Summary of Conference Call Records Industry or Company Involved - The discussion primarily revolves around the **Chinese active investment fund industry** and its comparison with the **U.S. active investment fund industry**. Core Points and Arguments 1. **Alpha Generation in China**: Chinese active fund managers demonstrate stronger alpha generation capabilities over the long term, especially in volatile market conditions, achieving significant excess returns. This year, the median return of many public sector active funds exceeded 30 percentage points [1][5][11]. 2. **Market Opportunities**: The Chinese market offers more opportunities for excess returns compared to the U.S. market, attributed to differences in index composition and the emergence of new industries such as robotics, innovative pharmaceuticals, new energy, and AI during China's economic transition [1][4][9]. 3. **Benchmark Selection**: Under the new regulatory framework, it is essential to choose a representative broad-based index that aligns with the investment style, and to regularly compare performance against this benchmark to ensure transparency and accuracy [1][6][18]. 4. **Performance of Chinese Active Funds**: Chinese active public funds have performed exceptionally well this year, with stock-type public funds rising over 20% since the peak on October 8 of the previous year. The proportion of equity public funds outperforming the CSI 300 index reached 70%, a historical high [1][13][14]. 5. **Comparison with U.S. Active Funds**: U.S. active funds are increasingly moving towards passive strategies due to the difficulty of beating indices, with only 27% of active funds outperforming the S&P 500. In contrast, over 90% of Chinese products have historically outperformed their passive counterparts [2][4][18]. 6. **Investment Environment**: Active investment thrives in volatile market environments, where selective stock picking and industry allocation can yield significant excess returns. The outlook for Chinese active investment remains positive as skilled fund managers are expected to continue outperforming market benchmarks [5][17]. 7. **Sector Performance**: Key sectors that have shown strong performance this year include electronics, new energy, communications, and pharmaceuticals, indicating a recovery in the active investment landscape [15][14]. 8. **Investment Strategy Recommendations**: Different investment styles should adopt specific strategies: - **Balanced**: Prefer broad-based indices like CSI 300 or A500. - **Growth**: Opt for growth-oriented indices such as CSI 300 Growth. - **Value and Dividend**: Choose broad-based indices rather than specialized value indices. - **Industry-Specific**: Match benchmarks to specific sectors of interest [29]. Other Important but Possibly Overlooked Content 1. **Impact of Economic Cycles**: The past few years saw a "barbell" investment strategy due to macroeconomic downturns, but the current environment is different, with many industries entering a harvest phase, leading to clearer investment signals [16]. 2. **Benchmark Performance**: The performance of benchmarks like the CSI 300 has been relatively weak compared to the S&P 500, but Chinese fund managers have shown a greater ability to generate alpha over the long term [8][20]. 3. **Investor Behavior**: The shift towards passive investment in the U.S. is influenced by historical financial crises that made investors wary of high volatility risks, leading to a preference for more stable investment strategies [2][10].

- The report discusses the construction of an out-of-sample effective index allocation portfolio, focusing on three key aspects: price judgment, tool expression, and risk control. Price judgment involves forming predictions on the price trends of major assets, industries, or individual stocks using macro, meso, and micro-level information through qualitative, quantitative, or mixed methods. Tool expression refers to selecting investable tools for portfolio implementation, while risk control manages potential losses in the portfolio[9] - The primary goal of the strategy is to reduce overfitting risks to enhance out-of-sample effectiveness. This is achieved through three measures: expanding the pool of targets, neutralizing factors to reduce style impact, and managing portfolio risks to mitigate the impact of tail risks on excess returns. Signal sustainability outside the sample is emphasized as a critical factor[2] - The report highlights the advantages of using equity indices as allocation tools. Indices, being a basket of stocks, can hedge individual stock-specific risks to some extent. They also serve as better tools for expressing investment views due to their distinct target attributes. Additionally, risk models at the index level are more effective, providing better risk management outcomes[11][12] - The construction of the index risk control model follows a process similar to stock risk control models but requires additional steps to synthesize index-level data. The process includes selecting indices published before the given trading day, ensuring all index components are A-shares, obtaining index component lists and weights, and calculating weighted scores for industry/style exposures based on real-time weights. The model's effectiveness is significantly higher than individual stock models, with industry contributions surpassing style contributions[22][23] - The report categorizes factors into four main types: fundamental, analyst, price-volume, and high-frequency. Each type is further divided into subcategories, such as growth, profitability, valuation, momentum reversal, volatility, liquidity, and fund flows. The factor library includes a total of 275 factors, with specific counts for each subcategory[26][27][30] - Historical performance analysis of sub-strategies shows varying correlations among them, emphasizing the necessity of multi-strategy approaches. For the period of January to August 2025, fundamental factors like profitability and growth, as well as price-volume sub-strategies, performed well. However, individual sub-strategies experienced periodic drawdowns, highlighting the importance of diversification[27][30] - Based on selected sub-strategies, the report constructs a composite index scoring signal for portfolio allocation. Anchored to the CSI All Share Index, the portfolio controls deviations in industry and major style exposures. The out-of-sample performance, including returns, drawdowns, and tracking errors, aligns closely with backtest results[32][33] - The report evaluates the use of existing products, including active and passive types, for tracking the target index portfolio. Combining active and passive products yields better out-of-sample tracking results compared to using ETFs alone. While ETFs perform well in certain months, the combined approach demonstrates superior consistency[37][38] - The report identifies the overall performance of factors in 2025, with fundamental factors like growth and profitability, as well as price-volume factors such as momentum reversal, volatility, and liquidity, showing strong results[36]

Group 1 - The current valuation of the ChiNext board is still in an undervalued period, with the 10-year price-to-earnings ratio percentile remaining below 50%, indicating that the index still offers good cost-performance for allocation [1] - According to China Galaxy Securities, the overall valuation level of A-shares is in a reasonable range, but there are significant differences among industries, with some industries being overvalued while others are undervalued but showing notable profit improvements [1] - As of September 1, 2025, the ChiNext index has seen a decline of 3.71%, with component stocks showing mixed performance, highlighting the volatility within the sector [3] Group 2 - The ChiNext ETF from Ping An has seen a net value increase of 21.31% over the past three years, ranking in the top two among comparable funds, indicating strong performance [4] - The ChiNext ETF has a management fee rate of 0.15% and a custody fee rate of 0.05%, which are among the lowest in comparable funds, suggesting cost efficiency [4] - As of September 1, 2025, the ChiNext ETF has a tracking error of 0.016% over the past three months, demonstrating its close tracking of the ChiNext index [5]