Volume risk

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Example

An electricity retailer cannot accurately predict the demand of all households for a given time which is why the producer cannot forecast the precise time that a power plant will provide more electricity that consumed, even if the plant always delivers the same output of energy.

Volume risk, also known as quantity risk, is the risk of production or sales volumes materially and adversely deviating from their expected quantities. [1] [2] It is context-specific.

As regards commodity risk, [3] a major concern is yield risk, which is the uncertainty regarding production fearing insufficient quantities of the respective commodity mined, extracted or otherwise produced. A participant here further faces uncertainty concerning demand, where large deviations from the forecasted volume may be caused, for example, by unseasonal weather impacting gas consumption. Other concerns include [4] plant availability, collective customer outrage, and regulatory interventions. These changes in supply and demand often result in market volatility. [2] Producers here are relatedly subject to price risk, [5] although in a narrower sense than usually employed.

In the context of business risk, volume risk relates primarily to revenue, where deviation from budget may be due to external or internal factors. [1] Internal factors, such as insufficient human capital and plant aging, may negate the business line's ability to execute the operational or business plan. External factors comprise primarily of the competitive landscape. [1] A public–private partnership (PPP), carries what is there referred to as "revenue risk". [6]

Risk management entails [2] formally modeling demand and responding dynamically (if not preemptively) to the market. Scenario planning may explicitly incorporate varying levels of demand. [7] For PPPs, a tax-supported minimum revenue guarantee (MRG), may be provided by the (local) government. [8] [9] Regarding production uncertainty, an approach often taken is to diversify spatially; [5] it may also be possible to allow for contingencies in plant availability.

However, direct hedging becomes difficult [10] when the quantity is uncertain, particularly where the underlying commodity is not storable. One approach is to hedge against fluctuations in total, [10] i.e. quantity times price. Various strategies have been developed using, for example, weather derivatives [11] and electricity options. [10] At the same time, producers and their customers regularly hedge against price risk using [12] available commodity derivatives. Commodity traders will similarly have hedges in place for the resultant market and volatility risk.

See also

Related Research Articles

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Volatility risk is the risk of an adverse change of price, due to changes in the volatility of a factor affecting that price. It usually applies to derivative instruments, and their portfolios, where the volatility of the underlying asset is a major influencer of option prices. It is also relevant to portfolios of basic assets, and to foreign currency trading.

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<span class="mw-page-title-main">Tokyo Commodity Exchange</span>

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<span class="mw-page-title-main">Bullwhip effect</span> Form of distribution marketing

The bullwhip effect is a supply chain phenomenon where orders to suppliers tend to have a larger variability than sales to buyers, which results in an amplified demand variability upstream. In part, this results in increasing swings in inventory in response to shifts in consumer demand as one moves further up the supply chain. The concept first appeared in Jay Forrester's Industrial Dynamics (1961) and thus it is also known as the Forrester effect. It has been described as "the observed propensity for material orders to be more variable than demand signals and for this variability to increase the further upstream a company is in a supply chain". Research at Stanford University helped incorporate the concept into supply chain vernacular using a story about Volvo. Suffering a glut in green cars, sales and marketing developed a program to sell the excess inventory. While successful in generating the desired market pull, manufacturing did not know about the promotional plans. Instead, they read the increase in sales as an indication of growing demand for green cars and ramped up production.

<span class="mw-page-title-main">VIX</span> Volatility index

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Foreign exchange risk is a financial risk that exists when a financial transaction is denominated in a currency other than the domestic currency of the company. The exchange risk arises when there is a risk of an unfavourable change in exchange rate between the domestic currency and the denominated currency before the date when the transaction is completed.

<span class="mw-page-title-main">Demand</span> Concept in economics

In economics, demand is the quantity of a good that consumers are willing and able to purchase at various prices during a given time. In economics "demand" for a commodity is not the same thing as "desire" for it. It refers to both the desire to purchase and the ability to pay for a commodity.

The following outline is provided as an overview of and topical guide to finance:

Revenue management (RM) is a discipline to maximize profit by optimizing rate (ADR) and occupancy (Occ). In its day to day application the maximization of Revenue per Available Room (RevPAR) is paramount. It is seen by some as synonymous with yield management.

<span class="mw-page-title-main">Volatility (finance)</span> Degree of variation of a trading price series over time

In finance, volatility is the degree of variation of a trading price series over time, usually measured by the standard deviation of logarithmic returns.

Weather risk management is a type of risk management done by organizations to address potential financial losses caused by unusual weather.

<span class="mw-page-title-main">Electricity pricing</span>

Electricity pricing can vary widely by country or by locality within a country. Electricity prices are dependent on many factors, such as the price of power generation, government taxes or subsidies, CO
2 taxes, local weather patterns, transmission and distribution infrastructure, and multi-tiered industry regulation. The pricing or tariffs can also differ depending on the customer-base, typically by residential, commercial, and industrial connections.

Channel coordination aims at improving supply chain performance by aligning the plans and the objectives of individual enterprises. It usually focuses on inventory management and ordering decisions in distributed inter-company settings. Channel coordination models may involve multi-echelon inventory theory, multiple decision makers, asymmetric information, as well as recent paradigms of manufacturing, such as mass customization, short product life-cycles, outsourcing and delayed differentiation. The theoretical foundations of the coordination are based chiefly on the contract theory. The problem of channel coordination was first modeled and analyzed by Anantasubramania Kumar in 1992.

Energy forecasting includes forecasting demand (load) and price of electricity, fossil fuels and renewable energy sources. Forecasting can be both expected price value and probabilistic forecasting.

References

  1. 1 2 3 Volume Risk, openriskmanual.org
  2. 1 2 3 Volume Risk, capital.com
  3. ↑ Kandl, Peter; Studer, Gerold (January 2001). "Factoring in volume risk". Risk Magazine: 84f. Retrieved 23 October 2015.
  4. ↑ Pellegrino, R.; Tauro, D. (March 27, 2018). "Supply Chain Finance: A supply chain-oriented perspective to mitigate commodity risk and pricing volatility (in press)". Journal of Purchasing and Supply Management . doi:10.1016/j.pursup.2018.03.004. S2CID   169679135.
  5. 1 2 Volume Risk and Price Risk, TAS Royalty Company
  6. ↑ Revenue Risk, APM Group
  7. ↑ Jay Ogilvy (2015). "Scenario Planning and Strategic Forecasting", forbes.com
  8. ↑ International Monetary Fund (2019). "PPP Fiscal Risk Assessment Model"
  9. ↑ Global Infrastructure Hub (2016). "Allocating Risks in Public-Private Partnership Contracts"
  10. 1 2 3 Yumi Oum, Shmuel Oren, Shijie Deng (2006). "Hedging Quantity Risks with Standard Power Options in a Competitive Wholesale Electricity Market". Naval Research Logistics. Vol. 53.
  11. ↑ Takuji Matsumoto, Yuji Yamada (2021). "Simultaneous hedging strategy for price and volume risks in electricity businesses using energy and weather derivatives". Energy Economics. Volume 95, March 2021
  12. ↑ Bloomberg.com (2022). 5 things new commodities hedgers need to know
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