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.

Considering sustainability factors in the development project life-cycle : a framework for increasing successful adoption of improved stoves

Indoor air pollution from combustion of solid fuels is the fifth leading contributor to disease burden in low-income countries. This, and potential to reduce environmental impacts, has resulted in emphasis on use of improved stoves. However, many efforts have failed to meet expectations and effective coverage remains limited. A disconnect exists between technologies, delivery methods, and long-term adoption. The purpose of this research is to develop a framework to increase long-term success of improved stove projects. The framework integrates sustainability factors into the project life-cycle. It is represented as a matrix and checklist which encourages consideration of social, economic, and environmental issues in projects. A case study was conducted in which an improved stove project in Honduras was evaluated using the framework. Results indicated areas of strength and weakness in project execution and highlighted potential improvements for future projects. The framework is also useful as a guide during project planning.

Big Manistee River Tributaries as Potential Arctic Grayling Habitat

The Big Manistee River was one of the most well known Michigan rivers to historically support a population of Arctic grayling (Thymallus arctics). Overfishing, competition with introduced fish, and habitat loss due to logging are believed to have caused their decline and ultimate extirpation from the Big Manistee River around 1900 and from the State of Michigan by 1936. Grayling are a species of great cultural importance to Little River Band of Ottawa Indian tribal heritage and although past attempts to reintroduce Arctic grayling have been unsuccessful, a continued interest in their return led to the assessment of environmental conditions of tributaries within a 21 kilometer section of the Big Manistee River to determine if suitable habitat exists. Although data describing historical conditions in the Big Manistee River is limited, we reviewed the literature to determine abiotic conditions prior to Arctic grayling disappearance and the habitat conditions in rivers in western and northwestern North America where they currently exist. We assessed abiotic habitat metrics from 23 sites distributed across 8 tributaries within the Manistee River watershed. Data collected included basic water parameters, streambed substrate composition, channel profile and areal measurements of channel geomorphic unit, and stream velocity and discharge measurements. These environmental condition values were compared to literature values, habitat suitability thresholds, and current conditions of rivers with Arctic grayling populations to assess the feasibility of the abiotic habitat in Big Manistee River tributaries to support Arctic grayling. Although the historic grayling habitat in the region was disturbed during the era of major logging around the turn of the 20th century, our results indicate that some important abiotic conditions within Big Manistee River tributaries are within the range of conditions that support current and past populations of Arctic grayling. Seven tributaries contained between 20-30% pools by area, used by grayling for refuge. All but two tributaries were composed primarily of pebbles, with the remaining two dominated by fine substrates (sand, silt, clay). Basic water parameters and channel depth were within the ranges of those found for populations of Arctic grayling persisting in Montana, Alaska, and Canada for all tributaries. Based on the metrics analyzed in this study, suitable abiotic grayling habitat does exist in Big Manistee River tributaries.