市场形态周报（20250707-20250711）：本周指数普遍上涨-20250713

Quantitative Models and Construction 1. Model Name: Heston Model - Model Construction Idea: The Heston model is used to calculate the implied volatility of near-month at-the-money options, which serves as a market fear index. It reflects market participants' expectations of future volatility[7]. - Model Construction Process: The Heston model is a stochastic volatility model where the variance of the asset price follows a mean-reverting square-root process. The model is defined by the following equations: $ dS_t = \mu S_t dt + \sqrt{v_t} S_t dW_t^1 $ $ dv_t = \kappa (\theta - v_t) dt + \sigma \sqrt{v_t} dW_t^2 $ Here: - $S_t$: Asset price - $v_t$: Variance process - $\mu$: Drift rate of the asset price - $\kappa$: Rate of mean reversion of variance - $\theta$: Long-term variance - $\sigma$: Volatility of volatility - $W_t^1, W_t^2$: Two Wiener processes with correlation $\rho$[7]. - Model Evaluation: The Heston model is widely used in financial markets for its ability to capture the stochastic nature of volatility, making it a robust tool for implied volatility estimation[7]. --- Quantitative Factors and Construction 1. Factor Name: Multi-Industry Timing Factor (Scissor Difference) - Factor Construction Idea: This factor is based on the difference between the number of stocks with bullish and bearish signals within an industry. It is used to construct an industry timing strategy[15]. - Factor Construction Process: - Define the number of stocks with bullish signals as $N_{bullish}$ and bearish signals as $N_{bearish}$. - Compute the scissor difference as: $ \text{Scissor Difference} = N_{bullish} - N_{bearish} $ - Normalize the scissor difference by the total number of stocks in the industry to obtain the scissor difference ratio: $ \text{Scissor Difference Ratio} = \frac{N_{bullish} - N_{bearish}}{N_{total}} $ - Use this ratio to construct an industry timing strategy[15]. - Factor Evaluation: The backtesting results show that the timing model outperforms the respective industry indices in all cases, demonstrating excellent historical performance[15]. --- Backtesting Results of Models and Factors 1. Heston Model - Implied Volatility Results: - SSE 50: 14.41% (+2.91% WoW)[9] - SSE 500: 15.4% (+0.83% WoW)[9] - CSI 1000: 18.09% (+1.24% WoW)[9] - CSI 300: 14.48% (+3.15% WoW)[9] 2. Multi-Industry Timing Factor - Performance Metrics: - The timing model outperformed the respective industry indices in all cases, with a 100% success rate in backtesting[15]. - Specific industries with bullish signals include retail, light manufacturing, home appliances, and others[18].