HTSC(SH:601688) HTSC·2025-08-10 10:40Quantitative Models and Construction Methods Genetic Programming Industry Rotation Model - Model Name: Genetic Programming Industry Rotation Model - Model Construction Idea: Directly extract factors from industry index data such as volume, price, and valuation, and update the factor library at the end of each quarter[30] - Model Construction Process: The model adopts weekly frequency rebalancing, selecting the top five industries with the highest composite multi-factor scores for equal-weight allocation every weekend[30] - Model Evaluation: The model has achieved an absolute return of 28.79% this year, outperforming the industry equal-weight benchmark by 17.68 percentage points[30] - Model Testing Results: - Annualized Return: 31.39% - Annualized Volatility: 18.12% - Sharpe Ratio: 1.73 - Maximum Drawdown: -19.63% - Calmar Ratio: 1.60 - Last Week Performance: 3.15% - Year-to-Date (YTD): 28.79%[32] Absolute Return ETF Simulation Portfolio - Model Name: Absolute Return ETF Simulation Portfolio - Model Construction Idea: The asset allocation weights are mainly calculated based on the recent trends of various assets, with stronger trend assets assigned higher weights. The internal equity asset allocation weights directly adopt the monthly views of the monthly frequency industry rotation model[34] - Model Construction Process: The model's latest holdings include dividend style ETFs and ETFs related to pharmaceuticals, non-ferrous metals, media, steel, and energy chemicals[36] - Model Evaluation: The model has risen by 0.34% last week and has accumulated a 5.69% return this year[34] - Model Testing Results: - Annualized Return: 6.52% - Annualized Volatility: 3.81% - Maximum Drawdown: 4.65% - Sharpe Ratio: 1.71 - Calmar Ratio: 1.40 - Year-to-Date (YTD): 5.69% - Last Week Performance: 0.34%[39] Global Asset Allocation Simulation Portfolio - Model Name: Global Asset Allocation Simulation Portfolio - Model Construction Idea: Predict future returns of global major assets using a cycle three-factor pricing model, and construct the portfolio using a "momentum selects assets, cycle adjusts weights" risk budgeting framework[40] - Model Construction Process: The strategy currently overweights bonds and foreign exchange, with higher risk budgets assigned to assets such as Chinese bonds and US bonds[40] - Model Evaluation: The strategy has achieved an annualized return of 7.22% in the backtest period, with a Sharpe ratio of 1.50[40] - Model Testing Results: - Annualized Return: 7.22% - Annualized Volatility: 4.82% - Maximum Drawdown: -6.44% - Sharpe Ratio: 1.50 - Calmar Ratio: 1.12 - Year-to-Date (YTD): -3.04% - Last Week Performance: 0.61%[41] Quantitative Factors and Construction Methods Sentiment Indicators - Factor Name: Sentiment Indicators - Factor Construction Idea: Construct sentiment indicators from the perspectives of the put-call ratio, implied volatility, and basis in the options and futures markets[2] - Factor Construction Process: - Put-Call Ratio: Observe the ratio of the trading volume of call options to put options in the 50ETF and 500ETF options markets[17] - Implied Volatility: Construct the implied volatility ratio series of call and put options[20] - Basis: Construct the annualized basis rate weighted by the open interest for the four major stock index futures products[26] - Factor Evaluation: The sentiment indicators show that the previous overheating sentiment in the A-share market has continued to ease[2] Factor Backtesting Results Sentiment Indicators - Put-Call Ratio: The ratio has significantly fallen from the high levels observed on July 23, indicating a more rational market sentiment[17] - Implied Volatility Ratio: Despite the stock market rebound last week, the implied volatility ratio of call options to put options has been trending downward, further reflecting rational investor sentiment[20] - Annualized Basis Rate: The basis rate has been fluctuating downward, indicating rational sentiment in the futures market[26]