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Aggregate Asset Management
Singapore-based Aggregate Asset Management (AAM) said yesterday that it is is expanding the use of its proprietary AI-driven machine learning model, “Deep Deep,” to manage its Aggregate Value Fund.

The firm is harnessing AI at a time when heightened market volatility is driving greater investor focus on diversification and downside protection. The fund targets a compound annual growth rate of 7 to 9 per cent, AAM said in a statement.

Set up in 2012 as a deep-value fund focused primarily on Asia, the AVF’s strategy has since evolved significantly, aided by the data-handling capacity of AI. Today, the fund invests in almost 900 listed companies across 17 countries, including Singapore, Japan, the US and Germany, with assets under management exceeding S$600 million ($391 million).

AAM said it began developing its machine learning capabilities in 2016. Over five years, the firm has tested and refined the model using 10 years of historical market data across up to 20 countries before formally integrating machine learning into AVF in 2021.

“Humans can typically process only five to seven indicators at a time, whereas our machine learning model can evaluate more than 150 factors before a final human review,” Eric Kong, co-founder, fund manager and executive director at Aggregate Asset Management, said. “We believe more indicators are necessary for building a more resilient portfolio across different markets and market cycles.”

The firm said that before machine learning was introduced into the stock-picking process, the AVF maximum drawdown was 28.85 per cent. Since machine learning was incorporated in 2021, maximum drawdown has reduced to around 12.36 per cent as at February 2026. A smaller maximum drawdown indicates that a fund experienced a lower peak-to-trough decline during a market downturn.