Quantitative Models and Construction Methods 1. Model Name: Timing System Signal (Wind All A Moving Average Distance Model) - **Model Construction Idea**: This model uses the distance between the short-term moving average (20-day) and the long-term moving average (120-day) of the Wind All A Index to determine the market's overall trend. A positive and expanding distance indicates an upward trend[2][9]. - **Model Construction Process**: 1. Calculate the 20-day moving average (short-term) and the 120-day moving average (long-term) of the Wind All A Index. - Latest values: 20-day MA = 5658, 120-day MA = 5241[2][9]. 2. Compute the percentage difference between the two moving averages: $ \text{Distance} = \frac{\text{20-day MA} - \text{120-day MA}}{\text{120-day MA}} \times 100\% $ - Current distance = 7.96%[2][9]. 3. Interpret the signal: If the distance is greater than 3% and positive, the market is in an upward trend[2][9]. - **Model Evaluation**: The model effectively captures the market's upward momentum and provides a clear signal for maintaining high equity positions during positive trends[2][9]. 2. Model Name: Industry Allocation Model - **Model Construction Idea**: This model identifies industries with potential for medium-term outperformance based on factors such as policy support, valuation, and growth trends[2][10]. - **Model Construction Process**: 1. Analyze industry-specific drivers, including policy incentives and growth catalysts. 2. Identify sectors with "distressed reversal" characteristics or benefiting from policy-driven growth. 3. Recommend sectors such as innovative pharmaceuticals, securities insurance, photovoltaics, coal, and non-ferrous metals. 4. Use the TWO BETA model to emphasize technology-related sectors, including military, computing power, and batteries[2][10]. - **Model Evaluation**: The model provides actionable insights for sector rotation, aligning with macroeconomic and policy trends[2][10]. 3. Model Name: Position Management Model - **Model Construction Idea**: This model determines optimal equity allocation levels based on valuation metrics and market trends[3][10]. - **Model Construction Process**: 1. Assess valuation levels of the Wind All A Index using PE and PB ratios. - Current PE: 70th percentile (moderate level). - Current PB: 30th percentile (low level)[3][10]. 2. Combine valuation analysis with timing signals (e.g., moving average distance and profit-making effect). 3. Recommend equity allocation levels based on the above factors. - Current recommendation: 80% equity allocation[3][10]. - **Model Evaluation**: The model balances valuation and trend analysis, providing a systematic approach to equity allocation[3][10]. --- Model Backtesting Results 1. Timing System Signal - Moving average distance: 7.96% (greater than the 3% threshold, indicating an upward trend)[2][9]. 2. Industry Allocation Model - Recommended sectors: Innovative pharmaceuticals, securities insurance, photovoltaics, coal, non-ferrous metals, military, computing power, and batteries[2][10]. 3. Position Management Model - PE: 70th percentile (moderate level)[3][10]. - PB: 30th percentile (low level)[3][10]. - Recommended equity allocation: 80%[3][10]. --- Quantitative Factors and Construction Methods 1. Factor Name: Profit-Making Effect - **Factor Construction Idea**: This factor measures the market's ability to generate profits for investors, serving as a key indicator of market sentiment and potential capital inflows[2][10]. - **Factor Construction Process**: 1. Calculate the profit-making effect value based on market performance. - Current value: 3.73% (positive)[2][10]. 2. Interpret the signal: A positive value indicates sustained investor confidence and potential for further capital inflows[2][10]. - **Factor Evaluation**: The factor is a reliable indicator of market sentiment, supporting timing and allocation decisions[2][10]. --- Factor Backtesting Results 1. Profit-Making Effect - Current value: 3.73% (positive, indicating sustained market confidence)[2][10].

Core Viewpoint - The recent economic data in China exceeded expectations, leading to a collective rebound in A-shares despite external conflicts, with over 3,400 stocks rising [1][5]. Economic Data - China's industrial added value in May increased by 5.8% year-on-year, surpassing the expected 5.7% and the previous value of 6.1% [6]. - The retail sales of consumer goods in May reached 41,326 billion yuan, growing by 6.4% year-on-year, exceeding the expected 4.9% and the previous 5.1% [6]. Impact of External Conflicts - The geopolitical tensions in the Middle East have significant implications, but their actual impact on Chinese assets is limited. Short-term market fluctuations may provide investment opportunities [4][8]. - Analysts suggest that while external conflicts may trigger risk-averse sentiments globally, the fundamental factors within China will primarily dictate market trends [9]. Investment Opportunities - Goldman Sachs remains optimistic about A-shares, indicating a return of global capital to China, which could disproportionately benefit major index-weighted stocks like Tencent, Alibaba, Xiaomi, BYD, Meituan, NetEase, Midea, Heng Rui Pharmaceutical, Ctrip, and Anta [9]. - The upcoming Lujiazui Forum on June 18-19 is expected to announce significant financial policies, which could enhance domestic economic resilience [9]. Sector Performance - Recent trends show that sectors such as wind power, gaming, media, and computing have performed well, while pharmaceuticals and precious metals have seen corrections [3]. - The period from June 15 to July 15 has historically shown a high performance rate for industries with positive earnings forecasts, indicating potential investment opportunities in these sectors [10]. Market Rotation - Following the recent surge in innovative drugs and new consumption sectors, there is speculation that these themes may have reached a temporary peak. Funds are beginning to rotate towards technology sectors, including AI, media, and military technology [15][24]. - The technology sector has shown resilience during past geopolitical conflicts, suggesting it may continue to perform well despite external pressures [26].

近期AI（人工智能）产业链投资热度不减，市场聚焦算力方向。 5月8日，在光模块（CPO）概念股大涨的带动下，通信、5G主题ETF（交易型开放式指数基金）大幅反 弹，多只ETF涨超3%。而受黄金价格大幅跳水影响，全市场最大的黄金ETF放量下跌。此外，军工、高 端装备、国防等主题ETF涨幅居前。 受访人士认为，军工板块的上涨与地缘局势紧张有关，黄金价格跳水则与价格见顶回落等因素有关。 通信和军工ETF领涨 数据显示，截至5月8日收盘，概念指数光模块（CPO）以4.91%的涨幅领跑，通用航空、商业航空、军 工信息化三大概念指数均涨超4%。其中，领涨的光模块被市场称为A股"英伟达"概念股，是AI算力的代 表，该赛道三大热门股中，新易盛（300502）和中际旭创（300308）大涨超10%，天孚通信（300394） 大涨超7%。受AI算力和光模块上涨的带动，多只通信、5G相关主题ETF领涨同类，多只ETF涨幅超过 4%。 关注国产替代方向 调整许久的光模块再次获得关注。华西证券（002926）最新研究指出，短期内，考虑全球地缘政治冲 突、关税贸易冲突等一系列不确定性影响，国产算力建设加速对国内市场需求有望提振。而海外云 ...