Differentiating a Legitimate Hedge from a Target for Manipulation Presented to: EUCI Conference on Integrating Energy Trading, Valuation, Market and Credit Risk Management Presented by: Shaun D. Ledgerwood February 19, 2015
What is market manipulation? 1 brattle.com
Three types of behavior can trigger a 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 2 brattle.com
What is uneconomic trading? 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) 3 brattle.com
Example: Manipulation of a condominium market 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 4 brattle.com
Condominium market example (continued) 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 5 brattle.com
Market power is not needed to move market prices 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 6 brattle.com
Uneconomic trading is transactional fraud 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 7 brattle.com
A framework for the detection and analysis of market manipulation 8 brattle.com
Example-based enforcement causes uncertainty 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 9 brattle.com
A framework to analyze manipulation 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 10 brattle.com
A framework for analyzing market manipulation Manipulation Triggers Uneconomic Trading Outright Fraud Exercise Market Power Nexus Biased Market Outcome Manipulation Profits Manipulation Targets Financial Derivatives Physical At Index Cross-Market Positions 11 brattle.com
Analysis of an alleged manipulation using framework 12 brattle.com
Distinguishing normal losses from uneconomic trades 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 13 brattle.com
An example showing the role of leverage in an alleged market manipulation: Constellation Energy Commodities Group 14 brattle.com
A model: Using virtual bids to benefit the value of FTRs 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 15 brattle.com
The economics of trading virtual load 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 16 brattle.com
The convergence principle of virtual bidding 18 brattle.com
The derived demand for decremental bids 21 brattle.com
The paradox of convergence for virtual bids 22 brattle.com
The addition of FTRs to the virtual trader s portfolio 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 = (P sink P source )*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 24 brattle.com
Placing DECs at sink raises FTR value 26 brattle.com
Total revenues from DECs and FTR combined 28 brattle.com
Maximizing total portfolio value lowers virtual gains 29 brattle.com
Greater FTR leverage incents virtual losses 31 brattle.com
Losses on virtuals increase profit of total portfolio 33 brattle.com
Constellation s alleged manipulation & settlement 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 hubbased 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 34 brattle.com
BP America Inc., et al.: Alleged uneconomic trading of natural gas 35 brattle.com
Allegations in the BP case 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 36 brattle.com
Issues raised 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 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 37 brattle.com
Takeaways from the BP case 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 38 brattle.com
Additional resources and company information 39 brattle.com
Additional resources 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. 40 brattle.com
Presenter information SHAUN D. LEDGERWOOD Principal Washington, D.C. Shaun.Ledgerwood@brattle.com +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. 41 brattle.com
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