Price Risk Management in the Energy Industry: The Value at Risk Approach Alessandro Mauro, alessandro.mauro@gmail.com Paper presented to the XXII Annual International Conference of the International Association for Energy Economics, 9-12 June 1999, Rome Introduction It is well known that major breakthroughs in oil supply, starting from the 70s, have led to a considerable amount of volatility in oil prices Nowadays other sectors of the energy industry are undergoing major structural changes The result on prices will probably be similar, giving place to a new competitive environment A primary step for market actors will be the measurement of new price risk exposure A modern way to consider this issue is the Value at Risk (VaR) approach The utilisation of a VaR framework to assess price risk is widely diffused in financial institutions, where profits and losses are calculated daily (“marking-to-market”) VaR is not widespread in non-financial firms, because they not frequently perform marking-to-market on their assets Regardless, VaR seems appropriate for industrial firms whose revenues and monetary costs usually fluctuate due to volatility in prices, particularly in a short time horizon In this paper we show how VaR can be used to measure price risk exposure in the energy sector We start by introducing some principal theoretical facts about VaR, utilising it to calculate risk exposure in the refining industry We then investigate the conditions that imply price risk arising in the energy sector That enables us to understand where, in the near future, actors will need price risk management using VaR A further analysis of the gas sector demonstrates that also in a bundled supply chain there is already a certain amount of price risk, due to the formula prices used Liberalisation could introduce different scenarios regarding the amount of volatility in prices, and this point is analysed for power generation, where interfuel competition will be crucial Finally we extend the VaR concept to old and new supply of energy sources; producers, following either a passive or an active supply strategy, will soon need risk measurement tools 2 Value at Risk: a theoretical framework Value at Risk represents the maximum expected loss in the value of an activity due to an adverse movement in price The VaR is calculated with reference to a statistical confidence level and a holding period The simplest way to obtain a VaR measure is to suppose that return of the activity is normally distributed (“parametric approach”) In this case the daily VaR is VaR = α c Xσ R α [1] is a known function of the confidence level; X is the market value position at the time of calculation, that is quantity per price; σ R is the daily standard deviation of the return of the activity and it is the only parameter that must be estimated in some way One can expect that under normal market conditions, in the c% of the total cases, the maximum loss in the value of the activity will not exceed the VaR figure A VaR calculation for a portfolio of activities can also be easily performed; assuming that returns of all the activities are normally distributed, the VaR is [Dowd (1998)] C VaR = n n i =1 j =1 ∑ ∑ ρ VaR VaR ij i j [2] where ρ ij is the correlation coefficient between returns on activity i and activity j, and the individual VaR are calculated using [1] The role of correlations is crucial If ρ ij = 1, prices of two activities always move together; in this case, total VaR is simply (VaR1 + VaR2 ) This is not a good situation from the point of view of price risk management, because risks are additive Instead, if ρ ij < , VaR < (VaR1 + VaR2 ) , showing that there is a diversification benefit when activities are not perfectly correlated1 Both [1] and [2] demonstrate the principal advantage of VaR utilisation It summarises in a single measure the price risk associated with many activities and many business units composing a company VaR is easy to understand and communicate, also outside the company With VaR one can easily assess the impact of new regulation, as we will show in this paper However, we must note that VaR has some limitations, the most important being the assumptions that must be made about price behaviour of the activities composing the portfolio VaR for price risk management in refining The refining industry is one of the most clear examples of a nonfinancial sector widely exposed to price risk, where VaR can be successful implemented We therefore introduce VaR using well known cases taken from this industry As a first example, let us consider crude Brent, contracted in a competitive market and whose price fluctuates every day VaR figures are reported in the following table2 Table Brent VaR $/bbl $/t (% of m.v.) daily days 30 days 0,43 0,97 2,36 3,59 8,02 19,65 (3,95%) (8,82%) (21,61%) Percent VaR referred to market value (m.v.), that is VaR/X in the terms of [1], is very useful for comparing VaRs expressed in different unit measures If the refiner is committed to buy one million bbl of Brent tomorrow, the maximum expected loss he will suffer (due to a price increase) is 430.000$ This corresponds to 3,95% of today’s Brent market value As you know, the effective price in a oil transaction will be set as a mean of prices of more than one day; it is quite simple to take into account this case If the refiner has bought oil, with a price that will be calculated as a simple mean of five quotations, the total VaR will be the five days VaR, using σ R as total standard deviation3; on one million bbl, VaR will be 970.000$ It is simple to take further steps to arrive closer to reality The refiner will not use only Brent as input, but also many other crudes Utilising [2] one can always calculate the total VaR, starting from single VaRs and correlations These correlations are never perfect [Weiner (1996)], so there will always be a diversification benefit: the refiner should buy different types of crudes in order to reduce price risk As far as refined products are concerned, the refiner again faces price risk due to daily quotation In this case, in contrast to crudes, the refiner will be concerned about price falling The VaR calculation is again straightforward; for example, the VaR for gas oil and fuel oil (low and high Sulphur content) are Table daily days 30 days Products VaR gas oil $/t (% of m.v.) LSFO $/t (% of m.v.) HSFO $/t (% of m.v.) 3,12 6,97 17,08 (2,88%) (6,44%) (15,78%) 1,68 3,76 9,20 (2,13%) (4,77%) (11,68%) 2,32 5,20 12,73 (3,83%) (8,55%) (20,95%) This VaR calculations show that Brent oil purchases is more risky that products sales At the same time, LSFO is about 25% less risky than HSFO The final step is to aggregate crudes and products in VaR calculation This is simply done utilising [2], where buying positions (crudes) and selling positions (products) have different algebraic signs The need for price risk management in the energy industry: unbundling & commoditization Will it be possible to apply the VaR approach to the rest of the energy industry in the future? In this paragraph we investigate what market conditions define the environment for successful application The principal factor is the existence of a certain degree of volatility in prices Only in this case a risk management system is needed A much greater price volatility in the energy industry is very likely in the near future This is due to some major structural changes already taking place The first one is unbundling Vertically integrated structures, characterising the supply chain in the gas and the electricity industry, are beginning to break up, mainly as an impact of new regulation One of the results of this de-integration of the chain is the substitution of the internal flows of goods and services with transactions that have to be accomplished in open markets, with freely contracted prices taking the place of internal prices of transfer For every new breaking-up of the supply chain, a new market potentially arises In any case, unbundling is a necessary but not sufficient condition for price risk arising in the energy industry In this light, regulation is crucial For instance, regulated tariffs will show small or no price risk, also in a unbundled market This is the case of energy sold to consumers not free to choose the supplier Other examples are tariffs set for carriage of gas or electricity through a transmission system Also in liberalised markets, as the U.S and U.K., there is not a real market for these kind of services Regulators fix tariffs which depend on objective conditions It is clear that there is not a price risk arising here and therefore the VaR procedure cannot be applied In both cases, the rational for regulation is well known In the first case there is the “public service view”: a freely determined price would create damage to some individuals that instead need protection In the second case, there is also the well known circumstance that transportation of gas and electricity is a natural monopoly: it is impossible to create a competitive market and so it is better to regulate price and access conditions to infracstuctures The conclusion is that new amounts of regulation will not necessarily bring new amount of price risk to be managed The fulfilment of the public service view as well as technological characteristics create obstacle to the commoditization of energy A good example of commoditization is again the oil-products market There, standardisation of contracts (e.g lots, quality, etc.) has created the increase of transactions, liquidity and price volatility In contrast to unbundling, commoditization is a sufficient but not necessary condition for the existence of price risk In fact, let us consider the case of the price of an energy set, in the absence of commoditization, with reference to energy commodities prices The results is uncertainty in prices, not due however to the existence of a competitive market for the good We consider this situation in paragraph In order to better understand the analysis on the next pages, it will be useful to take a look at the following figure Fig Gas oil Fuel oil Oil REFINING GAS MERCHANT Gas Coal POWER GENERATION FINAL USERS LDC physical flow price link We have distinguished physical flows of goods (primary sources and refined products) from “price links” arising whenever there is indexation Natural gas industry: VaR in absence of commoditization Continental Europe gas merchants buy the gas from national and foreigner producers They pay a price indexed to prices of crudes and/or refined products At the same time, they sell the gas (mainly to local distributors, power generators and industries) with similar price formulas The principal aim of this practice is to keep gas competitive in comparison to substitutes in final markets Thanks to this kind of assurance, the construction of big infrastructures has been possible But what about price risk? Let us analyse the case of the Italian gas chain Formulas for the gas sold (so current gas prices), vary depending on the type of buyer Let us consider the case of the gas sold to electricity generators It is composed of a fixed term (so with a VaR equal to zero) and the floating term TE = 195* IND (Itl/m3), where IND is a three month average of this kind Gas Oili Crudesi LSFOi IND = 0,3 * + 0,3 * + 0,3 * + 0,1 KG KC KL [3] The Ks are constants and the other terms are stochastic It is obvious, from the point of view of price risk, that the supplier is selling gas oil, crudes and LSFO, instead of gas This is the present situation in Europe; gas is not sold as gas, but as crudes and refined products (see fig.1) Considering Value at Risk, TE is a portfolio composed of three activities Using again [2], VaR figures, calculated at the end of August ‘98 for gas that would be bought in October ‘98, are reported below4 Table TE VaR monthly 3 on one m on 3,3 Mm as % of TE 15,96 Itl 53.186.047 Itl 10,49% This VaR calculation demonstrates that also for uncommoditized energy there is a relevant quantity of price risk already in place The lack of a price risk assessment of this kind could lead to an undervaluation of the necessity of a price risk management procedure Actors in the gas industry should not wait until final liberalisation of the market to understand their risk profile and eventually hedge risk exposure In the short run, gas merchants and utilities in the continent will take advantage of arbitrage opportunities offered by U.K liberalised market through the Interconnector [International Petroleum Exchange (1998)] In the long run, a new environment will arise due to the EU gas directive If the opening of the market will really lead to transactions and price quotation on a daily basis, price risk exposure will surely change Let us again take a look at tables and If gas market conditions will resemble those of crudes, we can state that price risk in the gas sector will probably increase VaR could play a more fundamental role in this riskier environment Power generation industry To analyse current and future price risk exposure in power generation and the possible applications of VaR, we must distinguish between inputs (fuel) and outputs (electricity generated) As far as inputs are concerned, here we consider fuel oil, coal and natural gas (see fig.1) Fuel oil is already contracted on free markets, and we know price risk exposure in terms of VaR (table 2) Clearly LSFO costs (and probably will continue to cost) more that HSFO, due to the different Sulphur content So the power generator could choose to utilise HSFO in combination with a technology of S02 emissions abatement But what about risk? Calculations in table demonstrates that HSFO is much riskier than LSFO, the differential VaR being about 0,6 $/t on daily basis An analogous analysis applies to coal; calculations should show if different qualities of coal present different VaRs, as for the fuel oil case As far as gas is concerned, we stated previously the influence of current and prospective market conditions on VaR applicability At present, confronting monthly percent data in table and 3, gas appear less risky than fuel oil in Italy This is due to the diversification benefit implicit in a price formula like [3] The first result of interfuel competition will be an alignment of the prices of these energy sources on a Btu basis So, other things equal, a multifuel power generator should choose the fuel presenting the smallest VaR figure If he will really switch from one fuel to another, in a time horizon longer than one day, he will hold a sort of fuels portfolio and the total VaR will be easily calculated with [2] Nevertheless, VaR inputs figure will be only a incomplete measure of price risk exposure in power generation In order to obtain the overall exposure, we must consider also potential volatility in electricity prices So let us consider the output side of the industry Electricity, with respect to gas, is some steps ahead in the way towards liberalisation in continental Europe This sector shows how the necessity of risk management will depend on the behaviour of market actors There will be countries where all the electricity will be exchanged in a free market, while there will be others that will retain a part of unliberalised market, for the energy supplied to “non-eligible” customers Probably the price will be indexed to commodities or to free electricity markets; we have already shown, for the gas case, the application of VaR in such framework The US case is useful to understand what already happens in a free electricity market and, at the same time, what will happen in the eligible part of the European market The price of electricity is very volatile, probably due to the non storable nature of the good This is the ideal situation to utilise VaR; the calculation is straightforward If an utility is committed to sell electricity, for h hours at a delivery rate of w megawatts per hour, market value in terms of [1] is X=hwP, where P is the actual current price of electricity So the total VaR for this contract is [Leong-Siddiqui (1998)] VaR = α c ( hwP) σ R elect [4] The US experience shows that liberalisation does not necessary mean a higher volatility of cash flows for all market actors In fact they can choose to give away all the risk to so called “power marketers” [Altman-Sioshansi (1998)] A financial instrument created to fulfil such result is the “spark spread”, by which the price of electricity is linked to input fuel prices In any case, also in this kind of environment there is space for VaR application, as power marketers will need, in turn, to measure price risk exposure due to the offered services VaR for old and new supply of energy The main topic regarding new supply is the availability of infrastructures for production and transportation in final markets Profitability and therefore realisation of projects depends also on marketing issues The method of pricing could foster a successful marketing strategy VaR will be useful to assess risk exposure of producers and buyers Let us take a look again at the world of oil supply Nowadays the price of many crudes is linked with a formula to the price of a few others, known as “benchmarks” For example, the price of Libyan Es Sider is simply the price of Brent minus a correction factor [PIW (1999)] This is optimal from the point of view of risk management: the buyer can hedge price fluctuations of Es Sider by hedging on Brent5 In fact the VaR of Es Sider will be quite the same as the Brent VaR, and we know that the maximum daily loss is 3,59 $/t (table 1) It is crucial to guarantee the buyer a way of pricing linked to final market conditions In fact, there will be a sort of insurance against price fluctuations, implicit in the pricing Producers will beat rivals if they will be able to introduce innovative pricing that meet the needs of price risk management of customers Producers can go further this way, utilising multiple benchmarking on crudes and products; this is the case, for example, of Mexican crude Isthmus [PIW (1999)] Probably the most extreme situation when producers meet the needs of buyers is with netback contracts In this case, the price of oil is determined by the Gross Production Worth (GPW) of refined products in the buyer market The price of the crude is calculated as P = GPW - costs (refining, transport) - netback margin [5] The refiner transfers the risk to the producer, locking in a fixed netback margin on every ton of crude bought The producer will gain market share, sustaining all the risk of an adverse movement in the refining market (instead of crudes market) How can he state how big is the risk? How can he make comparisons? To give an answer, he must have a risk measure Using VaR, the answer is straightforward If costs and netback margin are constant, VaR(P)=VaR(GPW); considering the GPW of a complex refinery processing Brent, the daily VaR is 2,5$/t The supplier will gain market shares with a less risky position: simply benchmarking to Brent has a daily VaR of 3,6$/t (table 1) In order to assume a more active role in the market, the producer could choose to refine the crude by himself, directly selling the refined products This could be a good strategy: it would allow him to appropriate the netback margin (see [5]), at the same VaR of selling crude with netback contracts However, this is true only assuming once more the utilisation of a complex refinery But there are areas of the world where technology is not so up-todate, where they will use a hydroskimming process It is well known that running this kind of refinery will mean a smaller GPW, due to the large proportion of heavy distillates produced At the same time, a VaR analysis shows that operating with this kind of refinery will be less risky: Table daily VaR $/ t (as % of GPW) Complex Hydroskimming 2,55 2,33% 2,04 2,04% For every ton of crude processed, the producer-refiner will sustain Values at Risk that can differ of about 0,5$: hydroskimming is nearly 25 % less risky than complex refinery So VaR can be useful to identify riskiness in an active supply strategy for oil producers Maintaining a “passive” strategy, there will probably be a change in price risk exposure for producers, because of new pressures arising in final markets The Italian gas market can again give us an example The price of the gas sold by the gas merchant to the local distribution companies (LDCs) is determined, as we know, with a formula Like the power generation case, there is a floating component, whose price is currently linked only to the gas oil price Recently, the Italian regulation authority proposed a change in the formula, introducing this kind of indexation6: It = α Gas Oilt LSFOt Crudest +β +γ +δ Gas Oil0 LSFO0 Crudes0 [6] Risk exposure of LDCs will not change, as they will be allowed to pass on these costs to final consumers (see fig.1) On the contrary, for the gas merchant, the proposed change in indexation would change the actual risk profile A number of questions naturally arise How risky is the present situation? And the new potential one? Is it necessary to hedge new risk exposure? If the new situation is unacceptable risky, an option for the gas merchant could be to try to re-negotiate long term contracts with producers, proposing new rules and indexations So the previous questions apply also to the gas producer In the end, a new environment arising in just a segment of the final market, can easily spread to create consequences for producers We have demonstrated that market pressures will arise also in the short run, in the absence of full liberalisation of the continental gas market It is already time to establish a sound risk management procedure, at every level of the gas chain, aiming at assessing price risk exposure Value at Risk approach is capable of performing all of the necessary analyses Endnotes This is true if the portfolio contains only buying (or selling) positions; see Smithson (1997), pp.462-463 All calculations in the paper are performed on data collected from Price Assessments tables in Platt’s Oilgram Price Report; data range is 1/’969/’98 Confidence level is always 95%, standard deviations and correlations are historical ones Returns are calculated as relative variations of prices Quantities are measured in metric tons (t) or barrels (bbl) This is true if some hypotheses hold; see Iacono-Skeie (1996) At the end of August ‘98 there were uncertainty only on September prices so, equivalently, on 1/3 of the total quantity (here 10 Mm3) bought in October ‘98 Moreover, while the voice Crudes in [3] refers to eight crudes, we utilised only Brent in calculations Weiner (1996) investigates the real effectiveness of this kind of hedging Fixed weights were not established [Autorità per l’energia elettrica e il gas (1999)] References Altman, A.M., Sioshansi, F.P., (1998), Implication of Power Marketing in The Restructured Electricity Market, Electric Power Research Institute Autorità per l’energia elettrica e il gas, (1999), Criteri per l’indicizzazione delle tariffe, per la parte del costo della materia prima, nei servizi di fornitura di gas attraverso reti urbane, February Dowd, K, (1998), Beyond Value at Risk The New Science of Risk Management, John Wiley & Sons International Petroleum Exchange, (1998), Natural Gas Trading in Europe: Liberalisation and its Impact on Long-term Contracts Iacono, F., Skeie, D., (1996), “Translating VaR Using SQRT(T)”, Derivatives Week, October 14 Leong, K., Siddiqui, R., (1998), “Value at Risk for Power Markets”, in P.C Fusaro (ed.), Energy Risk Management, McGraw-Hill PIW (1999), Petroleum Intelligence Weekly, Special Supplement, vol XXXVII, n.4, January 25 Smithson, C.W., (1997), Managing Financial Risk, McGraw-Hill Weiner, R.J., (1996), “Middle East Crude Oil Pricing and Risk Management in The 1990s: An Exploratory Investigation”, Journal of Energy Finance and Development, vol.1, n.1, pp.21-49 Acknowledgements The preparation of this paper was supported by the aid of Giorgio Crespi, Lorenzo Furia, Regina Jain, Elisa Molinari, Arnaldo Orlandini, Vincenzo Soprano Only public information was used Opinions and eventual errors are those of the author ... and refined products) from “price links” arising whenever there is indexation Natural gas industry: VaR in absence of commoditization Continental Europe gas merchants buy the gas from national... more active role in the market, the producer could choose to refine the crude by himself, directly selling the refined products This could be a good strategy: it would allow him to appropriate the... where they will use a hydroskimming process It is well known that running this kind of refinery will mean a smaller GPW, due to the large proportion of heavy distillates produced At the same time,