Background: Algorithmic Trading Regulations (2024-2026)

From 2024 through 2026, algorithmic-trading rules and supervisory expectations continued to evolve. China introduced detailed program-trading reporting and control rules, while US and European regulators developed enforcement and control expectations for automated and AI-assisted activity. Always verify the current rule, venue notice, account scope, and effective date before implementation.

I. China Algorithmic Trading Regulations

1.1 Regulatory Milestones

1.2 High-Frequency Trading Reporting and Attention Triggers

The SSE program-trading reporting notice uses the following account-level metrics for enhanced reporting and regulatory attention. They are not a blanket statement that every order at or beyond the number is prohibited:

Accounts crossing these triggers receive particular attention and must provide additional information. Scope, calculation, exemptions, and venue-specific procedures must be checked against the current exchange notice and member guidance.

1.3 Four Types of Abnormal Trading Behavior

Penalties:

• Trading restrictions
• Forced suspension
• Differentiated fees
• Severe cases: temporary market halt and report to CSRC

1.4 Compliance Reporting Requirements

Investors within the rules' definition of program trading generally report through their securities-company member before program trading, subject to the rule's scope, transitional arrangements, and specified exemptions. Required fields include:

• Account basic information
• Capital information
• Trading information
• Software information

Additional reporting for high-frequency trading:

• Server physical location
• System test report
• Fault emergency plan

Core Principle: "Report first, trade second"

1.5 Private Fund Special Requirements

Private fund managers must:

1. Develop dedicated business management and compliance risk control systems
2. Improve algorithmic trading order review and monitoring systems
3. Establish risk prevention and control mechanisms

1.6 Enforcement Case: Lingjun Investment

Date: February 20, 2024

What happened:

• In the first minute of trading on February 19, 2024, Lingjun's computer-generated orders sold CNY 1.195 billion of Shanghai-listed and CNY 1.372 billion of Shenzhen-listed stocks, driving the indices down sharply
• The next day the SSE and SZSE imposed trading restrictions (February 20-22) and initiated public censure

Warning Significance: This case happened before the Programmatic Trading Regulations took effect (October 2024) — it was one of the events that accelerated them. Even if an account's overall direction for the day is "correct," concentrated order flow in the opening seconds can itself cross the regulatory red line.

Note: the differentiated fee schedule for HFT (higher flow fees, cancellation fees) remains a stated direction in the Implementation Details — as of mid-2026 no concrete fee schedule has been published. Budget for it as "coming any time."

1.7 2024 Enforcement Intensity

II. US AI Quantitative Trading Regulations

2.1 Regulatory Architecture

Core Rules:

• FINRA Rule 3110 (Supervision Rule)
• FINRA Rule 3120 (Supplemental Supervision Responsibilities)

2.2 AI Application Compliance Requirements

June 27, 2024, FINRA released Regulatory Notice 24-09:

2.3 AI-Washing Enforcement (2024 Focus)

Definition: False claims about AI capabilities

SEC Enforcement: Filed lawsuits against two investment advisory firms

• Charged with violating Marketing Rule
• False claims about AI technology application in investment decisions

Compliance Requirements:

• Truthfully disclose actual AI technology application
• Cannot exaggerate or mislead investors
• Strict anti-fraud review

2.4 Major Penalty Case: Two Sigma

Date: January 16, 2025

Penalty Amount: $90 million (industry record)

Violation Reasons:

• Failed to address algorithm vulnerabilities
• Other violations
• Supervision failures

Warning: Even top quant institutions face severe penalties for inadequate algorithm risk control

2.5 SEC Fiscal Year 2024 Enforcement Data

Trend: Enforcement focus shifting from penalty amounts to case volume and deterrent effect

III. EU MiFID II Framework

3.1 Regulatory Evolution

3.2 MiFID RTS 6 Requirements (Algorithmic Trading Regulatory Technical Standards)

3.3 FCA Review Report (August 2024)

UK Financial Conduct Authority released multi-firm review report on algorithmic trading controls:

Key Requirements:

• Comply with MiFID RTS 6 requirements
• Strengthen algorithmic trading risk management and monitoring
• Improve system resilience and emergency response capability

IV. Regulatory Impact on Strategies

4.1 Impact Level Analysis

4.2 Leading Institution Response

Actual Situation:

• Alpha strategy turnover of large quant institutions is generally not high
• Most leading strategies have turnover below implementation detail limits
• Can basically meet new regulations

4.3 Industry Frequency Reduction Trend

Driving Factors:

1. Regulatory constraints (hard limits)
2. Capacity considerations (high-frequency cannot support billions in AUM)

Results:

• Medium-low frequency strategies gain importance
• Excess returns will inevitably decline
• Requires managers to continuously innovate in strategy depth and breadth

V. Compliance System Design Recommendations

5.1 Trading Frequency Monitoring

# Example: Trading frequency monitor
class TradingFrequencyMonitor:
    """
    Monitor trading frequency to ensure not triggering
    high-frequency trading identification criteria
    """

    # China regulatory thresholds
    CHINA_SECOND_LIMIT = 300   # Per-second order+cancel limit
    CHINA_DAILY_LIMIT = 20000  # Daily order+cancel limit

    def __init__(self):
        self.second_counter = 0
        self.daily_counter = 0
        self.last_second = None

    def check_order(self, timestamp: datetime) -> dict:
        """
        Check if approaching regulatory threshold
        """
        # Update counter logic...

        return {
            'second_usage': self.second_counter / self.CHINA_SECOND_LIMIT,
            'daily_usage': self.daily_counter / self.CHINA_DAILY_LIMIT,
            'warning': self._should_warn(),
            'block': self._should_block()
        }

    def _should_warn(self) -> bool:
        """Warn at 80% threshold"""
        return (self.second_counter > self.CHINA_SECOND_LIMIT * 0.8 or
                self.daily_counter > self.CHINA_DAILY_LIMIT * 0.8)

    def _should_block(self) -> bool:
        """Block at 95% threshold"""
        return (self.second_counter > self.CHINA_SECOND_LIMIT * 0.95 or
                self.daily_counter > self.CHINA_DAILY_LIMIT * 0.95)

5.2 Abnormal Trading Detection

# Example: Abnormal trading behavior detection
class AbnormalTradingDetector:
    """
    Detect four types of abnormal trading behavior
    """

    def detect_spoofing(self, orders: list) -> bool:
        """
        Detect spoofing (frequent instant cancellations)
        """
        # Calculate cancel rate within short time window
        cancel_rate = self._calculate_cancel_rate(orders, window_seconds=1)
        return cancel_rate >0.9  # 90%+ cancel rate considered abnormal

    def detect_layering(self, orderbook_changes: list) -> bool:
        """
        Detect layering (frequent ramping/dumping)
        """
        # Analyze order book change patterns
        pass

    def detect_burst_volume(self, trades: list,
                           window_seconds: int = 60) -> bool:
        """
        Detect short-term large volume
        """
        # Calculate volume anomaly within time window
        pass

5.3 Compliance Report Generation

Suggested daily compliance report content:

VI. Regulatory Trend Outlook

6.1 China Market

Positive Impacts:

• "Spoofing" and other improper behaviors suppressed
• "Fake quant" and market-disrupting behaviors cleaned up
• Enhanced market vitality and resilience

Long-term Outlook:

• Standardized regulatory environment will eliminate inferior institutions
• Raise overall industry standards
• Protect investor interests

6.2 Global Trends

VII. Further Reading

Official Documents

• CSRC: "Securities Market Algorithmic Trading Management Regulations (Trial)"
• Shanghai/Shenzhen/Beijing Exchanges: "Algorithmic Trading Management Implementation Details"
• FINRA: Regulatory Notice 24-09
• SEC: 2024 Examination Priorities
• ESMA: MiFID II/MiFIR Technical Standards

Industry Reports

• FINRA 2025 Annual Regulatory Report
• SEC 2024 Fiscal Year Enforcement Results

Core Insight: Regulation is the "second layer of risk control" for quantitative trading. Compliance is not a burden but protection - protecting market fairness and ensuring your strategy can run long-term.