Metal Commodities Research Articles

Interplay multifractal dynamics among metal commodities and US-EPU

Interplay multifractal dynamics among metal commodities and US-EPU

PERBANDINGAN METODE DOUBLE EXPONENTIAL SMOOTHING HOLT DAN FUZZY TIME SERIES CHEN UNTUK PERAMALAN HARGA PALADIUM

Palladium is one of the precious metal commodities with the best performance since 3 years ago. Palladium has many benefits, including being used in the electronics, medical, jewelry and chemical industries. The benefits of palladium in the chemical field are that it can help speed up chemical reactions, filter out toxic gases in exhaust gases, and convert the gas into safer substances, so palladium is usually used as a catalyst for cars. Forecasting is a process of processing past data and projected for future interest using several mathematical models. The model used in this study is the Double Exponential Smoothing Holt and Fuzzy Time Series Chen methods. The process of forecasting palladium prices using monthly data from January 2011 to December 2020 with the Double Exponential Smoothing Holt method and the Fuzzy Time Series Chen method will be carried out in this study to describe the performance of the two methods. Based on the results of the analysis, it can be concluded that the Double Exponential Smoothing Holt and Fuzzy Time Series Chen methods have equally good performance with sMAPE values of 6.21% for Double Exponential Smoothing Holt and 9.554% for Fuzzy Time Series Chen. Forecasting for the next 3 periods using these two methods generally produces forecasting values that are close to the actual data.

Stock Price Determinant of PT Timah Tbk During the Covid-19 Pandemic

Stock Price Determinant of PT Timah Tbk during the Covid-19 Pandemic, the Covid-19 Pandemic involves the world economy. Lockdown and Large-Scale Social Restrictions make the economy slow down due to the restricted activities. The prices of crude oil and metal commodities also corrected, including the price of tin commodity due to the decrease of demand. Therefore, the aim of this study is to analyze the impact of the tin price variable, Interest Rate (BI Rate), Net Profit Margin (NPM), and Debt to Equity Ratio (DER) on the Stock Price of PT Timah Tbk during the Covid-19 pandemic. This study used a quantitative method. The object of the study was PT Timah Tbk. The samples used were secondary data, which were tin commodity price, and interest rate of SBI in 2020, and the quarterly financial statements of PT Timah Tbk. The analysis method used was Multiple Linear Regression. The data collection techniques used in this study consisted of two stages: conducting library research (studying literature in the form of research journals, scientific papers, articles, and books) and the documentation stage. The results of the study show that (1) Partially, tin price has a positive and significant impact on the stock price of PT Timah Tbk. (2) Partially, variables of interest rate, NPM, and DER have a negative and not significant impact on the stock price of PT Timah Tbk. (2) Simultaneously, tin price, interest rate, NPM, and DER have a significant impact on the stock price of PT Timah Tbk.
 Keywords : Tin Price, Interest Rate (BI Rate), Net Profit Margin (NPM), Debt to Equity Ratio (DER), and Stock Price

Prospective life cycle assessment of metal commodities obtained from deep-sea polymetallic nodules

Sustainable metal supply will be essential to achieve climate and sustainability goals (e.g., Paris agreement), for instance by providing the necessary raw materials for renewable energy infrastructure systems. The potential exploitation of mineral resources from the deep sea (e.g., polymetallic nodules) can play a major role in this supply. A holistic environmental analysis is needed, in order to consider the entire value chain of the products obtained out of deep-sea exploitation. Therefore, the objective of this study was to perform a prospective life cycle assessment (LCA) of deep-sea-sourced commodities and compare it to equivalent products obtained from terrestrial mining. It considered as reference flow one tonne of (dry) nodules, using a cradle-to-gate approach up to the final metal commodities, analyzing the delivery to the market of 10.5 kg of copper, 12.8 kg of nickel, 2.3 kg of cobalt and 311.3 kg of ferromanganese. Three environmental impact categories were analyzed, i.e., climate change, acidification and photochemical oxidant formation. Overall, onshore activities (e.g., hydrometallurgical processing) are the main hotspots for environmental impacts of metals sourced from the deep sea; offshore activities play a minor role in the value chain. While photochemical oxidant formation impacts would be similar to terrestrial alternatives, the deep-sea-sourced commodities can bring environmental gains in the order of 38% for climate change and up to 72% for acidification. As this study shows, a strategic selection of the location for onshore processing of the polymetallic nodules is key to target cleaner production, not only because of the distance from the nodules site, but especially because of the available energy mix. The results should be interpreted with care, though, due to intrinsic limitations of the LCA study, e.g., the prospective nature of this study, the limited access to terrestrial mining data, amongst others. Nonetheless, regardless the limitations a prospective LCA imposes, this study highlights some important potential benefits that commodities from deep-sea polymetallic nodules can bring to society with respect to three important environmental impacts.

Spillovers and interdependency across base metals: Evidence from China's futures and spot markets

Using the framework of Diebold and Yilmaz (2012, 2014), we examine the spillovers of informational shocks and the connectedness in China's base metals futures and spot markets. We find that base metals tend to generate more total spillovers in the futures market than in the spot market and that individual metals, apart from nickel, have nearly identical directional spillover impacts on or from other base metals in both the futures and spot markets. Copper and zinc act as the pricing centre in both futures and spot markets, where informational innovation is expected to flow from copper and zinc to other metal commodities. According to the dynamic analysis, the US-China trade dispute tends to significantly reduce total spillovers in both the futures and spot markets. We also find that the information transmission channels between base metals in futures and spot markets differ slightly and that the futures market leads the spot market in price discovery.

Spillovers and portfolio optimization of precious metals and global/regional equity markets

ABSTRACT We examine the spillovers and resource allocation characteristics of a portfolio of precious metal commodities and global/regional equity markets using a directional spillover index and portfolio optimization methods. Spillover index results show that the largest spillovers among precious metals occur between gold and silver and between zinc and lead. The largest spillovers of the world, Americas, Europe and Asia Pacific equity indices are on palladium and copper. Copper and zinc most largely spillover on the world and Americas equity indices. Copper and lead most largely spillover on the Europe equity index, while copper and silver most largely spillover on the Asia Pacific equity index. Portfolio optimization results indicate that nickel and lead add the most risk to total portfolio risk, whereas gold, platinum and aluminium add the least risk to the portfolio of commodities. Gold and aluminium are the precious metals most desirable for investment.

The safe-haven property of precious metal commodities in the COVID-19 era

This paper examines the presence of short- and long-run asymmetric relationships between precious metal commodities and S&P 500 stock market index and explores the safe-haven role of five precious metals (Aluminum, Platinum, Palladium, Copper, Gold) against the S&P 500 market index. We apply the nonlinear ARDL framework on daily data covering the COVID-19 pandemic period from 12/31/2019 to 06/25/2021. The main results highlight that precious metal commodities still impact the S&P 500 stock market index in an asymmetric manner but have lost their safe-haven role against the S&P 500 index. In the short-run, only aluminum has an asymmetric effect on S&P 500. However, Platinum, palladium, copper and gold have a symmetric effect on S&P 500. In the short-term, palladium, copper and gold are safe-haven assets against the S&P 500 stock market index. Furthermore, none of the considered precious metals acts as a safe-haven asset in the long-run. Our results have significant implications for portfolio investment strategies.

Traders’ motivation and hedging pressure in commodity futures markets

This study seeks to explain the major drivers of trading activity in commodity futures markets and gage the effect of trading activity on commodity prices. Rather than concentrating on a specific commodity subgroup or a particular type of commodity traders, we provide an extensive overview of the behavior across all market participants and their influence on commodity prices by using a broad set of commodity futures contracts. Although commodity futures returns show co-movement with financial fundamentals (U.S. dollar index, equity, and bond markets), based on the Disaggregated Commitment of Traders Report (DCOT), this relationship cannot be attributed to trading activity. Pricing in commodity markets can be predominantly attributed to hedgers and influential speculators (money managers), whereas small speculators (nonreportable traders) are crucial to some soft commodity futures similar to dealers in metals commodity futures. Furthermore, we find limited cases where inventory changes exert a sizable influence on position changes of DCOT traders.

The role of income and substitution in commodity demand

Abstract We estimate income elasticities of demand for three energy and six base metal commodities and their group aggregates. The elasticities, which vary with income levels, are estimated using a panel autoregressive distributed lag model covering the period 1965–2017, for up to 63 countries. We report three findings. First, most income elasticities are inversely proportional to income and decline rapidly as income rises. This implies commodity demand growth slows as economies develop, consistent with the dematerialization hypothesis. At median per capita income levels, the elasticity for metals (in aggregate) was 0.9, while that of energy was 0.7. Second, there is significant heterogeneity between commodities, both in terms of income elasticities and in terms of the performance of the model, with larger commodities and group aggregates performing better. Finally, we find evidence of substitution between commodities (e.g. oil/coal, aluminum/copper), estimated by the inclusion of the prices of similar commodities.

Expanding Perspectives of Element Cycling from 1970 to 2020: The Influence of Stumm and Morgan.

There has been significant advancement in understanding of element cycles over the past 50 years, and the contributions of the three editions of Aquatic Chemistry by Stumm and Morgan on the critical role of reactions in the aqueous phase on the global cycles of elements have been substantial. The primary focus of investigation of biogeochemical element cycles has been on the "grand nutrients" carbon, nitrogen, phosphorus, and sulfur. The basic chemistry and chemical systems perspective of Aquatic Chemistry helped elucidate the cycles of these elements. Most of the element cycling research beyond the grand nutrients has occurred in the past 20 years and has focused on commodity metals in widespread use, that is, the "technological nutrients". Focus in Aquatic Chemistry on metal chemistry has contributed to understanding of metal cycles. Development of integrated anthropogenic-biogeochemical cycles of metals, led by Graedel and collaborators, has revealed that anthropogenic mobilization of metals dominates the cycles. Integrated "anthrobiogeochemical" element cycles provide for more detailed understanding of sources and their cascading impacts, and enable identification of priorities for source control and/or element recovery. The fundamentals of water chemistry and their application in engineered and natural systems, as presented so effectively in Aquatic Chemistry, have contributed to advancement of anthrobiogeochemical cycle development and analysis and, directly or indirectly, to the scholars who will continue to evolve the understanding and use of element cycles in the years ahead.

Measuring Price and Income Elasticity of Demand Function of the Iranian Imports

Investigating the import demand function has particular importance in identifying the macroeconomic models and effectiveness and commercial efficiencies of the Iranian economy. For this reason, one of the major issues that can be addressed in the field of importing goods is the estimation of import demand function and investigating impacting factors on imports. Therefore, in this paper, throughout using seasonal data for the period 1992-2017 and applying the almost ideal demand system (AIDS) and using seemingly unrelated regression (SUR) econometric technique, we have estimated import price and income elasticities for five commodity groups based on one-digit tariffs code for the Iranian economy. The empirical results indicated that the import allocation pattern is single-stage and depends on the domestic sales. Also, the own-price elasticities had a negative sign which supports import behavior. Cross-price elasticities also showed a poor complementarity between the Other portable and metal commodities and, Social & personal services and Financial & business Services, domestic sales with Agricultural, forestry & fishing products, Other portable & metal commodities and Financial & business Services groups. The expenditure elasticities in five commodity groups were significant, except the first group, which implying effectiveness of demand for each commodity groups relative to income.

Future–Spot Relationship in Commodity Market: A Comparison Across Commodity Segments in India

This study aims to analyse the future–spot pricing relationship in the context of most actively traded commodities traded on Multi Commodity Exchange of India, which is the leading commodity exchange in the country today. The study intends to compare the pricing relations of three popular commodity segments, that is, bullion and metal, energy and agricultural segments, to explore whether future–spot pricing relationships are similar for all commodity segments or not. The study has applied vector autoregressive (VAR) model on a sample of 13 commodities, categorized as 7 commodities from bullion and metal segment, 2 commodities from energy segment and 4 commodities from agricultural segment. The results of VAR model show that in India, the non-agricultural commodity sector constituting of bullion, metal and energy commodities behave close to each other, but the behaviour of agricultural commodities is quite different from non-agricultural commodities. As regards non-agricultural commodities, the futures market plays a quite dominant and significant role as compared to the spot markets. However, in case of agricultural commodities, the futures market has a comparatively less dominant and strong role, and their spot market also plays an equally strong role. A comparative study of the pricing relationships existing among the three commodity segments will be extremely helpful for farmers, traders, investors as well as the portfolio managers in choosing the most profitable commodity classes for trading, investment and portfolio optimization. Regulators and policymakers can plan and implement an appropriate regulatory framework to strengthen these markets, especially agricultural commodity market, to promote economic growth.

Functional Effectiveness of Commodity Futures Market: A Comparative Assessment of Agricultural and Metal Commodities

The study focuses on examining the price discovery process, short run disturbances and hedging mechanism of agricultural and metal commodities futures market for the period January 2010 to December 2018. Contango and normal backwardation have also been taken into deliberation for select commodities which are traded in MCX and NCDEX, India which is a valuable addition to the existing body of literature in derivatives market. Johansen’s co-integration, VECM, Granger causality test and OLS are employed for understanding the price discovery and constant hedging for select commodities. Further, existence contango and normal backwardation have been observed by comparing the spot and futures prices. It has been found that spot market is acting as a leader in the longer period and laggard in short run investors can be benefitted to take short run or long run investment decision.

Seasonality in Indian Commodities Market: Insights for modeling from preceding commodity cycle

In this study we analyze seasonal behavior of Indian agriculture, energy and metal commodities through the ten years of preceding Super-cycle (2003-13) by considering monthly data for near month futures prices to remove basis variance. The thrust of the paper is to investigate seasonal behavior of selected commodities in India using monthly seasonal dummies. We found seasonal variation in four commodities namely gold, barley, guar and Jeera. In a declining interest-rate scenario and Post-Covid world, there is elevated likelihood that we are going to witness the next commodities super-cycle. It is imperative for hedge fund managers, global investors, commodities traders, high net-worth individuals, market participants and spread-traders to know what to expect based on the preceding super-cycle to strategize better and address seasonality.

An R-vine copula analysis of non-ferrous metal futures with application in Value-at-Risk forecasting

We employ the R-vine copula approach to study the dependence structure between non-ferrous metal commodity futures on the London Metal Exchange, focusing on the comparison before and after structural breaks. We find that the center of the dependence structure between non-ferrous metal futures shifts from copper to zinc after the first structural break in 2008 and moves back to copper after the second structural break in 2014. Additionally, we document that non-ferrous metals experienced an increase in the level of integration and tail dependence between 2008 and 2014, while this increase is shown to cease after 2014. We further develop an R-vine copula-based method for forecasting Value-at-Risk, and the backtesting results show superior forecasting accuracy over the benchmark methods. Our study is useful for market participants seeking to enhance their risk management for non-ferrous metals.

On the dynamic passivity and corrosion resistance of a low cost and low density multi-principal-element alloy produced via commodity metals

Recent exploration of multi-principal-element alloys (MPEAs), which include the so-called high-entropy alloys, has revealed hitherto unreported properties and phenomena arising from investigation of broader compositional space. Herein, a low cost and lightweight alloy (equiatomic AlFeMnSi) is presented that exhibits exceptional corrosion resistance in 0.6 M NaCl solution, despite a multiphase structure and the absence of well-known passivating elements (such as Cr, Mo, Ti and Nb). In-line inductively-coupled plasma mass spectroscopy (ICP-MS) analysis of alloy dissolution and angle-resolved X-ray photoelectron spectroscopy (AR-XPS) of the surface film revealed that the alloy passivates by a unique mechanism involving dissolution–precipitation of Si. The dynamic precipitation of a Si hydroxide surface film results in excellent passivity of the alloy, revealing the possibility of developing low-cost corrosion-resistant alloys from metals available from waste streams.

A Risk Measurement Model of China’s Non-Ferrous Metal Futures Market

With the impact of foreign exchange markets, risks in financial markets are becoming more complex and diversified, which underlines the importance of risk management in financial supervision. In this paper, China’s non-ferrous metal futures market is selected as the research object, and Shanghai Futures Exchange’s Industrial Metal Commodity Index (IMCI) data are used to measure risk using the conditional autoregressive value at risk (CAViaR) model. The US dollar index (USDX) is incorporated into the CAViaR model to study its impact on the risk. Through empirical analysis, we arrive at the following conclusions: First, the asymmetric slope CAViaR model (AS-CAViaR) is more suitable for measuring the risk in China’s non-ferrous metal futures market. Second, the risk is positively impacted by the lagged risk. Moreover, the impacts of positive and negative returns on the risk are asymmetric, with a negative return having a greater impact. Third, the positive and negative shock of USDX has significant and different impacts on the risk. These impacts can be caused by global capital flows. In addition, the impact of the vector of explanatory variables on the IMCI at different quantile levels is discussed based on the CAViaR-USDX model, which reflects the comprehensive advantages of the quantile regression method and the model’s applicability. The above conclusions verify the impact of USDX on China’s non-ferrous metal futures market and provide a theoretical basis and direction for risk monitoring.

Does Commodity Derivatives Function Effectively? A lengthy Discussion

The present work has been designed to intensely investigate the capability of the commodity futures market in achieving the aim of price discovery. Further, the downside of the cash and futures market and transfer of the risk to other markets has also been studied using VaR, and Bivariate EGARCH. The findings of the work point that the metal commodity derivative market helps in the efficient discovery of price in the spot market except for nickel. But, in the case of the agricultural commodities, the spot is found to be leading and thus there is no price discovery except turmeric. On the other hand, the volatility spillover is bidirectional for both agri and metal commodities except copper, where volatility spills only from futures to spot. Further, the effect of negative shock informational bias differs from commodity to commodity, irrespective of metal or agriculture.

Commodity prices and global economic activity: A derived-demand approach

We propose a derived-demand approach to explain the positive correlation and the synchronicity between the growth rates of commodity prices and of economic activity at the global level. Our focus is on important traded commodities, which supply function is very price inelastic in the short run, such as oil and major metal commodities. Our contributions are as follows. We first show the synchronicity of oil-price and global activity cycles using the tools of the common-feature literature. Second, we show how to improve forecasts of global activity using commodity prices, noting that we observe the latter at an almost continuous-time basis, but observe the former at a much lower frequency and with considerable delay. Third, we show the usefulness of optimal forecast combinations for oil prices employing a wide array of macroeconomic and financial variables. The out-of-sample R2 statistic for model combinations can reach up to about 14%, a major improvement over the previous literature.

Volatility of international commodity prices in times of COVID-19: Effects of oil supply and global demand shocks

This study examines the effects of oil supply and global demand shocks on the volatility of commodity prices in the metal and agricultural commodity markets using the SVAR model. The empirical evidence is based on real time daily closing international commodity prices covering the period 2 December 2019 to 1 October 2020. The findings are presented in cumulative impulse responses and variance decompositions. The former is utilized to examine the accumulated influence of structural shocks on the volatility of agricultural and metal commodities whereas the latter reflect the share of variation in the volatility of each commodity arising from each structural shock. Various patterns are provided on how metal and agricultural commodity prices have been influenced by the COVID-19 pandemic. Policy implications are discussed.