FEATURES: INFORMATION SERVICES 
Physical benchmarksin an on-line world Startup on-line commodity exchanges seem not to realize that there are several good reasons why benchmarks derived from volumetric indices may not work--and may not be useful--for physical products, such as oil and petrochemicals. But there are other routes to price discovery 
By Neil Fleming 

Apr. 1, 2001 
Global Energy Business 
Page 37 
Copyright 2001 McGraw-Hill, Inc. 

Somewhere near 500 Internet-based exchanges for energy, oil, petrochemicals, and hydrocarbon shipping have been launched worldwide over the past two years. But most have since folded or been acquired. It's interesting to note that virtually all of those exchanges--both the survivors and the deceased--have two things in common. -- They were created from scratch by entrepreneurs from the technology world, or from the industries their exchanges are (or were) intended to serve. -- The businessmen and women behind them have followed the same train of thought in concluding that on-line trading was a business they could succeed at. 

This train of thought can be broken down into four parts.

Premise 1: On-line trading is ``more efficient'' and will save its participants money.

Premise 2: I can capture some of those savings as site revenue.

Premise 3: My site will be the best site out there, so everyone will use it.

Premise 4: With all this liquidity, I can construct benchmarks. My benchmarks will be unimpeachably scientific and replace the existing, unscientific benchmarks currently used by the industry. As a result, I will make even more money, because I will become an information provider.

This article will examine those premises and the limits of their inherent logic, with a view to showing why very few--if any--of the 500 launched exchanges will survive. In particular, it will show why the logic of Premise 4 is not valid for markets in physical commodities, such as oil and petrochemicals.

Premise 1: On-line trading is more efficient

Few would question that, in theory, electronic trading has the potential to make liquid markets much more efficient. The history of EnronOnline, probably the most successful electronic energy trading system in the world today, supports that view. According to Enron, EnronOnline has succeeded in raising the number of transactions completed by each of its market makers from an average 672 in 1999 to 3,084 last year, while lowering the marginal cost per transaction by 75% over the two-year period.

However, the markets that EnronOnline predominantly serves are two of the most liquid and homogeneous in the energy business: natural gas and electricity. Moreover, the exchange has achieved its efficiency gains using a model very different from any deployed by--or available to--most on-line exchanges. Essentially, Enron has used on-line trading to extend and complement its existing, off-line trading business. Enron's focus remains the transaction, rather than the transaction system.

By contrast, the majority of transaction platforms for physical commodities are interlopers. Their operators assume that commodities traders are willing to depersonalize their business by having their complex transactions executed not by humans, but by an electronic system that can do deals faster and more anonymously, and--at least in theory--with more players.

This assumption is a risky one, largely because it is based on a buyer's perception of how marketplaces should operate. It fails to take into account the concerns of physical commodity sellers and--more importantly--producers. Typically, producers wish to ensure that the uptake of their commodity is continuous, because that minimizes the volatility of the commodity's price. Relationships become all-important under such conditions--but relationships are hardly enhanced by electronic dealing. To quote the November/December 2000 issue of the Harvard Business Review, ``Few suppliers want to be anonymous contestants in ruthless bidding wars.''

Premise 2: I can make money selling gains in efficiency

The logic underlying Premise 2 is potentially seriously flawed. For while there is no doubt that market participants are prepared to pay for more efficient services, such as electronic trading, the nature of the forces driving physical energy commodity markets casts doubt on whether a trading system can, in the long term, make a profit by charging per-transaction fees.

Here's why: Although the era of competition is just beginning, it's clear that pressure on transaction fees is already downward, and will remain in that direction even if the number of participants in an exchange shrinks to a handful. In the energy business, the potential for efficiency gains--as a percentage of total industry cost--simply is not that great. For example, research done for Platts, a division of The McGraw-Hill Companies, New York, indicates that the total potential efficiency ``pool'' in the oil industry is only $150 million/year. Even if only 10 businesses were to try to carve a profitable enterprise out of such a pool, each would be hard-pressed to do so.

What's more, such businesses would have an even harder time turning a profit because some of their competitors wouldn't be using a per-trade revenue model. In particular, sites operated by market participants, such as EnronOnline, will tend to charge nothing per trade, because their business models seek to profit not from commissions on transactions, but rather from the transactions themselves. By implication, it seems likely that an exchange will be able to make money only if its owners sell something else: clearing facilities, back-office integration, or information to decision-makers.

Premise 3: My site will be the best, so it will capture all the market liquidity available

This statement--which essentially says that given enough marketing support, a site can change the trading patterns of an industry to capture all of its liquidity--is a fallacy.

The logical problem with the premise is clear. Because no one has yet developed a trading software package that is clearly superior to others, what ``best site'' really means is ``most liquid site.'' So the pre-condition for capturing ``all'' the liquidity is that the site must already be the most liquid site.

Some startup exchanges have attempted to solve this problem by insisting that their participants make volume guarantees. But volume guarantees conflict directly with traders' focus on profits. Trading businesses that tell their traders to sacrifice profits for the sake of the common good are playing a risky game; if the common good means lower trading profits, the traders will simply leave for greener pastures.

To become the ``best'' site, then, a site must somehow find a way to bootstrap its liquidity, perhaps by offering substantial, non-volume-related incentives or efficiencies to users.

However, the paradox is that most sites' revenue models depend almost exclusively on volume.

Premise 4: Once I capture lots of liquidity, I can build benchmarks

This premise is the most startling and--in some ways--the most flawed of the four. It raises many serious questions, the answers to any of which can invalidate the model. Worse, these questions are all highly theoretical, making persuasive answers even harder to come by.

Among the questions are: -- How much liquidity is enough? -- Do indexes (volumetric averages) make good physical benchmarks? -- Can a trading site benchmark with the bid/offer range? -- Can a trading site generate a close? And, last but not least: What is a benchmark, anyway?

Benchmarks and indices

A benchmark is a price or series of prices that a market's participants agree to use as the basis for determining other prices. Useful benchmarks are good indicators of transactable value. A benchmark allows market participants to determine at what price they should buy or sell the commodity.

Benchmarks are typically used in complex markets with multi-dimensional variables for arbitrage. In oil, for example, benchmark pricing has grown up around the need to compute relative values for differing commodities across time, geographical distance, commodity type, and the degree to which one commodity may be substituted for another.

It is a common error, however, to believe that markets should or do use their most liquidly traded commodities as benchmarks. Although liquidity is a major asset of benchmarks, many markets use illiquid benchmarks whose other characteristics outweigh the liquidity advantage. These include market transparency; the free and open availability of the commodity; the absence of political or partisan control of the commodity; the absence of delivery restrictions on it; and the size of the end-user market where the commodity will be consumed. For example, although the physical volume of Dubai crude oil actually produced is tiny, it nonetheless is used as a key benchmark for all of Asia because--unlike its Persian Gulf competitors--it is the only crude oil that has these characteristics.

One way to compute a commodity's benchmark price is through strict indexation, the process of constructing a price marker from a volumetric average of concluded business. However, this process will have little chance of producing a useful benchmark unless the contributing volumes are high. If it doesn't reflect a sufficient number of trades, an index has little or no statistical validity as an indication of transactable price.

This represents a problem for benchmarking oil prices, whether for crude or products. Of the 77 million barrels of crude produced worldwide each day, the vast majority are sold on the long-term contract market, leaving perhaps as little as 10% to be traded ``spot.'' In reality, this figure is boosted in multiple ways, primarily by transaction chaining--the repeated on-selling of cargos--but, even assuming threefold transaction growth as a result of electronic trading, is still perilously low to be used as a valid basis for strict indexation, especially considering the great diversity of crude oil specifications around the world. For many crude oils, the trading basis for establishing price can be just a few transactions per month. Even for ``liquid'' benchmark crudes, the basis is typically just a handful of trades per day. Oil markets, however, don't seem to care. For example, the settlement basis for the International Petroleum Exchange's Brent crude oil futures contract is an index based on a smattering of
 physical trades taking place on the day of expiry. Acceptance of an indexation mechanism such as this has difficult prerequisites. These include open participation in the mechanism, the perceived existence of a ``level playing field,'' the existence of comparative historical data, and achieving ``buy in'' from the market's dominant players.

The nature of today's on-line exchanges makes these conditions hard to meet. Not everyone uses exchanges; they may be owned by industry players; they typically have little or no historical data; their daily volume fluctuates wildly; and major players' commitment to them is either fragmentary or compromised by volume commitments. In today's environment, the chance that an index will be able to gain market acceptance as a benchmark is extremely slim.

Are strict volumetric indices useful? Another big question surrounding volumetric indices is how useful they are as benchmarks for physical commodities. Advocates of indexation argue that its statistical methodology helps eliminate market distortions caused, for example, by market closes. In addition, they argue that the alternative approach--``market assessment,'' based on human judgements about transactable prices--is too subjective to be relied on to determine benchmark prices. Indexation, its proponents argue, ``eliminates'' this subjectivity.

In practice, however, this argument doesn't pass the ``so what?'' test. Even if a system such as indexation succeeds in taking judgement out of the determination of market prices, it cannot prevent attempts to distort the index by exploiting the ``rules'' on which the system is based.

In many markets, human judgement is the only effective defense against market plays whose goal is profit, not price transparency. Even in highly liquid markets--such as, for example, the monthly natural gas market in the U.S.--the indices generated by information companies like Platts are subject to human review and analysis. During their generation, Platts' market specialists undertake a string of comparative tests to unearth potential distortions in reported prices. Whenever such distortions become apparent, Platts' editors investigate the market further and, where necessary, eliminate certain trades from the assessment picture. There are good reasons for their diligence. A volumetric index can be manipulated by volume plays, by a few players under the cloak of ``anonymous dealing,'' by selective trading, or by hedging in one marketplace and trading in another.

Figures 1 and 2 illustrate how players with exposure to a particular price on the buy side might--and actually do--manipulate a volumetric index. By doing lots of business early in the day when the market is rising, they can skew the volumetric average for the day lower (Figure 1). When the market is falling, they reverse the pattern and shift their transactions to late in the day, again pushing the market down (Figure 2). When players do this consistently, the impact on an index can be considerable over time.

There are other, potentially more serious problems with indices. Because an index is a theoretical construct, in a rapidly moving market it will manifest lag--and become useless to market participants seeking the answer to the question, ``At what price should I buy or sell?'' Indeed, an index may even actively mislead people asking this question. For example, in a fast rising market, an index generated over the course of one day will be significantly below the opening market price on the following day. This creates the impression that prices have somehow moved overnight, whereas in fact they may not have moved at all.

But perhaps the biggest problem with indices relates to their use in heavily interlinked markets, where prices are constrained by a complex of spread and arbitrage values. This description applies to most energy markets, and is particularly apt for today's global, physical market for oil. In markets where spread relationships are as or more important than outright prices, the process of generating averaged indices tends to generate sets of prices that cannot be reconciled with each other.

Figure 3 depicts a dramatized version of this problem. Price 1 and Price 2 are interdependent; here, there is always a 5 cents difference between them. However, the volume pattern for the day's trade (shown in the lower part of the figure) is such that while Price 1 has very high volume early in the day, Price 2 does not enjoy its volume boost until later. The result: Contrary to market reality, the volumetric averages for Price 1 and Price 2 say that they only differ by 1 cents.

Other routes to price discovery

So, if an on-line trading system cannot generate a reliable benchmark from an index, are there other routes to price discovery? Yes, two. The first is to benchmark from a bid-offer range, and the second is to use a close of some kind.

Bid-offer ranges are widely used as market measurement tools by Platts and others. However, the automated application of bid-offer ranges in pursuit of ``scientific'' benchmarks is fraught with difficulty. What happens when there is a bid, but no offer? An offer, but no bid? What rules can be written to discriminate between an ``off-market'' bid and an ``on-market'' one? How should a system decide when a bid or offer's timing is not representative of the typical market? Most on-line exchanges have not even begun to answer these questions, and at best offer their users a ``last bid-last offer'' price range that can accidentally distort their perception of the market, if the two are not aligned in time, or if it turns out, for example, that the ``last bid'' was actually withdrawn in response to the ``last offer.''

Some exchanges, implicitly acknowledging that creating useful benchmarks is difficult, have tried to incorporate their transactions and bid/offers into published benchmarks. Obviously, they hope that their system will attract more liquidity if it is tied to a traditional benchmark. But it's safe to say that a publisher will be interested in incorporating an exchange's proprietary markers only if transaction bid/offers are open and transparent.

Can an on-line site benchmark from a close? In theory, yes. But if human hands and brains intervene, the process is no longer a mechanical one, but rather an editorial/judgement effort. Here too, there are many obstacles. One of the biggest is that closing prices work best in two kinds of markets: completely ``open'' markets, in which assessments are derived by surveying all participants; and ``sole-operator'' markets--like futures markets--where the traded instrument exists only on that exchange.

Physical commodities, by contrast, are traded across a broad spectrum of instruments and sub-markets. It would be virtually impossible for the owner of a single sub-market--or on-line exchange--to assert the superiority of its close over someone else's, or to build market acceptance for a price derived from a trading pool that doesn't include all players.

Even a system used by most players--for example, the oil industry's derivatives-trading Intercontinental Exchange--would have a hard time convincing anyone to rely exclusively on its closing prices. That's not only because ``most'' is not the same as ``all,'' but also because liquidity is frequently too low to assure that there will in fact be a traded market to close every day. What happens to the benchmark on days when no one comes out to play?

In conclusion, it appears that price discovery may not necessarily be an emergent property of on-line trading systems. That may be the case because the creators of most on-line trading systems have confused its mechanism with its function. Trading systems are neither new markets nor new marketplaces; they are simply new vehicles for participating in existing marketplaces. A telephone is also a vehicle for participating in markets--but no one expects their phone to be able to tell them the price of a commodity. 

GEB0111600001  


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