Query: metal price

title: Effect of oil price uncertainty on clean energy metal stocks in China: Evidence from a nonparametric causality in quantiles approach
abstract: Using the nonparametric causality in quantiles approach, we investigate the causal effects of oil price uncertainty on the returns and volatility of clean energy metal stocks under different market conditions in China. The results suggest that there is a causal relationship between oil price uncertainty and the returns and volatility of Chinese clean energy metal stocks. The effect differs slightly between returns and volatility. Specifically, the causal effect of oil price uncertainty on returns is mainly observed for lower quantiles, whereas the effect on volatility exists for all quantiles. In addition, the effects of change of market environment in China on the causal relationship are tested. The results show that change in market environment has significantly weakened the causal relationship between oil price uncertainty and clean energy metal stocks, suggesting that the structure of the Chinese clean energy metal stock market has undergone major changes.

title: Economic shocks and their effect on the schooling and labor participation of youth: evidence from the metal mining price boom in Chilean counties
abstract: We analyze the effect of an exogenous economic shock on youth, specifically their incentive for preferring to participate in the labor market over continuing their education. We examine the Chilean case and the sustained increase in the market price of the minerals extracted there during the period of Metal Mining Price Boom between the years 2003 and 2011. Chile is a large scale producer of metals, being the world's largest producer of copper and the third largest producer of molybdenum. The prices of such metals increased steadily during the shock, what boosted the economic growth and the demand for labor. This shock altered the skill composition in the labor market, increasing the jobs for low and medium low skilled workers in the counties more exposed to the shock, thus being the metal mining counties the most affected by its impact. According to this, our results show a negative impact of the shock on returns to schooling that simultaneously reduced school enrollment rates while increasing youth labor participation in those counties.

title: The impacts of oil price shocks and jumps on China's nonferrous metal markets
abstract: Existing studies have been concerned with the relationship between oil price and nonferrous metal markets. However, little attention has been paid to the impacts of lagged oil price shocks and volatility spillover effects of oil price jumps on China's nonferrous metal markets. This paper employs the ARMA EGARCH ARJI model to capture the volatility clustering and dynamic jumps in oil price fluctuation and the ARMA EGARCH model to study the impacts of oil price changes on China's nonferrous metal markets. The results indicate that both the shocks and jumps of oil price affect China's nonferrous metal markets. First, the nonferrous metal markets are negatively affected by the expected shocks and unexpected positive shocks, while the impacts of unexpected negative shocks are positive on most nonferrous metal markets. Second, the impacts of oil price shocks are characterized by time lag, and both the current and lagged oil price shocks affect the nonferrous metal markets. Third, oil price jumps lead to overreaction of volatility in nonferrous metal markets. This study not only contributes to advancing the existing literature, but also merits particular attention from both policy makers and market participants.

title: Interdependence and lead lag relationships between the oil price and metal markets: Fresh insights from the wavelet and quantile coherency approaches
abstract: We empirically examine the connectedness between the oil market and the major precious metals (gold, silver platinum, palladium) and the base metal copper over the available period covering December 06, 1988 to August 31, 2018, using the wavelet coherence and quantile cross spectral analyses. The major findings can be summed up as follows. First, regarding the connectedness among the considered precious metal markets, there is no evidence of identifying the causal interplays. Second, gold and platinum are highly connected with oil and they influence oil prices, especially during global markets' turmoil. Third, the cross quantile coherency analysis shows that gold and silver exhibit the highest quantile coherency. Fourth, the intensity of the nexus between gold and copper attains its nadir at the extreme upper and lower quantiles. Our empirical findings have relevant implications for investors. It is important for investors in commodity markets to make appropriate investment market decisions in extreme market circumstances. On the other hand, policymakers may benefit from our research, as they could generate suitable strategies.

title: Hyperfine field distributions at 119Sn nuclei in ferromagnetic transition metal alloys

title: Co movement of commodity price indexes and energy price index: a wavelet coherence approach
abstract: This research sheds light on the causal link between commodity price indexes, i.e. the Agricultural Raw Materials Price Index, Industry Input Price Index, Metal Price Index, and Energy Price Index, in the global market, using wavelet coherence, Toda Yamamoto causality, and gradual shift causality tests over the period 1992M1 to 2019M12. Findings from the wavelet power spectrum and partial wavelet coherence reveal that: (1) there was significant volatility in the Agricultural Raw Materials Price Index, Industry Input Price Index, Metal Price Index, and Energy Price Index between 2004 and 2014 at different frequencies; and (2) commodity price indexes significantly caused the energy price index at different time periods and frequencies. It is noteworthy that the outcomes of the Toda Yamamoto causality and gradual shift causality tests are in line with the results of wavelet coherence.

title: Price overreactions in the commodity futures market: An intraday analysis of the Covid 19 pandemic impact
abstract: The objective of this paper is to examine the overreaction behavior of 20 commodity futures based on intraday data from November 20, 2019 to June 3, 2020 with a focus on the impact of the Covid 19 pandemic. A dynamic and non parametric approach is applied on intraday data for four different frequencies (from 1 min to 1 h) and two different sub periods (pre Covid 19 pandemic and during Covid 19 pandemic) in order to detect overreaction behavior which is defined as a large change of prices followed by proportional price reversals. Our empirical findings show that the overreaction hypothesis is confirmed for the considered commodity futures. Furthermore, both the number and the amplitude of overreactions is higher during the Covid 19 pandemic. Our findings also indicate that soft and metal commodities show much less overreactions than precious metals and especially energy commodities. In particular, crude oil futures exhibit a different overreaction behavior compared to other commodities since it has a higher number of negative than positive overreactions during the Covid 19 pandemic. We also find that the data frequency is independent of the overreacting behavior in both periods as the results continuously improve when having more observations due to higher frequencies. Finally, we find that extreme overreactions during the Covid 19 pandemic provide a great potential for profitable trading returns, which can be exploited by traders.

title: COMMODITY PRICE AND INFLATION DYNAMICS: EVIDENCE FROM BRIICS
abstract: In this study, we use a commodity augmented Phillips curve to investigate the impact of global commodity prices on domestic inflation in Brazil, Russia, India, Indonesia, China, and South Africa. Oil and energy prices cause inflationary pressures in all countries, except Russia, where they cause deflationary pressures. In Indiaand Indonesia, global food prices are highly significant and positively related to inflation, while in South Africa precious metal prices impact inflation negatively. For policymakers, this study provides insights on the domestic adjustments required for inflation targeting in response to global commodity price volatility.

title: Forecasting copper price by application of robust artificial intelligence techniques
abstract: Metal price is one of the most important and effective parameters in assessing different projects such as industry and mining. In this regard, price variations can play a vital role in the correct decision making of managers to develop or limit mining activities. Considering the increasing use of artificial intelligence (AI) based networks in different fields such as price estimation, four methods were used in the present work for the first time to predict the price of important and extensively used copper grade A cathode. These methods include Gene expression programming (GEP) Artificial neural network (ANN) Adaptive neuro fuzzy inference system (ANFIS) and ANFIS ACO (ant colony optimization algorithm) In this process, coal, aluminum, crude oil, gold, iron ore, natural gas, nickel, and lead were selected as the copper price parameters from 1990 to 2020. In this study, the ANN model with one hidden layer comprising 13 neurons, RMSE of 356.51, M A E of 239.105 /ton) M A P E of 5.70% /ton) and coefficient of determination (R2) of 98.1% for network test data was selected as the best model in predicting copper prices. In terms of their performance, ANFIS, ANFIS ACO and GEP models were ranked next in the order of their appearance. Overall, an acceptable performance was found through all four AI methods in this study for predicting copper prices.

title: Oil price shocks and the return and volatility spillover between industrial and precious metals
abstract: This study explores the dynamic return and volatility connectedness for some dominant industrial (Aluminium, Copper, Lead, Nickel, Tin, and Zinc) and precious metals (Gold, Palladium, Platinum, Silver) to crude oil shocks (risk, demand, and supply) during the sample period between January 2, 2009 and July 17, 2020. Our findings indicate that, demand shocks and risk shocks are the dominant receiver (transmitter) of shocks from (to) for metal returns. Second, we document the time varying nature of both total return and volatility connectedness. Third, both net directional return and volatility connectedness show that some metals such as Tin, Gold and, even, Nickel, Lead and Aluminium appear as net transmitters, at least in some intervals of the sample period analysed. On the other hand, other industrial and precious metal markets show a net receiver profile, such as Copper, Zinc and Platinum, among others. Lastly, we find more differences between the net dynamic connectedness of the metal markets analysed in terms of return than volatility. The net directional volatility connectedness increases sizably during the global crisis due to the spread of the SARS CoV 2 coronavirus.