KraneShares has unveiled its latest China-focused ETF, an innovative fund that harnesses artificial intelligence to capture alpha within the onshore equities market.
KraneShares views Chinese A-Shares as a compelling opportunity for alpha generation due to their unique market characteristics.
The KraneShares China Alpha Index ETF (KCAI US) has been listed on NYSE Arca with an expense ratio of 0.79%.
The fund tracks the Qi China Alpha Index which seeks to outperform the CSI 300 Index, a benchmark for the performance of large-cap Chinese A-Shares – stocks listed locally on the Shanghai and Shenzhen stock exchanges.
KCAI’s index was developed by its sub-advisor, Quant Insight, to generate excess returns in China A-Shares through an alpha optimization filtering process combined with proprietary AI technology.
The index delivers long-only exposure to a subset of stocks selected exclusively from the CSI 300 universe. No individual stock may account for more than 5% of the total allocation, and the index is rebalanced every month.
KraneShares highlights the significant underrepresentation of Chinese A-Shares in global indices. Despite China’s economic prominence, these shares account for only 2.57% of the MSCI ACWI, compared to the United States’ dominant 64.70% weight.
Chinese A-Shares have also demonstrated an unusually low correlation with global markets, averaging below 0.4 over the past decade. This low correlation suggests that including Chinese A-Shares in a portfolio could provide substantial diversification benefits.
Furthermore, the market’s unique characteristics, such as high retail investor participation and inherent volatility, further position Chinese A-Shares as a potential source of alpha for investors seeking to enhance portfolio performance.
Brendan Ahern, CIO of KraneShares, commented: “It has been challenging for active managers to produce consistent alpha in the China A-Share market in recent years. We believe KCAI’s AI-driven approach has the potential to outperform the broad market consistently and its rules-based strategy could be used as a source of portable alpha for global investors.”
Mahmood Noorani, CEO of Quant Insight, added: “China’s A-Share market is a prime candidate for this strategy. Our research shows it has inefficiencies and volatility. It is also dominated by retail investors. This creates significant market ‘noise’—an opportunity our AI-powered machine learning algorithm is uniquely positioned to exploit.”