Commodity Price Risk Research Articles

Security of supply and regulation of energy networks

In recent years, the security of energy supplies has re-emerged as a central issue in the energy policy arena in the UK and elsewhere. This re-emergence takes place against a backdrop of increased liberalisation of the energy markets, so that security of supply needs to be revisited within this context. Security of supply is multifaceted, but is often discussed in terms of physical availability of energy sources and their commodity price risk. This paper discusses the relationship between security of supply and network regulation—that is, how the energy networks, and appropriate regulation of them, can contribute to security of supply in liberalised energy sectors. Energy networks are predominantly natural monopolies and as a result are generally subject to regulatory oversight. We discuss a range of issues and trends that pose challenges and opportunities to network regulation and which call for new and innovative measures. The paper identifies a number of areas where network regulation can play a significant role in increasing the security of supply of future energy systems.

Enhancing hedging performance with the spanning polynomial projection

Statistical time-series approaches to hedging are difficult to beat, especially out-of-sample, and are capable of out-performing many theory-based derivative pricing model approaches to hedging commodity price risks using futures contracts. However, the vast majority of time-series approaches to hedging discussed in the literature are essentially linear statistical projections, whether univariate or multivariate. Little is known about the potential hedging capabilities of nonlinear methods. This study describes how least-squares orthogonal polynomial approximation methods based on the spanning polynomial projection (SPP) can be used to enhance standard (linear) optimal hedging methods and improve hedging performance for a hedger with a mean–variance objective. Empirical analyses show that the SPP can be used effectively for hedging and gives better out-of-sample hedging performance than the benchmark VEC-GARCH hedging model. Results are robust to the inclusion of transaction costs and risk-aversion assumptions.

Financial Instruments to Hedge Commodity Price Risk for Developing Countries

Many developing economies are heavily exposed to commodity markets, leaving them vulnerable to the vagaries of international commodity prices. This paper examines the use of commodity options-including plain vanilla, risk reversal, and barrier options-to hedge such risk. It then proposes the use of a new structured product-a sovereign Eurobond with an embedded option on a specific commodity price. By extracting commodity price risk out of the bond, such an instrument insulates the bond default risk from commodity price movements, allowing it to be marketed at a lower credit spread. The product is also designed to help developing countries establish a credit derivatives market, which would in turn enhance the marketability and liquidity of sovereign bonds.

Financial Instruments to Hedge Commodity Price Risk for Developing Countries

Financial Instruments to Hedge Commodity Price Risk for Developing Countries

Market risks and oilfield ownership—Refining oil and gas disclosures

Market risk exposures of balance sheet asset values are becoming an increasingly important accounting issue. In oil and gas, oilfield exposures to oil prices are specific and contractual, presenting a contingency problem for investors, financial analysts, standard setting bodies and government agencies. Our paper uses an extensive sample of 292 oilfields to provide evidence that the US Securities and Exchange Commission (SEC) supplementary disclosures do not capture the price sensitivities of oil and gas disclosures implicit in the two main forms of oilfield ownership, concession and production sharing contracts (PSCs). Current asset disclosures neither distinguish between global variations in oilfield ownership terms, nor on market risk implications for the value of oilfield assets. Importantly, we show that unlike concessions, reserve and production disclosures vary in response to oil price movements for PSC regimes. Our results highlight the need to differentiate PSC disclosures from concession fields, and to fully reflect price risks implicit in oilfield ownership contracts. We extend findings by Rajgopal [1999. Early evidence on the informativeness of the SEC's market risk disclosures: the case of commodity price risk exposure of oil and gas producers. The Accounting Review 74, 251–280] and propose refinements to capture market risk in financial reporting.

Price discovery in a private cash forward market for lumber

Cash forward contracting is a common, and often preferred, means of managing commodity price risk in many industries. Despite this, little is known about the performance of cash forward markets, in particular the role they play in price discovery. The US lumber market provides a unique case for examining this issue. The Bloch Lumber Company maintains an active cash forward market for many lumber products, and publishes benchmark forward prices on their website and disseminates these prices to data vendors. Focusing on 2×4 random lengths lumber and 7/16 oriented strand board, this research examines the lead–lag relationships between the 3-month forward prices published by Bloch Lumber, representative spot prices, and lumber futures prices at the Chicago Mercantile Exchange. Results suggest that at least for 2×4 random lengths lumber, the forward prices published by Block Lumber lead both the spot price and futures price, suggesting that this private cash forward market provides some level of price discovery in the lumber markets.

Hedging Energy Price Risk Using Artificial Neural Networks

This paper provides an empirical study of the effectiveness of hedging energy prices using a neural network model. The hedging effectiveness of the model is investigated using daily crude oil, natural gas, and unleaded gasoline futures prices. Empirical results show that the neural network hedging model is effective in reducing commodity price risks.

The Impact of Commodity Price Risk on Firm Value - An Empirical Analysis of Corporate Commodity Price Exposures

Commodity prices are more volatile than exchange rates and interest rates. Hence, a priori, commodity price risk represents a more important source of risk to corporations. This paper presents a comprehensive analysis of the economic commodity price exposure of a large sample of nonfinancial firms. The results indicate that corporations exhibit net exposures with regard to several commodity prices. Even though commodity prices are highly volatile, commodity price risk is, however, not found to be of greater importance than other financial risks. The results are consistent with few cash flows being affected by commodity price movements, and with corporate hedging of commodity price risk

Does Risk Management Add Value? A Survey of the Evidence

The fact that 92% of the world's 500 largest companies recently reported using derivatives suggests that corporate managers believe financial risk management can increase shareholder value. Surveys of finance academics indicate that they too believe that corporate risk management is, on the whole, a valueadding activity. This article provides an overview of almost 30 years of broadbased, stock-market-oriented academic studies that address one or more of the following questions: •Are interest rate, exchange rate, and commodity price risks reflected in stock price movements? •Is volatility in corporate earnings and cash flows related in a systematic way to corporate market values? •Is the corporate use of derivatives associated with reduced risk and higher market values? The answer to the first question, at least in the case of financial institutions and interest rate risk, is a definite yes; all studies with this focus find that the stock returns of financial firms are clearly sensitive to interest rate changes. The stock returns of industrial companies exhibit no pronounced interest rate exposure (at least as a group), but industrial firms with significant cross-border revenues and costs show considerable sensitivity to exchange rates (although such sensitivity actually appears to be reduced by the size and geographical diversity of the largest multinationals). What's more, the corporate use of derivatives to hedge interest rate and currency exposures appears to be associated with lower sensitivity of stock returns to interest rate and FX changes. But does the resulting reduction in price sensitivity affect value—and, if so, how? Consistent with a widely cited theory that risk management increases value by limiting the corporate “underinvestment problem,” a number of studies show a correlation between lower cash flow volatility and higher corporate investment and market values. The article also cites a small but growing group of studies that show a strong positive association between derivatives use and stock price performance (typically measured using price-to-book ratios). But perhaps the nearest the research comes to establishing causality are two studies—one of companies that hedge FX exposures and another of airlines' hedging of fuel costs—that show that, in industries where hedging with derivatives is common, companies that hedge outperform companies that don't.

Derivative pricing model and time-series approaches to hedging: A comparison

This research compares derivative pricing model and statistical time-series approaches to hedging. The finance literature stresses the former approach, while the applied economics literature has focused on the latter. We compare the out-of-sample hedging effectiveness of the two approaches when hedging commodity price risk using futures contracts. For various methods of parameter estimation and inference, we find that the derivative pricing models cannot out-perform a vector error-correction model with a GARCH error structure. The derivative pricing models’ unpalatable assumption of deterministically evolving futures volatility seems to impede

Cost of Risk Transfer: Pricing Agreements in Residential Supply Chains

Theoretical and computational studies of supply chains are confined mainly to buyer-supplier dyads. Evaluation of more tiers in the construction sector specifically is also rare, perhaps in part because short-term partnerships are typical. However, supplier selection in residential construction is often conducted in support of multiple subdivision tracts over a comparatively long time-horizon. This paper describes the lumber supply chain for residential construction, extending from the homebuyer to the lumber company. A particular case for a real builder is examined in which a builder adopted a pricing strategy to control their lumber cost risk. The strategy included minimum time periods of fixed pricing, insulating the builder from price fluctuations during those periods. Consideration of supply-chain lead times allows financial risk modeling for the builder-framer/lumber yard.lumber company portion of the supply chain in order to evaluate the cost-effectiveness of this strategy. Historical records of lumber prices were used to conduct Monte Carlo simulations of three tiers of the supply chain. The pricing strategy is shown to result in a risk premium generally in excess of the true commodity price risk.

The Impact of Delivery Risk on Optimal Production and Futures Hedging *

Multiple delivery specifications exist on nearly all commodity futures contracts. Sellers are typically allowed to choose among several grades of the underlying commodity. On the delivery day, the futures price converges to the spot price of the cheapest-to-deliver grade rather than to that of the par-delivery grade of the commodity, thereby imposing an additional delivery risk on hedgers. This paper derives the optimal production and futures hedging strategy for a risk-averse competitive firm facing delivery risk. We show that the option value of the multiple delivery specification induces the firm to produce more with than without the delivery risk if the firm gauges this value higher than the market. We further show that if the delivery risk is additively related to the commodity price risk, the firm optimally under-hedges its risk exposure. On the other hand, if the delivery risk is multiplicatively related to the commodity price risk, the firm may optimally choose an under- or over-hedge which we illustrate using a numerical example. JEL classification codes: G11, D21, D81

Price Risk Management Strategies (The Case of Export-oriented Enterprises)

During the period of reforms the majority of Russian raw materials manufacturers has been reoriented at the world markets. The prices of raw materials have high volatility that leads to export incomes' uncertainty. In the article self-insurance and hedging strategies are considered with the purpose of minimizing commodity price risk.

Improving Design and Performance of Group Lending: Suggestions from Burkina Faso

We summarize lessons learned by a credit program for women in Burkina Faso. Three observations are made regarding program design: (a) high membership turnover means mutual guarantee groups should be smaller and more central to nonrepayment penalties; (b) high turnover in economic activities implies more training in best practices and more variety and experimentation in credit and savings mechanisms; and (c) high degrees of stocking activity suggests the need to develop instruments to mitigate commodity price risk at the individual and program level. Three observations are made regarding program implementation: be more consistent in the treatment of debts of deceased borrowers; become more sensitive to the complexity and variety of procedures followed in the event of nonrepayment; and devote more attention to preventing and mitigating the effects of staff embezzlement.

Hedging financial and business risks in agriculture with commodity‐linked loans

One of the particular problems facing agribusiness firms is the relationship between commodity price risk (a source of business risk) and debt repayment ability (a source of financial risk). This study examines the use of commodity‐linked loans applied to agricultural credits. A commodity‐linked loan is a credit instrument whose payoff is contingent on the value of an underlying commodity or portfolio of commodities. The payoff structure includes an option (call or put) rider that provides a payoff if the commodity price rises above or drops below a preset strike price. The payoff is applied directly to the loan. This study introduces the general concept, reviews the literature, and develops and applies a particular model. Simulation results illustrate the interrelationship between options payoffs, strike prices, volatility, and downside financial risk reduction.

The Impact of Delivery Risk on Optimal Production and Futures Hedging

Multiple delivery specifications exist on nearly all commodity futures contracts. Sellers are typically allowed to choose among several grades of the underlying commodity. On the delivery day, the futures price converges to the spot price of the cheapest-to-deliver grade rather than to that of the par-delivery grade of the commodity. This imposes an additional delivery risk on hedgers. This paper derives the optimal production and futures hedging strategy for a risk-averse competitive firm in the presence of delivery risk. We show that, depending on its relative valuation, the delivery option may induce the firm to produce more than in the absence of delivery risk. If delivery risk is additively related to commodity price risk, the firm will under-hedge its exposure to commodity price risk. If delivery risk is multiplicatively related to commodity price risk, the firm will under- or over-hedge this exposure. For constant relative risk aversion, this is illustrated by a numerical example.

Commodity futures markets in LDCs: a review and prospects

Recent moves by the World Bank to devise market-based approaches for dealing with commodity price risk provide a fresh impetus for research in the area of commodity futures markets as a policy option. Since the collapse of the International Commodity Agreements there has been little progress in finding a solution to the perennial problem of price risk arising from price volatility. This paper aims to provide a background to the more general issue of development and growth in less developed countries (LDCs) by examining past and current policy attempts to reduce the effects of price volatility in primary commodity markets.

A COMPARABLES APPROACH TO MEASURING CASHFLOW‐AT‐RISK FOR NON‐FINANCIAL FIRMS

Cashflow‐at‐Risk (C‐FaR) is an attempt to create an analogue to Value at Risk (VaR) that can be used by non‐financial firms to quantify various kinds of risk exposures, including interest rate, exchange rate, and commodity price risks. There are two basic ways to attack this problem. One is from the “bottom up,” which involves building a detailed model of all of a company's specific exposures. The C‐Far approach presented here is a “top‐down” method of comparables that looks directly at the ultimate item of interest—the companies' cashflows. The fundamental challenge facing the top‐down strategy is that, for any one company, there is not enough data on its own cashflows to make precise statements about the likelihood of rare events. To get around this problem, the authors match a target company with a large set of comparable companies that are expected to have similar cashflow volatility. The comparables are chosen to be close to the target company on four dimensions: (1) market cap; (2) profitability; (3) industry risk; and (4) stock price volatility.C‐FaR can be useful to managers addressing a variety of corporate finance decisions. For example, by providing estimates of the probability of financial distress, the C‐FaR method can be used in conjunction with capital structure data to help formulate debt‐equity tradeoffs in a more precise, quantifiable fashion. It can also be used to evaluate a firm's overall risk management strategy, including the expected benefits of using derivatives to hedge commodity‐price exposures or the purchase of insurance policies. Moreover, C‐FaR may even have a use in investor relations: by disclosing the results of a comparables‐based C‐FaR analysis ahead of time, a company may be able to cushion earnings shocks by furnishing investors or analysts with credible, objective estimates of what is likely to happen to their cash flows under different economic scenarios.

An Applied Procedure for Estimating and Simulating Multivariate Empirical (MVE) Probability Distributions In Farm-Level Risk Assessment and Policy Analysis

Simulation as an analytical tool continues to gain popularity in industry, government, and academics. For agricultural economists, the popularity is driven by an increased interest in risk management tools and decision aids on the part of farmers, agribusinesses, and policy makers. Much of the recent interest in risk analysis in agriculture comes from changes in the farm program that ushered in an era of increased uncertainty. With increased planting flexibility and an abundance of insurance and marketing alternatives farmers face the daunting task of sorting out many options in managing the increased risk they face. Like farmers, decision makers throughout the food and fiber industry are seeking ways to understand and manage the increasingly uncertain environment in which they operate. The unique abilities of simulation as a tool in evaluating and presenting risky alternatives together with an expected increase in commodity price risk, as projected by Ray, et al., will likely accelerate the interest in simulation for years to come.

Early Evidence on the Informativeness of the SEC's Market Risk Disclosures: The Case of Commodity Price Risk Exposure of Oil and Gas Producers

The paper provides early evidence on the informativeness of commodity price risk measures required by the Securities and Exchange Commission's new market risk disclosure rules (SEC 1997). I use existing disclosures of oil and gas producers (O&G) to obtain proxies for the tabular and sensitivity analysis disclosures required by the new SEC rules. I find that proxies for the tabular and the sensitivity analysis format are significantly associated with O&G firms' stock return sensitivities to oil and gas price movements. This finding casts doubt on claims that the new market risk disclosures do not reflect firms' risk exposures. The proxies for the tabular format and sensitivity format disclosures are not substitutable explanations of firms' risk exposures. This evidence suggests that disclosures from one disclosure format are not comparable to those from the other reporting format.