- The report tracks various types of daily frequency data for ETFs, divided into "broad-based" and "thematic" sub-tables based on the indices they track[2] - The RSI (Relative Strength Index) is calculated using the formula: $ RSI = 100 – 100 / (1 + RS) $, where RSI is the ratio of average gains to average losses over a 12-day period. RSI > 70 indicates an overbought market, while RSI < 30 indicates an oversold market[2] - The net purchase amount (in billions) is calculated using the formula: $ NETBUY(T) = NAV(T) – NAV(T-1) * (1 + R(T)) $, where NETBUY(T) is the net purchase amount, NAV(T-1) is the ETF's net asset value from the previous trading day[2] - The report includes various metrics for ETFs such as intraday trend, management fee rate, tracking index, ETF name, security code, T+0 trading support, market capitalization, price change percentage, RSI, net purchase amount, trading volume, and institutional holding percentage[4] - The report provides detailed data on multiple ETFs, including their market capitalization, price change percentage, RSI, net purchase amount, trading volume, and institutional holding percentage[4] - The report covers a wide range of ETFs tracking different indices such as CSI 300, CSI 500, CSI 800, CSI 1000, CSI 2000, SSE 50, SSE STAR 50, and various thematic indices like consumption electronics, non-bank financials, banks, dividends, new energy, semiconductors, and more[4][6]

Quantitative Models and Construction Methods 1. Model Name: RSI (Relative Strength Index) - **Model Construction Idea**: RSI is used to measure the relative strength of price movements over a specific period, identifying overbought or oversold market conditions[2] - **Model Construction Process**: The RSI is calculated using the formula: $ RSI = 100 - \frac{100}{1 + RS} $ Where: - $ RS = \frac{\text{Average Gain over N periods}}{\text{Average Loss over N periods}} $ In this report, the RSI is calculated over a 12-day period. - RSI > 70 indicates an overbought market - RSI < 30 indicates an oversold market[2] - **Model Evaluation**: RSI is a widely used technical indicator for short-term market trend analysis, providing actionable insights for traders[2] 2. Model Name: Net Purchase (Net Subscription) - **Model Construction Idea**: This model calculates the net subscription amount of ETFs to track fund inflows and outflows[2] - **Model Construction Process**: The formula for Net Purchase is: $ NETBUY(T) = NAV(T) - NAV(T-1) \times (1 + R(T)) $ Where: - $ NETBUY(T) $ is the net subscription amount on day T - $ NAV(T) $ is the net asset value on day T - $ R(T) $ is the return on day T[2] - **Model Evaluation**: This metric is useful for understanding investor sentiment and fund flow dynamics in the ETF market[2] --- Model Backtesting Results RSI Model - RSI values for various ETFs: - Huatai-PineBridge CSI 300 ETF: 67.83[4] - E Fund CSI 300 ETF: 73.55[4] - ChinaAMC CSI 300 ETF: 57.08[4] - Bosera CSI 500 ETF: 69.93[4] - E Fund CSI 500 ETF: 71.67[4] - E Fund SSE STAR 50 ETF: 55.07[4] Net Purchase Model - Net Purchase values for various ETFs: - Huatai-PineBridge CSI 300 ETF: -7.83 billion[4] - E Fund CSI 300 ETF: -0.03 billion[4] - ChinaAMC CSI 300 ETF: -26.34 billion[4] - Bosera CSI 500 ETF: -1.45 billion[4] - E Fund CSI 500 ETF: -0.45 billion[4] - E Fund SSE STAR 50 ETF: 1.64 billion[4] --- Quantitative Factors and Construction Methods 1. Factor Name: Institutional Holding Ratio - **Factor Construction Idea**: This factor measures the proportion of ETF holdings owned by institutional investors, reflecting institutional confidence and participation[3] - **Factor Construction Process**: The institutional holding ratio is derived from the latest annual or semi-annual reports of ETFs, excluding holdings by linked funds. The data is estimated and may have deviations due to reporting delays[3] - **Factor Evaluation**: This factor provides insights into institutional investor behavior, which is often considered a signal of market confidence[3] --- Factor Backtesting Results Institutional Holding Ratio - Institutional holding ratios for various ETFs: - Huatai-PineBridge CSI 300 ETF: 83.06%[4] - E Fund CSI 300 ETF: 88.03%[4] - ChinaAMC CSI 300 ETF: 91.03%[4] - Bosera CSI 500 ETF: 77.51%[4] - E Fund CSI 500 ETF: 78.89%[4] - E Fund SSE STAR 50 ETF: 43.66%[4]