Quantitative Models and Construction Methods 1. Model Name: Timing Strategy Based on Dynamic Macro Event Factors for CSI Southbound Consumer Index - **Model Construction Idea**: The model aims to explore the impact of China's macroeconomic environment on the overall performance and trends of Hong Kong-listed consumer companies. It uses dynamic macro event factors to construct a timing strategy framework[3][4][21] - **Model Construction Process**: 1. **Macro Data Selection**: Over 20 macro indicators across four dimensions (economy, inflation, monetary, and credit) were tested, including PMI, PPI, M1, etc.[22][24] 2. **Data Preprocessing**: - Align data frequency to monthly - Fill missing values using the formula: $$ X_{t} = X_{t-1} + Median_{diff12} $$ - Apply filtering (e.g., one-sided HP filter): $$ \hat{t}_{t|t,\lambda} = \sum_{s=1}^{t} \omega_{t|t,s,\lambda} \cdot y_{s} = W_{t|t,\lambda}(L) \cdot y_{t} $$ - Derive factors using transformations like YoY, MoM, and moving averages[28][29][30] 3. **Event Factor Construction**: - Identify event breakout directions based on the correlation between data and asset returns - Generate event factors using methods like data breaking through moving averages, medians, or directional changes - Construct 28 different event factors per indicator[31][33] 4. **Factor Evaluation and Selection**: - Use metrics like "win rate of returns" and "volatility-adjusted returns" for screening - Select the top-performing factors based on statistical significance, win rate (>55%), and occurrence frequency[32][34] 5. **Final Macro Factor Selection**: - Five macro factors were selected based on their performance in the backtest, including "PMI: Raw Material Prices" and "YoY Growth of Aggregate Financing"[35][36] 6. **Timing Signal Construction**: - If >2/3 of factors signal bullish, the category signal is marked as 1 - If <1/3 signal bullish, the category signal is marked as 0 - Intermediate proportions are marked accordingly - Aggregate category scores determine the timing position signal[4][36][38] - **Model Evaluation**: The strategy effectively captures systematic opportunities and mitigates risks, outperforming benchmarks in most years and controlling drawdowns during market downturns[12][21] --- Model Backtest Results 1. Timing Strategy Based on Dynamic Macro Event Factors - **Annualized Return**: 9.31% (2018/11–2025/7)[11][23] - **Maximum Drawdown**: -29.72%[11][23] - **Sharpe Ratio**: 0.54[11][23] - **Return-to-Drawdown Ratio**: 0.31[11][23] - **Average Position**: 43%[11] - **Monthly Return (2025/7)**: 2.79% (vs. benchmark 2.48%)[11][13] --- Quantitative Factors and Construction Methods 1. Factor Name: PMI: Raw Material Prices - **Factor Construction Idea**: Captures inflationary pressures and their impact on consumer sector performance[36] - **Factor Construction Process**: - Data Type: Original data - Rolling Window: 96 months[36] 2. Factor Name: US-China 10Y Bond Spread - **Factor Construction Idea**: Reflects monetary policy divergence and its influence on capital flows[36] - **Factor Construction Process**: - Data Type: Original data - Rolling Window: 72 months[36] 3. Factor Name: YoY Growth of Aggregate Financing (12M Rolling) - **Factor Construction Idea**: Measures credit expansion and its implications for economic growth[36] - **Factor Construction Process**: - Data Type: Original data - Rolling Window: 96 months[36] 4. Factor Name: M1 YoY Growth - **Factor Construction Idea**: Tracks monetary liquidity and its correlation with asset prices[36] - **Factor Construction Process**: - Data Type: Original data - Rolling Window: 48 months[36] 5. Factor Name: YoY Growth of Medium- to Long-Term Loans (12M Rolling) - **Factor Construction Idea**: Indicates long-term credit trends and their impact on investment[36] - **Factor Construction Process**: - Data Type: Original data - Rolling Window: 48 months[36] --- Factor Backtest Results 1. PMI: Raw Material Prices - **Rolling Window**: 96 months[36] 2. US-China 10Y Bond Spread - **Rolling Window**: 72 months[36] 3. YoY Growth of Aggregate Financing (12M Rolling) - **Rolling Window**: 96 months[36] 4. M1 YoY Growth - **Rolling Window**: 48 months[36] 5. YoY Growth of Medium- to Long-Term Loans (12M Rolling) - **Rolling Window**: 48 months[36]

Investment Logic - The monthly timing model for the consumption sector under the Hong Kong Stock Connect shows a return of -1.66% for April 2025, outperforming the equal-weighted benchmark return of -2.21% and the CSI Hong Kong Stock Connect Consumption Index [1] - From November 2018 to April 2025, the strategy achieved an annualized return of 9.25%, with a maximum drawdown of -29.72% and a Sharpe ratio of 0.52, indicating superior performance across various metrics compared to the benchmark [1] - The strategy consistently generated positive excess returns in most years, effectively managing downside risk during periods of benchmark drawdown [1] Timing Strategy Framework - The timing strategy framework for the CSI Hong Kong Stock Connect Consumption Index is constructed based on dynamic macro event factors, focusing on the impact of China's macroeconomic conditions on the overall performance of Hong Kong consumption theme companies [2] - The strategy utilizes over 20 macroeconomic indicators across four dimensions: economy, inflation, monetary policy, and credit, to identify optimal event factors and data processing methods for each period [2] - Five macro factors were selected for their effectiveness in timing the CSI Hong Kong Stock Connect Consumption Index, with a scoring system to determine the timing position based on the proportion of bullish signals from these factors [2]