differentiating a legitimate hedge from a target for manipulation · 2018. 2. 2. ·...

Copyright © 2015 The Brattle Group, Inc.

Differentiating a Legitimate Hedge from a Target for Manipulation

EUCI Conference on Integrating Energy Trading, Valuation, Market and Credit Risk Management

Shaun D. Ledgerwood

February 19, 2015

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Copyright © 2015 The Brattle Group, Inc. | brattle.com1

What is market manipulation?


▀ Several recent FERC and CFTC cases involve outright fraud:− Electricity (FERC): Rumford Paper Company, Gila River Power− Oil (CFTC): Panther Energy Trading (“spoofing”)

▀ One case involved a manipulation caused by market power abuse: − The DOJ’s KeySpan‐Ravenswood decision considered a case first brought

before the FERC as a market manipulation, but triggered by withholding (resulted in an award of disgorgement as damages – a first for the DOJ)

▀ Most of the recent FERC and CFTC anti‐manipulation cases focus on the use of uneconomic behavior:− Electricity (FERC): Constellation Energy Commodities Group, Deutsche

Bank Energy Trading, J.P. Morgan Ventures Energy Corporation− Gas (FERC): Energy Transfer Partners, Amaranth (Brian Hunter), BP− Energy derivatives (CFTC): In re: DiPlacido (electricity), Optiver Holdings

BV (oil), Parnon Energy et al. (oil)▀ Whereas outright fraud and market power are well‐understood, “uneconomic” behavior is a less well‐known phenomenon

Three types of behavior can trigger a manipulation


▀ Uneconomic trading is:− The intentional accrual of losses;− To bias a market outcome;− To benefit the value of positions tied to that outcome

▀ Losses are measured relative to opportunity costs▀ Significant problem of proving manipulative intent:

− Concern of false positives, as losses are a normal market event− Must overcome presumption of transactional legitimacy− Need evidence of repeated, anomalous losses + objective evidence

▀ Behavior is as old as competition, but only recently prosecutable:− Betting against oneself then throwing a sports match− Made illegal in U.S. securities markets in 1942 (SEC Rule 10b‐5)− Made illegal in U.S. electricity/gas markets in 2005 (EPAct 2005)− Made illegal in U.S. physical petroleum/distillate markets in 2007 (EISA)− Made illegal in U.S. futures/derivatives markets in: 1974 (CFTC Act, modifying CEA ‐ artificial price rule) 2010 (Dodd‐Frank ‐ fraud‐based rule)

What is uneconomic trading?


▀ A trader owns one condo, but wants to buy many more

▀ The market price of equivalent condos is $500,000, based on a price index tracking the last 30 days’ average sales

▀ Hundreds of identical condos for sale in this market, all offered at or near the $500,000 index price

▀ If the trader offers its condo to the market for $100,000:− The sale executes immediately ‐ Trader incurs an opportunity cost‐based

loss of $400,000− Note that any seller can execute trades below the competitive price at

will and without the need of market power

▀ Loss‐based sale is observable evidence of anomalous market behavior and raises a question of the trader’s intent

Example: Manipulation of a condominium market


▀ Once this sale is recorded, it will register on the index and lower the average market price (the sale is “price‐making”)

▀ If the condo index contained 19 prior sales at $500,000:− Trader’s $100,000 sale lowers the average index price to $480,000− Everyone who owns a condo takes a potential $20,000 loss

▀ Trader next buys 50 condos at the lower index price:− These purchases are as a price‐taker to the index− Trader saves $20,000 on 50 condos = $1 million by this strategy− Net profit of $600,000 ($1 million – its $400,000 opportunity loss)

▀ These transactions are separable by cause and effect:− The trader used an uneconomic price‐making transaction (a trigger)− To move an indexed price to benefit a price‐taking position (a target)− By exploiting a nexus that exists between the trigger and target

Condominium market example (continued)


▀ Traditional economic analyses do not explain this behavior as they presume market power is needed to move prices

▀ The trader in the condo example was 1 of 20 index sellers:− Trader has market share of 5% of all price‐making trades− This demonstrates that market power is not needed to move prices− Issue becomes the liquidity of the index

▀ Traders without market power can thus move prices by intentionally executing uneconomic transactions:− Sellers post offers below the market price or sell in large volumes− Buyers post bids above the market price or buy in large volumes− Issue if such trading serves a legitimate business purpose

▀ Profitability of the manipulation is a function of the financial leverage built in the targeted position

▀ Liquidity on index prevents the ability to manipulate:− Risk of false positives chills legitimate trading & potentiates manipulation

Market power is not needed to move market prices


▀ Consider natural gas trader who owns a large derivatives position that is short to a daily settlement price. Assume the market price is currently $5.00/MMbtu:− Scenario 1: Trader issues a false storage report predicting a large surplus

of natural gas, causing the market price to fall to $3.00/MMbtu, benefiting its short derivatives position (outright fraud)

− Scenario 2: Trader says nothing, but sells large volumes as a price‐taker during the settlement period. The market price falls to $3.00/MMbtu, benefiting its short derivatives position (transactional fraud)

▀ Only difference between Scenarios 1 and 2 is who bears the loss of the manipulative trades:− Scenario 1: Other sellers in the natural gas market bear the entire cost of

the manipulation caused by the false report− Scenario 2: The manipulator bears some (but not all) of this loss

▀ There is need of way to explain all such manipulations, as well as those caused by the exercise of market power

Uneconomic trading is transactional fraud


A framework for the detection and analysis of market manipulation


▀ A key complaint about example‐driven manipulation enforcement is the uncertainty it provides:− “I know it when I see it” approach complicates compliance, potentially

decreasing market liquidity by chilling legitimate trading− “False positives” may lead to wrongful allegations requiring vigorous legal

defense at great expense to firms and individual traders ▀ There is need for a practical way to distinguish behavior that serves a stand‐alone, legitimate business purpose from that which is considered potentially manipulative:− Begin with a presumption that the trading is legitimate, then test to see if

this hypothesis is anomalously rejected▀ A useful framework would analyze manipulation cases consistently across products, markets, and agencies: − This framework needs to explain the logic of past manipulation cases and

prescribe guidance to assist future compliance so that traders can have certainty regarding what trades are legitimate vs. manipulative

Example-based enforcement causes uncertainty


▀ One way to explain the cause and effect of manipulation is to separate the analysis into a framework of three pieces:− A trigger – Acts intended to directionally bias a market outcome− A target – One or more position(s) that benefit from that bias− A nexus – A provable linkage between the trigger and target

▀ For example, triggers of a price‐based manipulation are:− Transactions that intentionally lose money to alter a price− Statements or actions that misrepresent value to alter a price− Use of market power to alter a price

▀ Targets of a price‐based manipulation could be:− Physical commodity TAS (a.k.a. priced “at index”)− Financial derivatives positions− Other related market positions

▀ The nexus of the manipulation could be any reference price, including a price determined from an index or auction

A framework to analyze manipulation


A framework for analyzing market manipulation

Manipulation Triggers

Uneconomic TradingOutright Fraud

Exercise Market Power

Nexus

Biased Market Outcome

Manipulation Profits

Manipulation Targets

Financial DerivativesPhysical “At Index”

Cross-Market Positions

Uneconomic Trading


Analysis of an alleged manipulation using framework


▀ Because losses are a normal market event, it is necessary to prove that the losses were intentional:− Pattern of repeated losses over time− Unexplained, anomalously large losses− Documentary evidence confirming intent

▀ Proof of the stand‐alone, legitimate business purpose of the trades is a key defense:− Trades intended to make a profit on a stand‐alone basis are in furtherance

of legitimate economic incentives and thus not manipulative− Losses on such trades are an inevitable result of legitimate risk taking− However, mindless repetition of such losses raises concerns of intent

▀ Key issue is the efficiency of the trades in question:− Trades that converge prices across markets improve economic efficiency

and thus should not be considered manipulative− By comparison, trades that intentionally diverge market prices harm

market efficiency and are of concern

Distinguishing normal losses from uneconomic trades


An example showing the role of leverage in an alleged market manipulation:

Constellation Energy Commodities Group


▀ The following economic model assumes a trader places virtual load (a.k.a., “DECs”) at the sink of its FTR position:− Begin by describing the trader’s decision to place virtual bids on a stand‐alone basis: Initial simplifying assumption of only one virtual trader Reality check afterwards (very important) Virtual bids used as the manipulation’s trigger

− Next, see how the addition of a FTR affects the trader’s behavior: The FTR is the manipulation’s target The profitability of the manipulation is shown to depend on the size of the FTR position

▀ The model identifies a “bright line” test to find the level of virtual bidding that suggests manipulation of the trader’s FTR, BUT...

▀ That test must be corroborated with additional evidence of intent before the trader can be reasonably accused of manipulation

A model: Using virtual bids to benefit the value of FTRs


▀ Virtual supply and demand (collectively, “virtuals”) give market participants the ability to hedge or speculate on price differences between the day‐ahead and real‐time markets at a particular nose

▀ A trader bids DECs at a location if it believes that the day ahead LMP will clear below the real time LMP in a given hour at that same location:− The trader essentially buys MW in the day ahead market, then sells them

back to itself in the real time market− Payment to a DEC bid = (LMPRT – LMPDA)*MW− Physical market participants hedge against risk in the real time market,

such as a generator wishing to protect against the risk of a unit outage− Non‐physical players seek the profit potential (and associated risk)

▀ However, DECs tend to raise congestion prices in the day ahead market and to lower congestion prices in the real time market:− Therefore, DECs are price setting transactions− This benefits the market if it converges the day ahead and real time prices− It can also be used to trigger a market manipulation

The economics of trading virtual load


The convergence principle of virtual bidding


The derived demand for decremental bids


The paradox of convergence for virtual bids


▀ FTRs (a.k.a. “CRRs” or “TCCs”) give market participants in “Day 2” wholesale electricity markets the ability to hedge or speculate on price differences between the day ahead prices at two locations− A FTR pays its holder the difference in the day ahead congestion prices between the FTR’s

“source” and “sink”− Payment to the FTR = (Psink – Psource)*MW− FTRs are price taking instruments

▀ FTRs can be used as a hedge for physical players or as a speculative investment− Original purpose of FTRs was to provide load serving utilities a hedge to competitive

congestion prices between their generator (the “source”) and load (the “sink”)− Some FTRs are still allocated to physical market participants for this purpose− Non‐physical players also buy FTRs for their associated risks and rewards

▀ However, if the FTR sinks at the same point where the virtual Trader is placing DECs, the value of the FTR will progressively increase as more DECs clear due to an increase in the day ahead congestion price at that point− Thus, FTRs can be the target of a market manipulation triggered by the DEC bids− The nexus is self‐evident, as the day ahead price at the sink is the link between the

manipulation trigger and target

The addition of FTRs to the virtual trader’s portfolio


Placing DECs at sink raises FTR value


Total revenues from DECs and FTR combined


Maximizing total portfolio value lowers virtual gains


Greater FTR leverage incents virtual losses


Losses on virtuals increase profit of total portfolio


▀ Constellation Energy Commodities Group was accused of using uneconomic virtual and physical energy trades to manipulate the value of FTRs and other financial swaps:− Triggers: Intentionally‐placed uneconomic virtual and physical trades in

the NYISO, ISO‐NE, PJM and IESO (not jurisdictional)− Targets: FTR and other swaps positions tied to nodal, zonal and hub‐

based LMPs within and across these regions− Nexuses: The LMPs linking the various triggers and targets

▀ The FTR/virtual model shown above mirrors the FERC’s reasoning described in the Constellation settlement

▀ $245 million in disgorgement and civil penalties awarded− $110 million in disgorgement to the NYISO, ISO‐NE and PJM− $135 million in civil penalties− Several traders’ licenses revoked

▀ Speculation exists as to the linkage between this settlement and the Constellation/Exelon merger

Constellation’s alleged manipulation & settlement


BP America Inc., et al.:Alleged uneconomic trading of natural gas


▀ BP’s “Texas Team” of traders traded physical natural gas at Katy Hub and Houston Ship Channel (HSC), and controlled capacity to flow gas from Katy to HSC

▀ Going into mid‐September 2008, BP:− Held a Houston Ship Channel (HSC)‐Henry Hub spread position that was

short to the Gas Daily index at HSC and long index swaps at Henry Hub− Made a tremendous amount of money on these positions due to the

approach and landfall of Hurricane Ike: Plant closures in Houston tanked daily gas prices at HSC, benefitting BP’s short index position

▀ From September through November 2008, BP’s traders allegedly:− Attempted to continually profit from this spread by selling next‐day fixed

price gas uneconomically at HSC to suppress the daily price in benefit to its short swaps position: Sales made money from an accounting perspective, but lost money relative to potential sales elsewhere

− Later increased the size of the spread and the amount of next‐day gas sold uneconomically at HSC

Allegations in the BP case


▀ The FERC issued an Order to Show Cause against BP on August 5, 2013, alleging violations of Rule 1c

▀ The main pillars of the FERC’s case are:− A recorded conversation between the trader executing the scheme and

his supervisor questioning whether the trades were manipulative

Issues raised in the BP case

− Uneconomic behavior inconsistent with past practice, including: Much higher pipeline capacity utilization

BP was historically a net buyer at HSC, but was a net seller during the suspect period

BP often “framed the open” by making the first sales of the day at low prices


▀ The case shows that the FERC is willing to look at past behavior as far as its five year statute of limitations allows:− FERC seeks $28 million in civil penalties− FERC seeks $800,000 in disgorgement− No individual penalties or trading bans

▀ Case alleges that “uneconomic” trading is measured relative to the trader’s opportunity costs:− Stated intent of the “Arbitrage Strategy” of the Texas Team was to flow

gas and sell at HSC only when higher prices would justify it− The Texas Team not only sold gas at prices below those available at Katy,

but below those obtainable at HSC daily prices▀ Additional evidence of main trader’s desperate circumstances and the effect on the trades on P&L are also highlighted

▀ Again, objective evidence (the recorded conversation and other communications) is serving as the first pillar of the agency’s case

▀ BP’s compliance efforts investigated the behavior but failed to find (and thus self‐report) a Rule 1c violation

Takeaways from the BP case


Additional resources andcompany information


▀ Market Power and Market Manipulation in Energy Markets: From the California Crisis to the Present. Coauthored with G. Taylor, R. Broehm and P. Fox‐Penner. Forthcoming from PUR Inc. (April/May 2015).

▀ “Market manipulation and the compliance chasm.” Coauthored with J. Tsoukalis. Forthcoming in Energy Risk Magazine (February 2015).

▀ “Using Virtual Bids to Manipulate the Value of Financial Transmission Rights.” Coauthored with H. Pfeifenberger. The Electricity Journal, vol. 26, issue 9, pp. 9‐25 (November 2013).

▀ “Uneconomic trading and market manipulation.” Energy Risk Magazine, p. 32 (July 2013).

▀ “A Framework for Analyzing Market Manipulation.” Coauthored with P. Carpenter. Review of Law & Economics, vol. 8, issue 1, pp. 253–295 (September 2012).

▀ “A Comparison of Anti‐Manipulation Rules in U.S. and EU Electricity and Natural Gas Markets: A Proposal for a Common Standard.” Coauthored with D. Harris. Energy Law Journal, vol. 33, p.1 (April 2012).

▀ Other documents are available at www.brattle.com.

Additional resources


Presenter information

SHAUN D. LEDGERWOODPrincipal│Washington, [email protected] +1.202.419.3375

Dr. Ledgerwood specializes in issues of market competitiveness with an emphasis on the economic analysis of market manipulation. He previously served as an economist and attorney for the FERC in its enforcement proceedings involving Energy Transfer Partners, L.P., Amaranth Advisors, LLC, and several other cases. He has built upon these experiences to develop a framework for defining, detecting and analyzing manipulative behavior. He has worked as a professor, economic consultant, attorney, and market advisor to the regulated industries for over twenty years, focusing on issues including ratemaking, power supply, resource planning, and electric asset valuations. In his broader practice, he specializes on issues in the analysis of liability and damages for actions based in tort, contract or fraud. He has testified as an expert witness before state utility commissions and in federal court.

The views expressed in this presentation are strictly those of the presenter(s) and do not necessarily state or reflect the views of The Brattle Group, Inc.


  The Brattle Group provides consulting and expert testimony in economics, finance, and regulation to corporations, law firms, and governments around the world. We aim for the highest level of client service and quality in our industry.  We are distinguished by our credibility and the clarity of our insights, which arise from the stature of our experts, affiliations with leading international academics and industry specialists, and thoughtful, timely, and transparent work. Our clients value our commitment to providing clear, independent results that withstand critical review.

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differentiating a legitimate hedge from a target for manipulation · 2018. 2. 2. ·...

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