What Happened
China's quantitative hedge funds were hit broadly in October as a deeper tech selloff erased earlier gains. That stumble threatens a boom that had drawn in billions earlier this year when algorithm-led approaches outpaced the market.
The pain was not confined to China. Hedge funds globally struggled in October as investors questioned how long the AI trade could hold up, and those worries deepened when the US midterm election results set off another selloff in tech shares worldwide.
How Big Were the Losses
According to China Merchants Futures Co., all six long-only quant strategies sank more than 10% in October, leaving what had been year-to-date gains as losses of at least 6%. Market-neutral funds, which seek to offset longs with shorts, still lost between 3% and 5% for the month.
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Index Moves and Benchmarks
China's CSI 300 Index slid 8.5% in October, its worst month in more than a decade as worries about weak economic growth weighed on sentiment. A Nov. 3 report from China Merchants Futures said products linked to the CSI 300 fell 11% in October, resulting in an 8.5% loss for the year.
Funds tied to the CSI 1000 fared worse, dropping 16.7% for the month, which left their year-to-date return at a 13% loss. For all six long-only strategies, October's excess returns were negative and lagged the CSI A500 by as much as 4.4 percentage points. Even so, their full-year edge remained, outpacing the CSI 2000 by 18.5 percentage points - the best relative result among the strategies.
Shenzhen Golden Axe Fund Sales Co. said the 68 CSI 1000 index-enhancement products it tracks fell an average of 9.3% in October's final week. All but one were negative for the year, with the largest decline at 26%.
What It Means for Your Portfolio
The bottom line: when tech leadership cracks, quant-heavy China exposures can move fast and in tandem with small and large cap benchmarks. If you hold China-focused quant or index-enhancement strategies tied to the CSI 300 or CSI 1000, these figures frame how October's drawdown stacked up against their reference indexes.
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