Systematic hedge funds suffered consecutive losses in October | High-frequency models and quantitative strategies face drawdown pressure

🕘 Release Date: October 13, 2025

📍 Source: BrokerHiveX Global Macro

🧩 Category: Quantitative Trading | Hedge Funds | Market Volatility

1. Background: Goldman Sachs report reveals a "systematic retracement wave"

In October 2025, Goldman Sachs released its latest market liquidity tracking report, pointing out that
Systematic hedge funds experienced their most significant daily losses since last year in early October.
The average drawdown was 1.8%–2.6% , with some high-frequency model strategy funds losing more than 4% .

The report points out that the main sources of losses include:

• The short-term rebound in U.S. Treasury yields caused the trend model to fail;

• AI-driven quantitative programs fail to capture sudden changes in macroeconomic policies;

• High-frequency traders are forced to reduce their positions and cut losses when volatility is amplified.

2. Core Reason: The Model Over-Relies on the “Stability Assumption”

Goldman Sachs mentioned in the report that in the past three months, the algorithmic models of some systematic funds have over-reliant on the "low volatility environment" assumption.
However, changes in policy signals from the Federal Reserve and the Bank of Japan in October led to a structural mismatch in the market.

“The model is correct, but the world is changing.” — Goldman Sachs QIS

III. Market Impact: A Sudden Drop in Liquidity and the Spread of Volatility

In early October, position reductions by quantitative and systematic funds exacerbated market liquidity tensions.

According to joint data from Goldman Sachs and JPMorgan Chase:

• Systematic funds reduced their holdings of global stocks by approximately $32 billion in a week;

• CTA (trend-following fund) positions fell by more than 25% ;

• The global stock market volatility index (VIX) rose to 22.8 points in the short term.

This caused a sharp drop in short-term market liquidity, triggering further programmatic sell-offs .
Forming a "Loss Feedback Loop".

IV. Mainly Affected Fund Categories

Source: Goldman Sachs Quantitative Investment Strategies (QIS) Report, 2025

5. Analysts’ View: Risk Shifts to “Model Stability”

Goldman Sachs strategists pointed out that this round of pullback did not come from the decline of traditional markets, but from the "crowded trading effect" caused by the excessive consistency of model behavior .

• Multiple funds use similar parameter training models (such as macro factor regression and LSTM trend prediction).
  This results in a collective reduction in positions and intensified volatility when the trigger signal reversal occurs.

• The average holding period of the high-frequency model is only 30 minutes, and the retracement period is short but the frequency is high.

Morgan Stanley added:
“The key challenge facing AI quantitative funds today is not computing power, but insufficient dynamic adaptive capabilities .”

6. Potential risk transmission: What does it mean for the market?

1️⃣ Short-term risks : Volatility increases, and the elasticity of CTA and high-frequency trading to market prices decreases.
2️⃣ Medium-term risk : If systemic funds continue to outflow, it may trigger a "passive deleveraging wave".
3️⃣ Long-term risks : AI model training sets rely on old cycle data and may face long-term strategy reconstruction in the future.

The Federal Reserve’s internal research department (FRB Labs) noted:

"Systemic funding synchronicity is the new variable of financial stability."

7. Strategy Adjustment: How Funds Should Respond

Faced with continuous drawdowns, many quantitative institutions are taking the following countermeasures:

• Expanding dynamic factor weights : Improving the real-time response of macroeconomic policy variables;

• Introducing an AI risk monitoring module : real-time assessment of model overfitting or parameter drift risks;

• Cross-market signal cross-validation : Simultaneously referencing signals from the bond, foreign exchange, and commodity markets to reduce consistency risk;

• Strengthen the manual intervention mechanism : manually review trading signals when the model outputs abnormally.

The industry expects that some institutions will bring forward the 2026 model update cycle to the end of this year.

8. Conclusion: The “algorithmic limits” of quantitative funds are once again revealed

The concentrated withdrawal of systematic funds not only exposed the vulnerability of high-frequency models,
It also reminds the market that in the AI era, algorithms are not omnipotent and liquidity remains the ultimate boundary condition .

As the Goldman Sachs report concludes:

“The core issue in financial markets over the past 20 years has been human emotion, and now it’s algorithmic consensus.”

🔗 References

• Reuters – Systematic hedge funds hit with daily losses in October, says Goldman Sachs (2025)

• Goldman Sachs Quantitative Investment Strategies Report, Oct 2025