Artificial Price
An artificial price is a market price that has been manipulated to a level that does not reflect legitimate supply and demand forces, typically through coordinated trading activity, deceptive order placement, or dissemination of false information designed to move prices for the benefit of the manipulator. The creation of artificial prices is a primary prohibition in virtually all securities and commodities laws globally.
Key takeaways
- The CFTC defines price manipulation as intentional conduct that causes a futures price to deviate from or fail to reflect the forces of supply and demand; the SEC applies a similar standard to securities under Section 9 and 10(b) of the Securities Exchange Act.
- Common manipulation techniques include cornering a market (accumulating sufficient dominance over supply or delivery to dictate settlement prices), wash trading (simultaneous buy/sell between related parties to generate false volume), spoofing (placing orders with intent to cancel), and painting the tape (creating the appearance of active trading).
- Cornering a commodity futures market historically required controlling physical supply as well as futures positions; Enron's manipulation of California electricity prices in 2000-2001 and the Hunt brothers' silver corner in 1979-1980 are canonical examples.
- Modern surveillance technology and cross-market data sharing have made traditional manipulation more difficult to execute and easier to detect; the CFTC and SEC use pattern recognition and trade reconstruction to identify suspicious activity.
- The legal boundary between legitimate trading (including large-scale hedging, position-building, and aggressive market making) and price manipulation often requires detailed factual analysis, making enforcement actions complex and contested.
Explanation
Artificial prices represent a failure of markets' core function: price discovery. When market prices reflect the genuine interplay of buyers and sellers with diverse information and motivations, they serve as efficient information aggregators—the Hayekian 'knowledge problem' solution. When prices are artificially influenced, they transmit false information to economic actors, misallocating resources and redistributing wealth from uninformed market participants to manipulators.
The legal framework for prohibiting artificial prices has evolved alongside market sophistication. The Commodity Exchange Act's anti-manipulation provisions originally required proof of specific intent, corner, squeeze, or control—a high evidentiary bar that made prosecutions difficult. Dodd-Frank Section 753 lowered the bar by introducing a 'reckless disregard' standard and explicitly prohibiting 'manipulative and deceptive devices and contrivances' in futures markets. This brought futures manipulation law closer to securities fraud standards under Rule 10b-5, enabling the CFTC to pursue manipulation cases without proving specific intent.
Spoofing—the most common modern form of attempted price manipulation—involves placing large orders on one side of the market to move prices, then canceling those orders before execution and trading on the opposite side. A spoofer who wants to buy at a lower price might submit a large sell order to push prices down, then cancel it and buy at the artificially depressed price. The manipulation creates an artificial price signal (apparent selling pressure) that misleads other participants about genuine supply and demand. High-profile prosecutions (United States v. Coscia, affirmed by the 7th Circuit in 2016; the CFTC's major bank spoofing settlements 2018-2020) have established clear legal liability.
For market participants, the distinction between aggressive legitimate trading and manipulation is not always obvious. A large market participant whose genuine hedging activity moves prices is not manipulating; a trader who accumulates positions with the specific intent of moving prices for profit is. The intent element is critical but often circumstantially inferred from trading patterns. Compliance programs at financial institutions must address manipulation risk through: surveillance systems monitoring for suspicious patterns, pre-trade controls limiting position size and order cancellation rates, and staff training on prohibited activities.
Example
In the Libor manipulation scandal (2012-2016), banks submitting daily estimates to the ICE Benchmark Administration were found to be artificially inflating or deflating their submissions to benefit proprietary derivatives positions. Barclays, for example, had traders requesting that submitters set Libor rates favorable to their interest rate swap positions. When Barclays held large notional positions in LIBOR-based swaps where a higher fixing was beneficial, submitters provided higher-than-warranted estimates. The resulting artificial LIBOR affected $350+ trillion in notional contracts globally—affecting mortgage rates, corporate loans, and derivatives settlements. Regulatory fines across participating banks exceeded $9 billion, illustrating both the scale of artificial price impacts and the severity of regulatory consequences.
Related terms
Alternative Trading System Blind Auction Daily Price Limit Exchange Hedging Interest Rate Interest Rate Swap Libor Order Book Price Discovery Price Improvement Spoofing