Quantitative Models and Construction Methods Model 1: Fund Selection Strategy Based on Trading Motivation Factor and Stock Price Difference Income Factor - **Model Name**: Fund Selection Strategy Based on Trading Motivation Factor and Stock Price Difference Income Factor - **Construction Idea**: The strategy aims to select funds with high stock price difference income, active trading motivation, and low possibility of performance dressing[2] - **Construction Process**: - The strategy combines the trading motivation factor and the stock price difference income factor - The trading motivation factor is constructed by classifying the trading motivations of funds[23] - The stock price difference income factor is derived from the stock price difference income in the fund's income statement[23] - The strategy adopts a semi-annual rebalancing approach, rebalancing at the end of March and August each year[23] - **Evaluation**: The strategy significantly outperformed the Wind Partial Equity Hybrid Fund Index in January 2026[2] Model 2: Fund Selection Strategy Based on Fund Manager's Trading Uniqueness - **Model Name**: Fund Selection Strategy Based on Fund Manager's Trading Uniqueness - **Construction Idea**: The strategy aims to capture the unique trading patterns of fund managers to generate excess returns[3] - **Construction Process**: - Construct a network based on the detailed holdings and transactions of fund managers[31] - Develop an indicator to measure the uniqueness of fund managers' trading[31] - The strategy adopts a semi-annual rebalancing approach, rebalancing at the beginning of April and September each year[31] - **Evaluation**: The strategy outperformed the Wind Partial Equity Hybrid Fund Index in January 2026[3] Model 3: Industry Theme ETF Rotation Strategy Based on Application Information - **Model Name**: Industry Theme ETF Rotation Strategy Based on Application Information - **Construction Idea**: The strategy aims to select industry theme ETFs similar to the applied ETFs to capture market investment hotspots[4] - **Construction Process**: - Conduct event-driven research on the entire issuance process of funds[36] - Construct the industry theme application similarity factor (T+1) based on the information disclosed during the application material public stage[36] - The strategy adopts a monthly rebalancing approach, with a transaction fee rate of 0.1% per side[36] - **Evaluation**: The strategy significantly outperformed the CSI 800 Index in January 2026[4] Model Backtesting Results Fund Selection Strategy Based on Trading Motivation Factor and Stock Price Difference Income Factor - **Monthly Return**: 10.96%[27] - **Annualized Return**: 11.56%[27] - **Annualized Volatility**: 21.60%[27] - **Sharpe Ratio**: 0.54[27] - **Maximum Drawdown**: 48.39%[27] - **Annualized Excess Return**: 3.87%[27] - **Excess Maximum Drawdown**: 19.22%[27] - **Information Ratio (IR)**: 0.64[27] - **Monthly Excess Return**: 3.60%[27] Fund Selection Strategy Based on Fund Manager's Trading Uniqueness - **Monthly Return**: 8.03%[35] - **Annualized Return**: 14.26%[35] - **Annualized Volatility**: 19.47%[35] - **Sharpe Ratio**: 0.73[35] - **Maximum Drawdown**: 37.26%[35] - **Annualized Excess Return**: 5.70%[35] - **Excess Maximum Drawdown**: 10.84%[35] - **Information Ratio (IR)**: 1.10[35] - **Monthly Excess Return**: 0.86%[35] Industry Theme ETF Rotation Strategy Based on Application Information - **Monthly Return**: 22.66%[40] - **Annualized Return**: 22.45%[40] - **Annualized Volatility**: 21.39%[40] - **Sharpe Ratio**: 1.05[40] - **Maximum Drawdown**: 34.89%[43] - **Annualized Excess Return**: 13.84%[43] - **Excess Maximum Drawdown**: 19.07%[43] - **Information Ratio (IR)**: 0.76[43] - **Monthly Excess Return**: 18.18%[43]

- The "Style Rotation Fund Selection Strategy" is based on constructing an absolute active rotation indicator using stock holdings from two reporting periods to identify style rotation or stable style funds. The strategy employs semi-annual rebalancing at the end of March and August, focusing on equity-biased mixed funds and ordinary stock funds, excluding transaction costs[26][31][31] - The "Comprehensive Fund Selection Strategy Based on Fund Characteristics and Capabilities" integrates multiple selection factors such as fund size, holder structure, performance momentum, stock-picking ability, hidden trading ability, and gold content. These factors are equally weighted and combined. The strategy uses quarterly rebalancing at the end of January, April, July, and October, excluding transaction costs[35][40][40] - The "Fund Selection Strategy Based on Trading Motivation Factor and Stock Spread Income Factor" combines trading motivation factors and stock spread income factors derived from fund profit statements. It aims to select funds with high stock spread income, active trading motivation, and low likelihood of performance manipulation. The strategy employs semi-annual rebalancing at the end of March and August, focusing on active equity funds, excluding transaction costs[41][42][47] - The "Fund Manager Trading Uniqueness Strategy" constructs a network based on fund manager holdings and trading details to create a trading uniqueness indicator. The strategy uses semi-annual rebalancing at the beginning of April and September, focusing on equity-biased mixed funds, ordinary stock funds, and flexible allocation funds, excluding transaction costs[48][54][54] - The "Style Rotation Fund Selection Strategy" achieved a June return of 4.45%, annualized return of 9.05%, annualized volatility of 19.67%, Sharpe ratio of 0.46, maximum drawdown of 37.30%, annualized excess return of 3.43%, excess maximum drawdown of 11.25%, and IR of 0.46[31] - The "Comprehensive Fund Selection Strategy Based on Fund Characteristics and Capabilities" achieved a June return of 4.26%, annualized return of 13.09%, annualized volatility of 22.51%, Sharpe ratio of 0.58, maximum drawdown of 44.27%, annualized excess return of 4.92%, excess maximum drawdown of 17.38%, and IR of 0.61[40] - The "Fund Selection Strategy Based on Trading Motivation Factor and Stock Spread Income Factor" achieved a June return of 6.47%, annualized return of 9.03%, annualized volatility of 21.66%, Sharpe ratio of 0.42, maximum drawdown of 48.39%, annualized excess return of 3.09%, excess maximum drawdown of 19.13%, and IR of 0.53[47] - The "Fund Manager Trading Uniqueness Strategy" achieved a June return of 5.38%, annualized return of 9.86%, annualized volatility of 19.51%, Sharpe ratio of 0.51, maximum drawdown of 37.26%, annualized excess return of 4.30%, excess maximum drawdown of 10.84%, and IR of 0.85[54]