Price risk management in the copper market using commodity derivatives and options strategies

Metals price risk management is a key issue related to financial risk in metal markets because of uncertainty of commodity price fluctuation, exchange rate, interest rate changes and huge price risk either to metals’ producers or consumers. Thus, it has been taken into account by all participants in metal markets including metals’ producers, consumers, merchants, banks, investment funds, speculators, traders and so on. Managing price risk provides stable income for both metals’ producers and consumers, so it increases the chance that a firm will invest in attractive projects. The purpose of this research is to evaluate risk management strategies in the copper market. The main tools and strategies of price risk management are hedging and other derivatives such as futures contracts, swaps and options contracts. Hedging is a transaction designed to reduce or eliminate price risk. Derivatives are financial instruments, whose returns are derived from other financial instruments and they are commonly used for managing financial risks. Although derivatives have been around in some form for centuries, their growth has accelerated rapidly during the last 20 years. Nowadays, they are widely used by financial institutions, corporations, professional investors, and individuals. This project is focused on the over-the-counter (OTC) market and its products such as exotic options, particularly Asian options. The first part of the project is a description of basic derivatives and risk management strategies. In addition, this part discusses basic concepts of spot and futures (forward) markets, benefits and costs of risk management and risks and rewards of positions in the derivative markets. The second part considers valuations of commodity derivatives. In this part, the options pricing model DerivaGem is applied to Asian call and put options on London Metal Exchange (LME) copper because it is important to understand how Asian options are valued and to compare theoretical values of the options with their market observed values. Predicting future trends of copper prices is important and would be essential to manage market price risk successfully. Therefore, the third part is a discussion about econometric commodity models. Based on this literature review, the fourth part of the project reports the construction and testing of an econometric model designed to forecast the monthly average price of copper on the LME. More specifically, this part aims at showing how LME copper prices can be explained by means of a simultaneous equation structural model (two-stage least squares regression) connecting supply and demand variables. A simultaneous econometric model for the copper industry is built: {█(Q_t^D=e^((-5.0485))∙P_((t-1))^((-0.1868) )∙〖GDP〗_t^((1.7151) )∙e^((0.0158)∙〖IP〗_t ) @Q_t^S=e^((-3.0785))∙P_((t-1))^((0.5960))∙T_t^((0.1408))∙P_(OIL(t))^((-0.1559))∙〖USDI〗_t^((1.2432))∙〖LIBOR〗_((t-6))^((-0.0561))@Q_t^D=Q_t^S )┤ P_((t-1))^CU=e^((-2.5165))∙〖GDP〗_t^((2.1910))∙e^((0.0202)∙〖IP〗_t )∙T_t^((-0.1799))∙P_(OIL(t))^((0.1991))∙〖USDI〗_t^((-1.5881))∙〖LIBOR〗_((t-6))^((0.0717) Where, Q_t^D and Q_t^Sare world demand for and supply of copper at time t respectively. P(t-1) is the lagged price of copper, which is the focus of the analysis in this part. GDPt is world gross domestic product at time t, which represents aggregate economic activity. In addition, industrial production should be considered here, so the global industrial production growth that is noted as IPt is included in the model. Tt is the time variable, which is a useful proxy for technological change. A proxy variable for the cost of energy in producing copper is the price of oil at time t, which is noted as POIL(t ) . USDIt is the U.S. dollar index variable at time t, which is an important variable for explaining the copper supply and copper prices. At last, LIBOR(t-6) is the 6-month lagged 1-year London Inter bank offering rate of interest. Although, the model can be applicable for different base metals' industries, the omitted exogenous variables such as the price of substitute or a combined variable related to the price of substitutes have not been considered in this study. Based on this econometric model and using a Monte-Carlo simulation analysis, the probabilities that the monthly average copper prices in 2006 and 2007 will be greater than specific strike price of an option are defined. The final part evaluates risk management strategies including options strategies, metal swaps and simple options in relation to the simulation results. The basic options strategies such as bull spreads, bear spreads and butterfly spreads, which are created by using both call and put options in 2006 and 2007 are evaluated. Consequently, each risk management strategy in 2006 and 2007 is analyzed based on the day of data and the price prediction model. As a result, applications stemming from this project include valuing Asian options, developing a copper price prediction model, forecasting and planning, and decision making for price risk management in the copper market.

The growth response of planted red pine (Pinus resinosa Ait.) to alternative thinning regimes

Red pine (Pinus resinosa Ait.) plantations have been established in Michigan with expectations of mixed final product goals: pulpwood, boltwood and possibly sawlogs. The effects of alternative treatments on tree and stand attributes were examined in: the Atlantic Mine trial, thinned in spring 2006 with three alternatives: (1) every fifth row removal plus crown thinning, (2) every third row removal plus crown thinning and (3) every third row removal plus thinning from below; the Crane Lake trial, thinned in fall 2004 with two alternatives: (1) every third row removal and (2) every third row removal plus thinning from above; the Middle Branch East trial, thinned in fall 2004 with two alternatives: (1) every third row removal plus one in three remaining trees and (2) every third row removal plus one in five remaining trees. All trials included control plots where no thinning was applied. The trials were established in the field as a randomized complete block experiments, in which individual trees were measured in 3-4 fixed-area plots located within each treatment unit. Growth responses of diameter at breast height, height, live crown length, stand basal area and stand volume were examined along with their increments. The Tukey multiple comparison test was used to detect significant differences between treatments in their effect on tree growth response. The results showed that diameter increment increased with increasing thinning intensity and was significantly larger in thinned plots compared to unthinned. Treatments did not substantially affect average tree height increment. Stand basal area increment was significantly larger in the control plot only the year after the harvest. Volume increment was significantly larger in controls, but did not differ considerably among remaining treatments. However, the ratio of volume increment to standing volume was significantly smaller in unthinned plots compared to thinned. Since thinning treatments in all trials hardly ever differed significantly in their effect on stand growth response, mainly due to the relatively short time of the evaluation, heavier thinnings should be favored due to higher volume increment rates and shorter time needed to reach desirable diameters. Nevertheless, economic evaluation based on obtained results will be conducted in the future in order to make final decisions about the most profitable treatment.

FACTORS AFFECTING DIPOREIA GROWTH RATES IN LAKE SUPERIOR

An ability to predict population dynamics of the amphipod Diporeia is important in understanding how energy pathways in the Lake Superior food web might be altered by disturbances to the ecosystem. Estimating growth rates for this prominent prey item for fish requires information on the physiological effects of changes to its environment. These effects have been investigated for Diporeia in other Great Lakes, but little is known about Lake Superior populations. The primary objective of this study is to obtain quantitative data for rates of Diporeia respiration and consumption that can be incorporated into a bioenergetics model for Lake Superior. Benthic communities in Lake Superior were sampled bimonthly from April through September during 2011 and 2012 to investigate spatial and temporal trends of Diporeia abundances as well as size class structures of the population. Additional samples of Diporeia were collected and kept alive in natural sediment for laboratory experiments. Respiration rates for Diporeia were measured by monitoring dissolved oxygen concentrations in microcosoms using microelectrodes. Additionally, a series of experiments to estimate consumption rates based on food availability were conducted using 14C-labeled algae (Selenastrum capricornutum). Amphipod population densities are highest between 30-110 m (slope) compared to 0-30 m (shelf) or >110 m (profundal) regions in Lake Superior. This heterogeneous distribution of Diporeia in Lake Superior is an important component to quantifying lake-wide biomass. Rates of oxygen consumption by Diporeia range from 32.0 to 44.7 mgO2*gDW-1*d-1, and do not vary significantly with body size per individual. The predicted consumption rate corresponding to average Lake Superior algal carbon fluxes was 0.08 ± SE mgC*gDW-1*d-1. Data on Lake Superior Diporeia biomass and bioenergetics found in this study can be incorporated in a model used to estimate the viability of this population under potential future environmental stressors.