliar exposure resulted in the maximum uptake of gold in leaves (552 mg/kg) and stems (18.4 mg/kg) at the highest applied nanoparticle concentration. The effect of nanoparticles on the Mentha spicata L. leaves' biochemical composition was assessed. Nanoparticles affected the content of chlorophyll and carotenoids and led to an increase in antioxidant activity. Root exposure to gold nanoparticles resulted in an increase in the number of starch grains in chloroplasts and also suppressed the activity of the soil microbiota. Gold extraction from mint leaves into herbal infusion varied from 2 to 90% depending on the concentration of nanoparticles in the solution and the exposure route. The health risk as a result of gold exposure via herbal tea intake was assessed through estimated daily intake. The hazard quotient values were found to be less than the cutoff, indicating that a cup of tea infusion should not cause a serious impact to human health.