Evaluation of the impact of commodity price change on mine plan of underground mining

Fluctuations in commodity prices should influence mining operations to continually update and adjust their mine plans in order to capture additional value under new market conditions. One of the adjustments is the change in production sequencing. This paper seeks to present a method for quantifying the net present value(NPV) that may be directly attributed to the change in commodity prices. The evaluation is conducted across ten copper price scenarios. Discrete event simulation combined with mixed integer programming was used to attain a viable production strategy and to generate optimal mine plans. The analysis indicates that an increase in prices results in an increased in the NPV from$96.57M to $755.65M. In an environment where mining operations must be striving to gain as much value as possible from the rights to exploit a finite resource, it is not appropriate to keep operating under the same mine plan if commodity prices alter during the course of operations.

Co‑movement of commodity price indexes and energy price index:a wavelet coherence approach

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.

Do the RMB exchange rate and global commodity prices have asymmetric or symmetric effects on China’s stock prices?

With the rapid expansion of the RMB exchange rate’s floating range,the effects of the RMB exchange rate and global commodity price changes on China’s stock prices are likely to increase.This study uses both auto regressive distributed lag(ARDL)and nonlinear ARDL(NARDL)approaches to explore the symmetric and asymmetric effects of the RMB exchange rate and global commodity prices on China’s stock prices.Our findings show that without considering the critical variable of global commodity prices,there is no cointegration relationship between the RMB exchange rate and China’s stock prices,and the coefficient of the RMB exchange rate is not statistically significant.However,when we introduce global commodity prices into the NARDL model,the result shows that the RMB exchange rate has a negative effect on China’s stock prices,that there indeed exists a long-run cointegration relationship among the RMB exchange rate,global commodity prices,and stock prices in the NARDL model,and that global commodity price changes have an asymmetric effect on China’s stock prices in the long run.Specifically,China’s stock prices are more sensitive to increases than decreases in global commodity prices.Thus,increases in global commodity prices cause China’s stock prices to decline sharply.In contrast,the same magnitude of decline in global commodity prices induces a smaller increase in China’s stock prices.

Evaluating the exchange rate and commodity price nexus in Malaysia: evidence from the threshold cointegration approach

This paper examines the long-and short-run dynamics of asymmetric adjustment between the nominal exchange rate and commodity prices,namely oil,palm oil,rubber,and natural gas prices,in Malaysia using monthly data from January 1994 to December 2017.The relationship between exchange rate and each commodity price is examined in terms of Engle-Granger and threshold cointegrations.The estimated results provide evidence of long-run threshold cointegration and show that the adjustments towards the long-run equilibrium position are asymmetric in the short run.Furthermore,this study finds evidence of a unidirectional causal relationship running from the nominal exchange rate to oil price in the long and short run using a spectral frequency domain causality application.There is also empirical evidence of bidirectional causality between the nominal exchange rate and palm oil price,rubber price,and natural gas price in the long and short run.Overall,the findings have significant implications for the current debate on the future of primary commodities in Malaysia.

Price linkage between Chinese and international nonferrous metals commodity markets based on VAR-DCC-GARCH models

Using VAR-DCC-GARCH model,the literature on commodity price was extended by exploring the co-movement between Chinese nonferrous metal prices and global nonferrous metal prices represented by the nonferrous metal prices from London Metal Exchange(LME).The results show that LME nonferrous metals prices still have a greater impact on Chinese nonferrous metals prices.However,the impact of Chinese nonferrous metals prices on LME nonferrous metals prices is still weak except for lead price.The co-movement of nonferrous metal prices between LME and China presents hysteretic nature,and it lasts for 7-8trading days.Furthermore,the co-movement between LME nonferrous metals prices and Chinese nonferrous metals prices has the characteristics of time-varying,and the correlation of lead prices between LME and China is the more stable than all other nonferrous metals prices.

Pass-through Effects of Global Commodity Prices on China's Inflation:An Empirical Investigation

The present paper uses a two-step approach to estimate the pass-through effects of changes in international commodity prices and the RMB exchange rate on domestic consumer price inflation in China. We first estimate the pass-through effects of international commodity prices on producer prices and then estimate the pass-through effects of producer price inflation on consumer price inflation. We find that a l O-percent increase in international commodity prices would lead to China＇ s producer prices increasing by 1.2 percent 3 months later, which in turn would increase China＇ s domestic inflation by 0.24 percent over the same period. However, a 10-percent appreciation of the RMB exchange rate against the US dollar would help to reduce increases in producer prices by 4.4 percent over the following 3 months, which in turn would lead to a 0. 89-percent decline in consumer price inflation over the same period. Our findings suggest that appreciation of the RMB in an environment of rising global commodity prices and a weak US dollar could be an effective instrument to help contain inflation in China.

Hot Money Flows, Cycles in Primary Commodity Prices, and Financial Control in Developing Countries

Because the U.S. Federal Reserve＇s monetary policy is at the center of the world dollar standard, it has a first-order impact on global financial stability. However, except during international crises, the Fed focuses on domestic American economic indicators and generally ignores collateral damage from its monetary policies on the rest of the world. Currently, ultra-low interest rates on short-term dollar assets ignite waves of hot money into Emerging Markets （EM） with convertible currencies. When each EM central bank intervenes to prevent its individual currency from appreciating, collectively they lose monetary control, inflate, and cause an upsurge in primary commodity prices internationally. These bubbles burst when some accident at the center, such as a banking crisis, causes a return of the hot money to the United States （and to other industrial countries） as commercial banks stop lending to foreign exchange speculators. World prices of primary products then collapse. African countries with exchange controls and less convertible currencies are not so attractive to currency speculators. Thus, they are less vulnerable than EM to the ebb and flow of hot money. However, Afi-ican countries are more vulnerable to cycles in primary commodity prices because food is a greater proportion of their consumption, and--being less industrialized--they are of their commodity exports. Supply-side more vulnerable to fluctuations in prices shocks, such as a crop failure anywhere in the world, can affect the price of an individual commodity. But joint fluctuations in the prices of all primary products--minerals, energy, cereals, and so on--reflect monetary conditions in the world economy as determined by the ebb and flow of hot money from the United States, and increasingly from other industrial countries with near-zero interest rates.

Hot Money Flows,Commodity Price Cycles and Financial Repression in the USA and China:The Consequences of Near-zero US Interest Rates

Under near-zero US interest rates, the international dollar standard malfunctions. Emerging markets with naturally higher interest rates are swamped with hot money inflows. Emerging market central banks intervene to prevent their currencies from rising precipitately. They lose monetary control and domestic prices begin inflating. Primary commodity prices rise worldwide unless interrupted by an international banking crisis＇. This cyclical inflation on the dollar＇s periphery only registers in the US core eonsumer price index with a long lag. The zero interest rate policy also fails to stimulate the US economy as domestic finaneial intermediation by banks and money market mutual funds is repressed. Because China is forced to keep its interest rates below market-clearing levels, it also suffers from finaneial repression, although in a form differing from that in the USA.

A Bayesian Nonparametric Investigation of the Predictive Effect of Exchange Rates on Commodity Prices

This study proposes a full Bayesian nonparametric procedure to investigate the predictive power of exchange rates in relation to commodity prices for three commodity-exporting countries:Canada,Australia,and New Zealand.We propose a new time-dependent infinite mixture of a normal linear regression model of the conditional distribution of the commodity price index.The mixing weights follow a set of Probit stick-breaking priors that are time-varying.We find that exchange rates have a positive predictive effect in general,but accounting for time variation does not improve forecasting performance.By contrast,the intercept in the regression and the lagged dependent variable show signs of parameter change over time in most cases,which is important in forecasting both the mean and the density of commodity prices one period ahead.The results also suggest that the variance is a large source of the time variation in the conditional distribution of commodity prices.

Near-zero U.S. Interest Rates, Primary Commodity Prices, and Financial Control in Emerging Markets

The U.S. Federal Reserve's monetary policy at the center of the world dollar standard has a first-order impact on global financial stability. However, except in moments of international crises, the Fed focuses inward on domestic American economic indicators and generally ignores collateral damage from its monetary policies in the rest of the world. But this makes the U.S. economy less stable. Currently, ultra-low interest rates on dollar assets ignite waves of hot money into emerging markets by carry traders that generate bubbles in international primary commodity prices and other assets. These bubbles burst when some accident at the center, such as a banking crisis, causes a reflux of the hot money. Ironically, these near-zero interest rates hold back investment in the American economy itself.

Hybridized Intelligent Neural Network Optimization Model for Forecasting Prices of Rubber in Malaysia

Rubber producers,consumers,traders,and those who are involved in the rubber industry face major risks of rubber price fluctuations.As a result,decision-makers are required to make an accurate estimation of the price of rubber.This paper aims to propose hybrid intelligent models,which can be utilized to forecast the price of rubber in Malaysia by employing monthly Malaysia’s rubber pricing data,spanning from January 2016 to March 2021.The projected hybrid model consists of different algorithms with the symbolic Radial Basis Functions Neural Network k-Satisfiability Logic Mining(RBFNN-kSAT).These algorithms,including Grey Wolf Optimization Algorithm,Artificial Bee Colony Algorithm,and Particle Swarm Optimization Algorithm were utilized in the forecasting data analysis.Several factors,which affect the monthly price of rubber,such as rubber production,total exports of rubber,total imports of rubber,stocks of rubber,currency exchange rate,and crude oil prices were also considered in the analysis.To evaluate the results of the introduced model,a comparison has been conducted for each model to identify the most optimum model for forecasting the price of rubber.The findings showed that GWO with RBFNN-kSAT represents the most accurate and efficient model compared with ABC with RBFNNkSAT and PSO with RBFNN-kSAT in forecasting the price of rubber.The GWO with RBFNN-kSAT obtained the greatest average accuracy(92%),with a better correlation coefficient R=0.983871 than ABC with RBFNN-kSAT and PSO with RBFNN-kSAT.Furthermore,the empirical results of this study provided several directions for policymakers to make the right decision in terms of devising proper measures in the industry to address frequent price changes so that the Malaysian rubber industry maintains dominance in the international markets.

Analysis of Price and Industry Dynamics of Sustainable and Specialty Coffee in Costa Rica

Volatility of commodity prices has affected dramatically the coffee industry in recent years, particularly small holder farmers. Differentiation of coffee through certification, such as sustainahility and quality attributes, has been proposed as a strategy for protection of the farmers against volatility in the international prices. This research paper evaluated three different models to explore the effectiveness of the differentiation strategies in protecting the farmer against price volatility in recent years, focusing on the case of Costa Rica. Evidence showed important differences in the price dynamics over time when comparing three groups of coffee.

Research on the Impact of Aging and New Generation in the Popula­tion Structure on China’s Real Estate Price Volatility

To clarify the internal mechanism of the influence of the aging population and the new generation on housing prices is helpful to scientifically analyze and predict the trend of housing prices and the aging population and the new generation.This paper uses the intergenerational overlap model of the two periods as the theoretical basis,and uses the provincial panel data from 1998 to 2018 to study the impact of the elderly population and the new generation on the price fluctuations of commercial housing.The results of the study show that on the whole,both the aging population and the new generation have promoted the rise in commodity housing prices.However,the regional heterogeneity is significant.The aging population has the most significant impact on housing price increases in developed and general developed areas,and has no significant impact on housing price increases in other places.The new generation has a negative impact on housing prices in backward areas and a positive impact on housing prices in other areas.Looking further,using the ARIMA model to predict housing prices in the next 10 years,it is concluded that housing prices will show a slow upward trend in the next 10 years.Therefore,the government can ensure the stable development of the real estate market by revitalizing the second-hand housing market and implementing housing projects.

China’s Path: A Great Practice in Human Social Development

Over the past few years,while the world＇s economic development has undergone a profound adjustment,China＇s economy has maintained a medium-to-high rate of growth.According to statistics from the World Bank,China contributed more than 30 percent on average to the global economic expansion annually from 2011 to 2016（at constant 2010prices in U.S.dollars）.

Global Spillovers of China's Monetary Policy

Spillovers from China's monetary policy have become increasingly obvious with China's growing importance in the global economy and its close economic and trade ties with the world.This study establishes a proxy structure vector autoregression model to investigate the magnitude and transmission channel of spillovers from China to global and regional economies,taking advantage of high-frequency changes in asset prices in the financial markets to identify monetary policy shocks.The analysis reveals that China's monetary policy can affect the global economy by influencing international trade and commodity prices but there is no evidence of China's monetary policy affecting global financial variables.Tightness in China's monetary policy can cause a decline in world output whereas expansion in monetary policy can support global trade and output.This study also finds that the response of emerging Asian economies to China's monetary policy shock was nearly twice that of developed economies,while the transmission path did not change.The results of this study are consistent with the stylized fact that China's monetary policy plays an important role in the global trade and commodity cycle,although it does not drive the global financial cycle.