Case Study

The tumultuous process of creating exchanges in the ongoing transition to a market economy is necessarily affecting sectors which produce a commodity typically traded on exchanges metal. In Moscow alone, three large special metal exchanges have recently begun operation the "Metals Exchange" (June 1991), the "Moscow Nonferrous Metals Exchange" (July 1991), and "Russian Metal" (RTSB November 1991). Specialized metal exchanges have been formed in the Ukraine, Kazakhstan, and other nations of the CIS, and nearly all of the large exchanges have set up special sections for metal products. There is already a trading market for such products, and a keen competition is developing between the different exchanges. The lead in this market will be taken by the exchange that can offer its stockholders and members the best prospects for growth and provide its brokers with the best opportunities for gain. It should be noted that that our leading metal exchanges bear little resemblance to classic international metal exchanges such as the London Metals Exchange (LME). The latter is a typical exchange and is one of the largest commodity trading centers in the world. Thus, the founders and managers of the exchanges in our country are very interested in the mechanism and organizational principles of its operation. The London Metals Exchange was organized in 1882 as the company "Metal Market and Exchange Company, Ltd." The exchange is a wholesale market for goods where deals are made for metal of a certain quantity at market prices. The exchange is a unique barometer of prices on the world nonferrous metals market. It is used to judge and establish the quality of metal and sets forth standard conditions for exchange contracts. The stock capital is 20,000 pounds sterling and is divided into 1000 ordinary shares costing 20 pounds each. The shareholders are all members of the exchange and must own at least two shares to enjoy the full rights of membership. The members of the exchange (about 100 companies) are divided into two categories: individual (principal) members, who have the right to conclude deals in their name; member-representatives (plenipotentiaries), who can make deals in the name of companies or corporations they represent. There is a small group of individual members who are in a priviledged position by virtue of the ability to conclude deals in the trading pit on their personal accounts and, for a fee, execute orders from non-priviledged members and third parties. The commissions thus earned range from 0.1 to 0.5% of the sale price in the case of copper and from 0.25 to 1% of the same in the case of lead and zinc. Non-priviledged members of the exchange generally pay lower brokerage fees than third parties. Shareholders and members of the exchange must be natives and residents of England. Individual members must be at least 21 years of age, as must the member-representatives and directors of the shareholding companies. All company shareholders must be English citizens, while at least 2/3 of the directors must also be citizens and residents of the country. The members of the exchange are chosen by the board of the exchange company by simple majority vote with at least 3/4 of the board present. New members are chosen by open ballot, but a secret ballot can be requested by any member of the board. The features of operation of our exchange stand in sharp contrast to the LME. First of all, a very limited number of metals is traded on the London exchange, and all of them are nonferrous metals. Our metal exchanges as most present domestic exchanges are of a universal character. Not only are all types of metal products traded, but so are many other goods. The exchanges are in essence large trade centers. And although most of the largest domestic exchanges began to specialize after prices were freed and a new law governing exchanges was enacted, they remain more diverse than the LME. This is due first of all to the lack of other channels for the sale of large quantities of metal products at market prices. In addition, the worsening shortage of all of the most important groups of commodities (at least for the short term) makes it almost mandatory that deals be concluded by barter which in turn requires broadening of the range of goods that can be traded.

The motivation of this paper is to identify the effect of treatment charge (TC) on LME (London Metal Exchange) copper prices. It is a fundamental variable as a supply side factor, because it is related to the smelting process and reflects the level of concentrates market tightness. To examine this question carefully, the regression model is applied. This paper finds a statistically significant negative link between TC and LME copper prices. It is found that a 10% increase in TC of copper decreases in copper return by 1.8%. Subsequently, the vector autoregression (VAR) model is introduced to consider the impact of TC to copper prices as a permanent effect. It is found that the negative impact of the TC to copper returns dies out quickly. The statistical estimation in this article will provide a good reference for future study.

This paper investigates the cross market linkages of Indian commodity futures for nine commodities with futures markets outside India. These commodities range from highly tradable commodities to less tradable agricultural commodities. We analyze the cross market linkages in terms of return and volatility spillovers. The nine commodities consist of two agricultural commodities: Soybean, and Corn, three metals: Aluminum, Copper and Zinc, two precious metals: Gold and Silver, and two energy commodities: Crude oil and Natural gas. Return spillover is investigated through Johansen’s cointegration test, error correction model, Granger causality test and variance decomposition techniques. We apply Bivariate GARCH model (BEKK) to investtigate volatility spillover between India and other World markets. We find that futures prices of agricultural commodities traded at National Commodity Derivatives Exchange, India (NCDEX) and Chicago Board of Trade (CBOT), prices of precious metals traded at Multi Commodity Exchange, India (MCX) and NYMEX, prices of industrial metals traded at MCX and the London Metal Exchange (LME) and prices of energy commodities traded at MCX and NYMEX are cointegrated. In case of commodities, it is found that world markets have bigger (unidirectional) impact on Indian markets. In bivariate model, we found bi-directional return spillover between MCX and LME markets. However, effect of LME on MCX is stronger than the effect of MCX on LME. Results of return and volatility spillovers indicate that the Indian commodity futures markets function as a satellite market and assimilate information from the world market.

This study applies a VECM DCC-MGARCH on the daily sampled data for the nickel 3 month and spot contracts traded on the London Metal Exchange in the period January 2010–December 2017 to show that the futures and spot exhibit a common stochastic trend. Their spread is not co-integrating, however. The hypothesis stating that the price of futures contracts departures from their long run equilibrium relationship do not affect the current price of the contract is rejected for 3 month futures contract. Periods of an increased conditional variances are observed. Volatility of nickel prices has been reacting to the situation on financial markets, especially in May 2010 when European Union announced financial help to Greece which is regarded as one step of financial crisis. Next increase was observed in October 2011, when there was a next step in Greek financial crisis (the agreement to write-off the Greek Debt). At the beginning of 2014, the one of the nickel producing country, Indonesia, stopped the export of minerals. That resulted in significant increase in nickel prices and their volatility. The increase of conditional variances was also observed in 2015 when there was an oversupply in the nickel market as far as the US dollar strengthening. Nevertheless, their conditional correlation coefficient remain almost stable and close to unity.

This paper presents a system for predicting the current price of lead based on artificial neural networks and NARX models. Using the London Metal Exchange (LME) spot metal price dataset for about 30 years, the proposed smart lead price prediction system can achieve prediction error of less than 10% (that's, approximately equal to $100). This article believes that in the near future, it can be expanded to predict futures prices from lead to other industries and even precious metals.

This study applies linear and nonlinear Granger causality tests to examine the dynamic relation between London Metal Exchange (LME) cash prices and three possible predictors. The analysis uses matched quarterly inventory, UK Treasury bill interest rates, futures prices and cash prices for the commodity lead traded on the LME. The effects of cointegration on both linear and nonlinear Granger causality tests is also examined. When cointegration is not modelled, evidence is found of both linear and nonlinear causality between cash prices and analysed predictor variables. However, after controlling for cointegration, evidence of significant nonlinear causality is no longer found. These results contribute to the empirical literature on commodity price forecasting by highlighting the relationship between cointegration and detectable linear and nonlinear causality. The importance of interest rate and inventory as well as futures price in forecasting cash prices is also illustrated. Failure to detect significant nonlinearity after controlling for cointegration may also go some way to explaining the reason for the disappointing forecasting performances of many nonlinear models in the general finance literature. It may be that the variables are correct, but the functional form is overly complex and a standard VAR or VECM may often apply.

Lunching futures market for steel has been regard as one of the most urgent issues in steel industry and futures exchanges. It is followed after chairman of IISI executive committee‘s suggestion and the LME (London Metal Exchange)‘s announcement of lunching plan in May of last year. In this paper, I examine the rationale for and the feasibility of the futures contract, together with the positive and negative impacts of the contract on the steel industry. Though there exist many obstacles, LME would not stop the effort to lunch the contract. This is because the futures market for steel products is expected to provide the industry with the following benefits : ① increase of price transparency, ② weakening of price control power, ③ settling of strained trade issues, and ④ promoting industry restructuring by driving un-competitive companies out of the market.

In this paper, we present a modification of the Weibull distribution for the Value-at- Risk (VaR) estimation of investment portfolios on the precious metals market. The reason for using the Weibull distribution is the similarity of its shape to that of empirical distributions of metals returns. These distributions are unimodal, leptokurtic and have heavy tails. A portfolio analysis is carried out based on daily log-returns of four precious metals quoted on the London Metal Exchange: gold, silver, platinum and palladium. The estimates of VaR calculated using GARCH-type models with non-classical error distributions are compared with the empirical estimates. The preliminary analysis proves that using conditional models based on the modified Weibull distribution to forecast values of VaR is fully justified.

Modeling Copper Prices

This thesis examines the legal problems affecting the marketing of Zambian copper. In this respect, the thesis seeks to discover the real causes of copper price instability and the effectiveness of international legal principles and institutional measures employed in an attempt to reduce such instabilities, A study of this nature, demands a careful scrutiny of the various legal and institutional mechanisms governing the marketing of copper and international measures designed to regulate such arrangements. To this effect, chapter one of the thesis provides an introduction which seeks to set out in general terms, the nature of the problems faced in the marketing of copper. These problems are then examined in relation to their effect on the Zambian economy in general. Chapter two, examines the background and development of the Zambian mining industry with a view to highlighting the genesis of the copper marketing system employed by Zambia. Discussed in this chapter are issues relating to mineral rights, mineral taxation, and measures aimed at the control of the production process. In chapter three an attempt is made to examine the rules and institutional organization of the most important copper marketing and price setting institution - the London Metal Exchange. Chapter four, examines one of the intergovernmental machinery employed to tackle the problems of commodity price instability and the possible application of its principles to copper. Chapter five, evaluates the United Nations Common Fund which is designed to support the international commodity agreement mechanism. Of prime concern in the analysis is to discover how far its principles may go in supporting a possible international copper agreement. Chapter six is devoted to a discussion of one of the existing intergovernmental mechanism for the stabilization of copper prices. The discussion centres on the role and effectiveness of the Intergovernmental Council for Copper Exporting Countries (CIPEC). The second existing intergovernmental approach to price stabilization is discussed in chapters seven and eight. This approach involves some form of international financial support machinery which may allow developing countries that produce copper to maintain their export earnings even when demand or prices decline. There are two such schemes operating at the moment and chapter seven is devoted to one scheme which is operated by the International Monetary Fund. Chapter eight examines the second scheme operating under a treaty of co-operation between the EEC countries on the one hand and ACP countries on the other. Chapter nine suggests an alternative approach to the problem of stabilization of copper prices. This approach involves the creation of a Southern African mineral marketing corporation that could act as a sole mineral marketing agency for countries in the sub region associated under Southern African Development Co-ordinating Conference (SADCC). The final chapter provides a summary of conclusions.

In this paper we propose a forward time update algorithm to recursively estimate subset vector autoregressive models (including an intercept term) with a forgetting factor, using the exact window case. The proposed recursions cover, for the first time, subset vector autoregressive models (VAR) with a forgetting factor and an intercept variable. We then present two applications. In the first application we apply the proposed estimation algorithm to the quarterly aluminium prices on the London Metal Exchange. The findings show that the proposed algorithm can improve the forecasting performance. In the second application a bivariate system investigates the relationship between the Australian's All Ordinaries Share Price Index (SPI) futures and BHP share price (BHP). The proposed algorithm also introduces the Monte Carlo Integration approach into the proposed algorithm to generate error bands for the impulse responses. These results confirm that the SPI Granger causes BHP, but not vice versa.

Non-ferrous metal inventories and the London metal exchange: a commentary

One of the most attractive aspects of commodity investment today is that there are now a number of passive indexes that are fully investable. The LMEX index is a narrowly focused index that offers returns based on a basket of industrial metals (aluminum, copper, nickel, zinc, tin, and lead). The index is constructed using futures contracts traded on the London Metals Exchange. This article presents the risk and return benefits of the LMEX index as an addition to existing stock and bond portfolios.

A recent paper, S. G. Hall and M. P. Taylor (1989), investigated a range of time-varying models for the risk premium for forward prices on the London Metal Exchange. By far the most successful model is the GARCH-M model, which assumes the GARCH process is exact. This paper considers how this assumption may be dropped and generates a stochastic GARCH process (SGARCH-M). This model is applied to the data used in Hall and Taylor (1989). A complication is that, under rational expectations, a second order moving average error process will exist. The model is extended to include this process. The results support the new model. Copyright 1991 by Blackwell Publishers Ltd and The Victoria University of Manchester

This study takes a close look at why Tsingshan Group decided to take a large short position in the London Metal Exchange (LME) nickel market. We examine the several factors that influenced their strategy. And explore the reasons behind Tsingshan's failure. In particular, we discuss thesize of their shot position in light of the difficulties they have encountered in reducing their positions quickly. The paper also analyzes Tsingshan's OTC trading activities and how they contributed to the crisis. Additionally, it discusses the strategies Tsingshan used to survive the crisis and compares their approach to other companies that have either succeeded or failed in short selling. It highlights the similarities that led to misjudgment and inadequate LME regulation while also looking at the unique factors that helped Tsingshan avoid disaster.