Commodity Price Risk Definition
Commodity price risk refers to financial losses that may occur to both the consumer, and the producer when there is a change in commodity prices. A risk for the buyers is that the prices for commodities may be high. Take an example of the carpenters. They have to buy wood to make furniture. If the wood prices go up, it will also mean that the costs of buying furniture will be higher. The producers will have lower profits because there will be few buyers.
A Little More on What is Classification of Commodity Price Risk
Generally, producers face the risk of low commodity prices. For instance, if in the first year of planting the prices of crops are high, the farmer plants more hoping for higher profit margins. What will happen when the prices suddenly fall? The farmer makes losses.
Commodity price risk does not happen just like that. Factors including weather, technology, politics, market conditions, and seasons affect commodity prices. Financial instruments like futures and options are now in the market to control commodity price risk.
Groups affected by commodity price risk
- Producers including farmers, mining companies, oil companies, and car manufacturers face price risks on their production inputs
- Consumers face price risk when the prices go up as this affects their demand for commodities
- Imposing tariffs on exports causes prices to go up. Exporters also experience hardship in the markets when this happens
- Governments face price risks, especially when it comes to revenue generation. An increase in prices causes the government to generate more revenue
Factors affecting commodity prices
An increase or decrease in commodity prices can occur due to political factors. In the USA, for example, manufacturers import steel and aluminum from foreign countries. In 2018, President Trump imposed tariffs on the imports. The tariffs’ goal was to increase the prices of aluminum, and steel in the USA compared to other countries.
China did not take this lightly. They later imposed their tariffs on agricultural products from the US. The low demand for agricultural produce from China meant the crops had to be bought by other countries. As a result, the crop prices in the US market reduced in 2019.
- Weather conditions
Change in seasons and weather conditions largely affect the prices of commodities. Farmers harvest plenty of farm produce towards the end of summer, making prices fall in October. The fluctuation of prices during the major seasons’ causes crashes in the stock market. Seasons like drought and floods temporarily lead to a hike in the prices of commodities.
- Transportation and storage costs
The type of commodity will determine its storage mechanism. The commodities that have a physical form need storage spaces before distribution. The cost of storage always affects the overall price of a commodity.
Technology has an intense impact on commodity prices. Improvements in technology can cause the prices of a commodity to drop. Take an example of aluminum. It was a valuable metal until new procedures were developed to isolate it. Its value then dropped, and its price in the market decreased.
- Production costs
Capital, labor patterns, raw materials, and production tools have a great influence on the commodity’s final price. If the cost of production is high, the commodity price will also be high. However, if the production cost is low, the commodity price will be low.
Using hedging futures to control the prices of a commodity
Futures markets protect consumers and producers against price fluctuations. A producer faces the risk of prices going down, while consumers face the risk of prices hiking. Hedging protects both parties against financial loss. Futures contracts have periods, and consumers and producers get to choose according to the risks they face. Investors, traders, speculators, and other people in the market can use the futures markets.
References for Commodity Price Risk
Academic Research for Commodity Price Risk
Early evidence on the informativeness of the SEC’s market risk disclosures: The case of commodity price risk exposure of oil and gas producers, Rajgopal, S. (1999). The Accounting Review, 74(3), 251-280. This article proves the knowledge of commodity price risk measures, the rules of the SEC (Securities & Exchange Commission) about the new market risk disclosure. The author uses oil and gas producers’ disclosures to get proxies for the sensitivity and tabular analysis disclosures, the new SEC rules require. The findings are that these are highly attached to stock return sensitivity of O&G firms to their price movements. These proxies cannot be substitutable explanations of risk exposures of firms. So, the author provides evidence that disclosures from one format cannot be compared to other reporting formats.
The effect of mandated market risk disclosures on trading volume sensitivity to interest rate, exchange rate, and commodity price movements, Linsmeier, T. J., Thornton, D. B., Venkatachalam, M., & Welker, M. (2002). The Accounting Review, 77(2), 343-377. This paper is based on a hypothesis that 10-K market risk disclosures of firms, which the SEC Financial Reporting Release Number 48 (FRR) mandated recently, decrease opinion diversity regarding the implications and uncertainty of investors. The authors argue that these decrements should dampen the sensitivity of trading volume to changes in underlying market prices. The findings are that after firms disclosure of mandates information FRR-48 about their exposure to interest rate, energy prices, foreign currency exchange rate, the sensitivity of trading volume to changes in the market rates decreases, even after one controls the associated factors.
On price risk and the inverse farm size-productivity relationship, Barrett, C. B. (1996). Journal of Development Economics, 51(2), 193-215. Productivity and farm size have an inverse relationship with each other. It has elicited many explanations with theoretical implications. This paper uses advanced analysis of price risk impacts on behaviour of the producer and a simple 2-period model of an agricultural household which produces and consumes when the price is uncertain and labour allocation is being decided. The author analytically shows that price risk and a non-degenerated land distribution produce together an inverse relationship. There is empirical evidence from Madagascar which confirms the validity of this intuitive elaboration for the phenomenon.
The Impact of Commodity Price Risk on Firm Value–An Empirical Analysis of Corporate Commodity Price Exposures, Bartram, S. M. (2015). Commodity prices have more validity as compared to interest rates and exchange rates. Therefore a priori, the price risk of a commodity represents a significant mean of risk to corporations. This paper makes a comprehensive analysis of the price exposure of the economic commodity from a large sample of non-financial companies. The findings are that the corporations show net exposures regarding many commodity prices. Though commodity prices have high volatility, however, their risk is not as much important as other financial risks are. There is consistency in results with corporate hedging of risk of commodity price and cash flows influenced by movements in the commodity prices.
A strategy for managing commodity price risk, Zsidisin, G. A., & Hartley, J. L. (2012). Supply Chain Management Review, 16(2). This paper presents a strategy to manage the price risk associated with every commodity. Every firm is affected by price changes attached to the commodities, it obtains for its operations. Such movements in the price can have detrimental effects on cash flow, budgeting, the overall performance of the organization and profitability. In this paper, the authors introduce a flexible process to be implemented by the companies to control the volatility of the commodity price. For this, one needs to understand one’s risk tolerance level and risk exposure.
Commodity derivatives and price risk management: An empirical anecdote from India, Lokare, S. M. (2007). Reserve Bank of India Occasional Papers, 28(2), 27-77. This research aims to evaluate the performance and efficiency of commodity derivatives in directing how to manage the price risk. Though the markets are yet to obtain least critical liquidity, all the commodities throw co-integration evidence in future and spot prices, presaging that the markets are going to march in the right direction of obtaining better operational efficiency. However, the future price volatility of some commodities is substantially lesser as compared to the spot price. This shows the inefficient use of information. Many commodities attract speculative trading widely. Hedging is an effective suggestion in case of some commodities whereas others entail significantly higher or moderate risk.
The theory of commodity price stabilisation rules: Welfare impacts and supply responses, Newbery, D. M., & Stiglitz, J. E. (1979). The Economic Journal, 89(356), 799-817. The stabilization schemes of commodity price are topical. This paper investigates their operation using a more realistic approach. Common assumptions are relaxed, e.g. linear curves of supply and demand with additive stochastic disruptions, welfare assumptions, costless perfect price stabilization, ex-ante ex-post supply curves, no measure of stabilizing price welfare effects, same attitude to risk exposed by all the farmers, producers fail to react and learn the varying average returns causing due to stabilization schemes, etc. It may be hard to assess the buffer stock schemes desirability without knowing specific critical parameters, e.g. the elasticity of demand and effort response, but it can quantify the advantages of price stabilization even with a more difficult model.
The theory of hedging and speculation in commodity futures, Johnson, L. L. (1960). The Review of Economic Studies, 27(3), 139-151. Though considerable contributions have been made in these years, today’s approach of speculation and hedging accounts for specific market practices inadequately. Particularly, the trader’s motivation who takes the responsibility of hedging, the role of hedging in all market operations and the difference between a trader who speculates and the one who hedges have increased difficulties. This paper aims to highlight the objective and mechanics of the future market of a commodity, appraise and discuss the latest approach of speculation and hedging, to propose a reformulated idea of hedging and to build a model that can help in clarifying the concepts of speculation and hedging.
Competitive storage and commodity price dynamics, Deaton, A., & Laroque, G. (1996). Journal of Political Economy, 104(5), 896-923. The risk-neutral commodity speculators can make the commodity prices smooth by purchasing cheap and selling dear and induce price serial dependence even under the simple forces of supply and demand. Commodity prices keep changing and are positively correlated from 1 year to the successive one. The supply factors often explain the variability and the speculators’ activities explain the autocorrelation. The authors prove that there is no consistency of this explanation with the evidence. The speculation can raise substantial auto-correlation for prices, weakly auto-correlated in the absence of speculation but not as high as noticed in the data.
Agricultural liberalization policy and commodity price volatility: a GARCH application, Yang, J., Haigh, M. S., & Leatham, D. J. (2001). Applied Economics Letters, 8(9), 593-598. This article examines the impact of the latest radical agricultural liberalization policy, that is, the Fair Act 1996, on the volatility of agricultural commodity price with the help of GARCH models (Generalized Autoregressive Conditional Heteroscedasticity). The findings are that the agricultural liberalization policy leads to increase the price volatility for 3 main grain commodities, i.e. wheat, corn and soybeans and minor changes for oats but a decline in cotton. These results oppose Crain & Lee’s findings in 1996 on the basis of wheat markets. These measures in State Farm policies are likely to decrease the volatility of the agricultural price.
Volatility and commodity price dynamics, Pindyck, R. S. (2004). Journal of Futures Markets: Futures, Options, and Other Derivative Products, 24(11), 1029-1047. Commodity prices are likely to be volatile and volatility changes with the passage of time. The volatility changes may influence market variables by influencing the storage marginal value and by influencing an element of the productions’ overall marginal cost. The opportunity cost of option exercising to produce the commodity today instead of looking for more price information. The author evaluates the volatility role in the dynamics of the short-run commodity market and the volatility determinants, itself. Particularly, he develops a model explaining the combined dynamics of inventories, volatility and future and spot prices. He computes it with the help of daily and weekly information for the petroleum company: gasoline, crude oil and heating oil.