1. Introduction

Herd behaviour in energy trading refers to a situation in which traders, generators, retailers, or other market participants make similar trading decisions because they observe the actions, prices, orders, or expectations of other participants rather than relying independently on fundamental information.

In electricity markets, herd behaviour can be particularly significant because electricity is difficult to store economically at large scale, demand and supply must remain balanced almost instantaneously, and prices can change sharply in response to weather, generation outages, transmission constraints, fuel prices, and demand forecasts.

Herding is not automatically illegal. Traders are ordinarily permitted to respond to publicly available information and to follow market trends. The legal problem arises when coordinated or deceptive behaviour creates false or misleading signals, produces an artificial price, or involves manipulation or insider information. The EU's REMIT framework, for example, prohibits market manipulation and attempted manipulation in wholesale energy markets. (ACER)

2. Meaning of Herd Behaviour

Herd behaviour generally involves three characteristics:

Observation of other traders' behaviour

Imitation or convergence of trading decisions

Reduced reliance on independent information or fundamental analysis

For example, suppose several electricity traders observe rapidly increasing prices in a day-ahead market. Even though their own analysis does not show a comparable shortage, they may purchase electricity because they believe that other traders possess better information.

This can create a feedback loop:

Price increase → traders interpret increase as information → additional buying → further price increase → more traders enter → increased volatility.

The same phenomenon can occur on the selling side.

3. Why Herd Behaviour Is Particularly Important in Electricity Markets

Electricity markets have structural characteristics that amplify collective behaviour.

A. Electricity cannot easily be stored

Unlike many commodities, electricity generally has to be produced close to the time it is consumed. Consequently, a relatively small change in expected supply or demand can have a disproportionate effect on price.

B. Inelastic short-term demand

Consumers generally cannot immediately reduce electricity consumption when wholesale prices increase. Therefore, a relatively small supply reduction may cause a large price movement.

C. Transmission constraints

Congestion can divide markets into different price zones. Traders observing price movements in one zone may rapidly adjust positions in another.

D. Information asymmetry

Generators may possess information concerning outages, maintenance, fuel availability or expected generation that other traders do not have.

E. Algorithmic trading

Modern energy markets increasingly use automated trading systems. Algorithms may respond to similar price signals, causing independent algorithms to produce highly correlated orders.

ACER specifically recognises that modern wholesale energy trading has become more complex because of algorithmic trading and has strengthened REMIT monitoring accordingly. (ACER)

4. Forms of Herd Behaviour in Energy Trading

4.1 Price-following behaviour

Traders may purchase electricity simply because prices are increasing.

For example:

Trader A buys heavily.

The market price increases.

Traders B, C and D interpret the increase as evidence of future scarcity.

They also buy.

The additional demand further increases the price.

This can create self-reinforcing price movements.

Price-following itself is not market manipulation. It becomes legally problematic where the price signal has been deliberately manufactured through deceptive conduct.

4.2 Order-book herding

In continuous electricity markets, traders can observe buy and sell orders in an order book.

A trader may observe:

Large apparent demand → expectation of shortage → additional buying.

The apparent demand may, however, be artificial.

This is closely related to spoofing and layering. ACER explains that non-genuine orders can alter the visible order book and create false or misleading signals concerning supply, demand or price. (ACER)

Thus, a trader may attempt to induce herd behaviour among other participants by making the market appear more bullish or bearish than it actually is.

4.3 Herding around fundamental announcements

Energy markets react strongly to:

generator outages;

weather forecasts;

gas prices;

transmission failures;

regulatory announcements;

renewable generation forecasts;

nuclear plant availability.

Suppose one trader obtains legitimate public information indicating that a major power plant will be offline. Other traders may independently react to that information.

That is legitimate market behaviour.

However, if a trader possesses inside information and trades before its disclosure, the issue becomes insider trading rather than merely herd behaviour.

REMIT prohibits trading on inside information as well as market manipulation. (ACER)

5. Herd Behaviour and Market Manipulation

The central legal distinction is:

Legitimate herding

Traders independently respond to:

public information;

market fundamentals;

legitimate price signals;

publicly observable supply and demand.

Potentially unlawful herding

A trader deliberately creates a false market signal so that others follow it.

For example:

Artificial buy orders → other traders believe demand is high → they purchase → price increases → manipulator sells at higher price.

The legal issue is therefore not simply that traders behave similarly. The important question is how the market signal was created and whether it was genuine.

6. European Union Legal Framework — REMIT

The EU's Regulation on Wholesale Energy Market Integrity and Transparency (REMIT) is one of the most important legal frameworks for analysing herd behaviour in wholesale electricity trading.

REMIT prohibits:

insider trading;

market manipulation;

attempted market manipulation;

dissemination of false or misleading information.

ACER explains that the objective is to ensure that wholesale energy prices reflect a fair and competitive interaction between supply and demand. (ACER)

Relevance to herding

Herd behaviour may become legally relevant when a participant intentionally generates:

false demand signals;

false supply signals;

artificial prices;

misleading order-book information.

ACER's guidance identifies various indicators that regulators may examine, including unusually large trading volumes, significant price effects, substantial market positions and rapid position reversals. These indicators are not automatically proof of manipulation and must be considered in context. (ACER)

7. ACER Guidance on Spoofing and Layering

An especially relevant example concerns layering and spoofing.

ACER describes these practices as involving large or multiple non-genuine orders on one side of the order book intended to facilitate transactions on the other side. Such orders can create false or misleading signals concerning supply, demand or price. (ACER)

This has a direct connection with herd behaviour.

Example

A trader wants to sell electricity at a higher price.

The trader:

places apparently large buy orders;

creates the impression of strong demand;

other market participants observe the demand;

they begin buying;

the price rises;

the original trader sells into the stronger market.

The other traders' behaviour has effectively been induced by an artificial signal.

8. Artificial Price Formation

ACER's guidance also provides an example involving electricity intraday trading where erroneous orders caused a product's closing price to rise dramatically above surrounding hours.

The guidance explains that regulators may consider whether the conduct positioned a product at an artificial price and whether the resulting price differed substantially from the price that would have emerged from genuine supply and demand. (ACER)

This demonstrates an important principle:

The existence of collective trading behaviour is not itself unlawful; manipulation of the information environment that causes collective behaviour can be.

9. United States Legal Framework

In the United States, electricity-market manipulation is principally addressed through the Federal Power Act (FPA) and FERC's anti-manipulation regulations.

FERC investigates conduct involving:

artificial pricing;

fraudulent transactions;

deceptive practices;

manipulation of electricity markets;

manipulation of related financial products.

The Western Energy Crisis of 2000–2001 remains one of the most important examples. FERC's investigation concluded that market conditions, including reduced power supplies, infrastructure limitations and market-design problems, contributed to manipulation that prolonged and intensified economic harm. FERC subsequently pursued extensive enforcement actions and settlements. (Federal Energy Regulatory Commission)

10. Case Law and Enforcement Examples

A. Amaranth Advisors L.L.C. v. FERC

The Amaranth litigation concerned FERC's authority to investigate alleged manipulation in natural-gas markets under its anti-manipulation authority.

The case is important because it demonstrates the expanding regulatory role of FERC in detecting manipulative trading strategies in energy markets and the interaction between FERC jurisdiction and federal commodities regulation. (Federal Energy Regulatory Commission)

Relevance to herd behaviour

Sophisticated energy trading strategies can influence the expectations and behaviour of other market participants. The legal analysis therefore focuses on the trading strategy, intent, market effect and regulatory jurisdiction, rather than simply asking whether other traders followed the market.

B. Barclays Bank PLC — FERC Enforcement

FERC's Barclays proceedings provide an important electricity-market manipulation example.

According to FERC, Barclays traded physical electricity in western U.S. markets with the purpose of affecting index prices at which related financial instruments settled. FERC assessed civil penalties and disgorgement, with the matter ultimately proceeding through federal-court litigation and settlement. (Federal Energy Regulatory Commission)

Legal significance

The case illustrates how trading in one market can influence expectations and pricing in another connected market.

This is important for herd behaviour because participants may respond to apparently genuine price signals even where those signals have been strategically influenced.

C. Deutsche Bank Energy Trading, LLC

FERC also brought an enforcement action concerning electricity exports in the California ISO market that allegedly affected the value of related congestion revenue rights.

FERC's enforcement materials state that the matter involved the anti-manipulation rule as well as false information submitted to the ISO. A settlement resulted in a civil penalty and disgorgement. (Federal Energy Regulatory Commission)

Relevance

This illustrates the importance of considering interrelated energy products. A trading strategy does not have to manipulate the final product directly; manipulation of one market can affect another economically connected market.

D. GreenHat Energy

The GreenHat proceedings concerned alleged manipulation of the Financial Transmission Rights (FTR) market operated by PJM.

FERC ultimately determined that GreenHat and associated individuals violated the Federal Power Act and FERC's anti-manipulation regulations through a manipulative scheme involving FTRs. FERC's enforcement record also reports substantial disgorgement and trader bans. (Federal Energy Regulatory Commission)

Relevance to herd behaviour

FTR markets demonstrate how traders' expectations concerning congestion and transmission conditions can become self-reinforcing. Where market participants are encouraged to act on misleading signals, collective behaviour can magnify the consequences of manipulation.

11. Western Energy Crisis and Collective Behaviour

The California electricity crisis provides a broader illustration of how trading strategies, market structure and participant expectations can interact.

FERC's investigation concluded that manipulation occurred in a market already experiencing supply shortages, transmission constraints and design weaknesses. (Federal Energy Regulatory Commission)

This is significant because herd behaviour can amplify an existing physical shortage.

For example:

Physical shortage → genuine price increase → traders expect further shortage → increased purchasing → further price pressure → increased volatility.

If the original signal is genuine, this may simply represent rational market behaviour. If the signal is deliberately manufactured, however, the same feedback mechanism can facilitate manipulation.

12. Herd Behaviour and Market Efficiency

Herd behaviour can have both positive and negative effects.

Potentially beneficial effects

Market participants may collectively respond quickly to new information.

For example, if several generators unexpectedly fail, traders may rapidly increase electricity prices to reflect genuine scarcity.

This can improve price discovery.

Potentially harmful effects

Excessive herding can cause:

price bubbles;

excessive volatility;

liquidity deterioration;

distorted price discovery;

inefficient allocation of electricity;

increased hedging costs;

systemic exposure;

consumer price impacts.

13. Herd Behaviour and Renewable Energy Markets

The growth of renewable generation creates additional opportunities for herd behaviour.

Solar and wind production depend on weather forecasts.

Suppose a forecast predicts unexpectedly low wind generation.

Traders may simultaneously:

increase purchases;

reduce short positions;

increase balancing-market positions;

revise forward prices.

If the forecast is subsequently revised, prices may reverse rapidly.

This can create substantial volatility even without manipulation.

Therefore, regulators need to distinguish between:

information-driven collective behaviour and deliberately induced collective behaviour.

14. Algorithmic Herding

Algorithmic trading creates a new legal challenge.

Different algorithms may independently react to:

identical price movements;

volatility;

order-book depth;

trading volume;

weather forecasts;

imbalance prices.

As a result, large numbers of algorithms can behave similarly without explicit communication.

This raises an important legal question:

When does independent algorithmic convergence become manipulation?

The answer generally depends on evidence of intentional or deceptive conduct rather than mere similarity in trading outcomes.

ACER's regulatory framework increasingly emphasises monitoring because wholesale energy trading has become more complex and algorithm-driven. (ACER)

15. Evidence Required to Establish Manipulation

A regulator examining alleged herd-inducing manipulation may consider:

1. Trading records

What orders were placed, modified or cancelled?

2. Timing

Did suspicious activity occur immediately before a major price movement?

3. Volume

Was the participant's trading unusually large compared with normal activity?

4. Position

Did the trader have an economic interest in the resulting price?

5. Communications

Were traders communicating with each other?

6. Economic rationale

Was there a legitimate commercial reason for the transaction?

7. Price effect

Did the conduct materially affect the market price?

8. Subsequent transactions

Did the trader profit after inducing the market movement?

ACER expressly cautions that individual indicators are not necessarily sufficient by themselves to establish market manipulation. (ACER)

16. Regulatory Challenges

Herd behaviour presents several difficult regulatory questions.

A. Distinguishing imitation from collusion

Two traders may make identical trades independently.

That alone does not demonstrate an agreement.

B. Distinguishing information aggregation from manipulation

Markets are designed to aggregate information. Collective responses can therefore be economically desirable.

C. Algorithmic convergence

Algorithms may independently produce similar orders.

D. Cross-market effects

Electricity, gas, carbon allowances, transmission rights and financial derivatives may be economically connected.

E. Cross-border enforcement

Energy markets frequently cross national boundaries.

The revised REMIT framework gives ACER a stronger role in cross-border investigations while national regulators retain important enforcement responsibilities. (ACER)

17. Legal Principles Emerging from the Case Law

Several principles can be identified.

Principle 1 — Herding is not inherently unlawful

Following market trends is generally a legitimate commercial activity.

Principle 2 — Artificial signals are legally significant

Creating false or misleading information about supply, demand or price may constitute market manipulation.

Principle 3 — Intent and context matter

A large transaction is not necessarily manipulative. Regulators examine its purpose, circumstances and market effect.

Principle 4 — Connected markets must be considered

Manipulation may involve physical electricity markets, financial products, congestion rights or other related instruments.

Principle 5 — Market integrity protects consumers as well as traders

Wholesale price distortion can ultimately affect electricity retailers, businesses and consumers.

18. Indian Perspective

In India, the issue is particularly relevant to electricity trading conducted through power exchanges and electricity-market mechanisms regulated under the Electricity Act, 2003, CERC regulations and exchange/market rules.

The regulatory framework involves institutions such as:

Central Electricity Regulatory Commission (CERC);

Power Exchange India Limited (PXIL);

Indian Energy Exchange (IEX);

Grid Controller of India Limited;

electricity distribution and generating entities.

For India, the principal legal concern is whether coordinated or deceptive trading undermines transparent price discovery and compliance with electricity-market regulations.

The conceptual distinction remains the same:

Independent response to public information ≠ manipulation

while

deliberately creating false market signals to induce other traders ≈ potential market abuse/manipulation, depending on the applicable statutory and regulatory provisions.

19. Economic Impact of Herd Behaviour

The consequences can be represented as follows:

20. Conclusion

Herd behaviour in energy trading is not itself a prohibited trading practice. It is a market phenomenon in which participants may imitate or respond to the actions of others. In electricity markets, physical scarcity, transmission constraints, weather dependence, algorithmic trading and rapid price formation can make such behaviour particularly powerful.

The legal boundary arises where collective behaviour is deliberately induced through deception, fictitious transactions, artificial orders, dissemination of false information, insider information or other manipulative conduct.

The Western Energy Crisis, Amaranth, Barclays and GreenHat proceedings demonstrate why regulators examine not merely the resulting price movement but the method, purpose, market effect and surrounding circumstances of trading. FERC's enforcement experience and ACER's REMIT framework both emphasise protection of genuine price discovery and market integrity. (Federal Energy Regulatory Commission)

Thus, the central legal principle can be stated simply:

Market participants may follow genuine market information, but they cannot lawfully manufacture false signals designed to make other participants follow them.

Key case/enforcement authorities

Amaranth Advisors L.L.C. v. FERC — FERC anti-manipulation authority and energy-market trading. (Federal Energy Regulatory Commission)

Barclays Bank PLC / FERC — manipulation involving electricity trading and related financial-index prices. (Federal Energy Regulatory Commission)

Deutsche Bank Energy Trading, LLC / FERC — manipulation involving California electricity and congestion-related financial interests. (Federal Energy Regulatory Commission)

GreenHat Energy / FERC — manipulation involving PJM Financial Transmission Rights. (Federal Energy Regulatory Commission)

Western Energy Crisis proceedings — extensive FERC investigation into manipulation and market-design problems. (Federal Energy Regulatory Commission)

ACER REMIT Guidance — artificial pricing, spoofing, layering and other forms of potential wholesale-energy market manipulation. (ACER)