以下文章来源于36氪财经 ，作者黄绎达 郑怀舟 36氪财经 . 36氪旗下官方账号。洞见市场，比99%的投资者更聪明。 经济弱复苏再度被确认， 红利板块投资价值凸显。 文 ｜ 黄绎达 编辑 ｜ 郑怀舟 来源｜ 36氪财经（ID：krfinance） 封面来源 ｜ 视觉中国 本周（5月5日~9日）A股大盘先扬后抑，上证指数在周内上涨1.68%，于5月9日收盘报收3342点；万得全A指数本周上涨2.32%。 板块方面，本周，申万31个一级行业全部上涨，其中军工、通信、电力设备、银行等板块涨幅居前，房地产、电子、商贸零售、石油化工等板块在本周涨幅 居后。 风格方面，中小盘、科创在本周相对占优。 反映到宽基/风格指数上，北证50、万得微盘股指数、创业板50、创业板指、国证2000、创成长等指数领涨，红 利、大市值相关指数涨幅相对居后。 港股大盘的走势与A股相当，恒生指数周内上涨3.38%；恒生科技指数在本周下跌1.22%。板块方面，12个恒生行业指数在本周有9个上涨，金融、电讯、非 必选消费、能源等板块领涨，医疗保健、资讯科技、必需消费品这三个板块在本周下跌。 海外大类资产方面，美股三大指数在本周均上涨；欧洲方面，东 ...

Market Overview - The market showed an increase in cautious sentiment before the long holiday, with broad market indices experiencing a decline, while small-cap stocks stabilized and recovered [4][2]. - The week before the May Day holiday saw a balanced performance between large-cap and small-cap styles, as well as between value and growth styles, with a continued decrease in style volatility [6][2]. Market Structure - The excess return dispersion of industry indices slightly decreased, and the proportion of rising constituent stocks also saw a decline, indicating a slowdown in industry rotation [6][2]. - The trading concentration decreased, with the proportion of trading volume from the top 100 stocks rebounding from a low level, while the top five industries' trading volume proportion continued to decline [6][2]. Market Activity - Market volatility continued to decrease due to the upcoming holiday, and turnover rates also saw a reduction [7][2]. Commodity Market - There was a divergence in trend strength among commodity sectors, with energy and black metals maintaining strong trends, while non-ferrous and agricultural products showed weaker trends, and precious metals experienced a significant decline in trend strength [18][17]. - The non-ferrous sector had the highest basis momentum, while the black sector saw a rapid decline [18][17]. - Volatility across all sectors remained high, and liquidity was stable across the board [18][17]. Options Market - Implied volatility levels for the Shanghai Stock Exchange 50 and CSI 1000 indices increased, indicating some speculative sentiment in the market before the holiday [23][3]. - The skew of call options for the CSI 1000 improved, while the skew for the Shanghai Stock Exchange 50 saw a notable decline, suggesting a market expectation of small-cap stocks performing better post-holiday [23][3]. Convertible Bond Market - The valuation level of the convertible bond market slightly increased, remaining above the historical median for the past year, with a small rebound in the number of convertible bonds with low conversion premiums [27][3]. - Overall trading volume in the convertible bond market continued to recover [27][3].

Quantitative Factors and Construction Methods 1. Factor Name: Market Style Factors - **Construction Idea**: The market style factors track the balance and volatility between different market styles, such as large-cap vs. small-cap and value vs. growth[11][13] - **Construction Process**: - **Style Balance**: Measure the relative performance of large-cap vs. small-cap stocks and value vs. growth stocks to determine the market's style preference[11] - **Style Volatility**: Calculate the fluctuations in the relative performance of these styles over time to assess the stability of the market's style preference[11] - **Evaluation**: The market style factors showed a balanced preference between large-cap and small-cap stocks, as well as between value and growth stocks. Additionally, the volatility of these styles continued to decline, indicating a more stable market environment[11][13] 2. Factor Name: Market Structure Factors - **Construction Idea**: These factors analyze the dispersion of returns, sector rotation, and trading concentration to understand the structural dynamics of the market[11][13] - **Construction Process**: - **Return Dispersion**: Measure the excess return dispersion across industry indices to evaluate the variability in sector performance[11] - **Sector Rotation**: Assess the speed of sector rotation by tracking changes in sector leadership over time[11] - **Trading Concentration**: Calculate the proportion of trading volume concentrated in the top 100 stocks and the top 5 industries to gauge market concentration[11] - **Evaluation**: The market structure factors indicated a decline in return dispersion, slower sector rotation, and reduced trading concentration, suggesting a more evenly distributed market environment[11][13] 3. Factor Name: Market Activity Factors - **Construction Idea**: These factors measure the overall activity and liquidity of the market through volatility and turnover rates[12][13] - **Construction Process**: - **Volatility**: Calculate the index-level volatility to assess market stability[12] - **Turnover Rate**: Measure the turnover rate of the market to evaluate trading activity[12] - **Evaluation**: The market activity factors showed a decline in both volatility and turnover rates, reflecting reduced market activity, likely influenced by the holiday period[12][13] 4. Factor Name: Commodity Market Factors - **Construction Idea**: These factors analyze the performance, momentum, and liquidity of various commodity sectors[27][30] - **Construction Process**: - **Trend Strength**: Measure the strength of price trends in different commodity sectors, such as energy, metals, and agriculture[27] - **Basis Momentum**: Calculate the basis momentum, particularly for the metals sector, to assess the relative strength of futures prices compared to spot prices[27][30] - **Volatility**: Track the volatility levels across commodity sectors to evaluate risk[27][30] - **Liquidity**: Measure the liquidity of commodity sectors to assess trading ease[27][30] - **Evaluation**: The commodity market factors showed mixed performance, with strong trends in energy and metals, weaker trends in agriculture, and high volatility across sectors. Liquidity remained stable overall[27][30] 5. Factor Name: Options Market Factors - **Construction Idea**: These factors analyze the implied volatility and skewness of options to infer market sentiment and expectations[35] - **Construction Process**: - **Implied Volatility**: Measure the implied volatility levels of options on major indices, such as the SSE 50 and CSI 1000, to gauge market uncertainty[35] - **Skewness**: Analyze the skewness of call and put options to understand market expectations for upward or downward movements[35] - **Evaluation**: The options market factors indicated a divergence in sentiment, with increased optimism for small-cap stocks (CSI 1000) and reduced optimism for large-cap stocks (SSE 50). This suggests a potential shift in market preference post-holiday[35] 6. Factor Name: Convertible Bond Market Factors - **Construction Idea**: These factors evaluate the valuation and trading activity of the convertible bond market[38] - **Construction Process**: - **Valuation**: Measure the average conversion premium of convertible bonds to assess their relative attractiveness[38] - **Trading Activity**: Track the trading volume and turnover in the convertible bond market to evaluate market interest[38] - **Evaluation**: The convertible bond market factors showed a slight increase in valuation, with trading activity continuing to recover, indicating improving market sentiment[38] --- Factor Backtesting Results 1. Market Style Factors - **Style Balance**: Balanced between large-cap and small-cap, as well as value and growth[11][13] - **Style Volatility**: Continued decline in volatility, indicating stability[11][13] 2. Market Structure Factors - **Return Dispersion**: Declined, indicating less variability in sector performance[11][13] - **Sector Rotation**: Slowed down, suggesting reduced changes in sector leadership[11][13] - **Trading Concentration**: Decreased, reflecting a more evenly distributed market[11][13] 3. Market Activity Factors - **Volatility**: Declined, indicating reduced market risk[12][13] - **Turnover Rate**: Decreased, reflecting lower trading activity[12][13] 4. Commodity Market Factors - **Trend Strength**: Strong in energy and metals, weak in agriculture[27][30] - **Basis Momentum**: Highest in metals, declined in other sectors[27][30] - **Volatility**: High across all sectors[27][30] - **Liquidity**: Stable overall[27][30] 5. Options Market Factors - **Implied Volatility**: Increased for both SSE 50 and CSI 1000, indicating higher uncertainty[35] - **Skewness**: Positive for CSI 1000 (small-cap optimism), negative for SSE 50 (large-cap caution)[35] 6. Convertible Bond Market Factors - **Valuation**: Slight increase in average conversion premium[38] - **Trading Activity**: Continued recovery in trading volume[38]

Agriculture - Soybeans: High temperatures and low rainfall in the U.S. during July-August affect the quality and yield, while La Niña may cause drought in Brazil and Argentina, impacting logistics and shipments to China [3] - Corn: Abnormal rainfall in South America due to El Niño and La Niña disrupts crop growth, while extreme heat in Ukraine from late June to early September negatively impacts corn yields [4] - Apples: Unpredictable weather in spring can lead to severe frost damage, as seen in 2018 when temperatures dropped to -6°C, causing over 30% yield loss [5] - Canola: La Niña causes high temperatures in Canada from May to September, leading to significant yield reductions, while Europe faces spring frost issues in 2024 [6] - Palm Oil: El Niño results in low temperatures and rainfall in Malaysia and Indonesia, causing delayed production impacts seen in previous years [7] - Live Pigs: Winter increases the likelihood of disease outbreaks, but extreme weather impacts are generally localized and short-term [10] - Eggs: High summer temperatures lead to a slight decrease in egg production rates, but do not alter the overall supply-demand balance [11] Soft Commodities - Cotton: Low temperatures and excessive rainfall in Xinjiang affect seedling emergence, while drought in the U.S. during June-August raises abandonment rates and reduces production [12] - Sugar: Drought in Brazil and India during September-October affects sugarcane quality and yield, while heavy rainfall in Thailand and Guangxi also impacts production [13] Energy and Chemicals - Crude Oil: North American cold waves in January-February affect shale oil production, while hurricanes from June to November impact refinery operations [15] - Urea: Extreme heat affects production, while rainfall patterns influence application timing [16] - Methanol: Cold weather in Iran reduces chemical demand, leading to decreased imports [17] - PTA: Typhoons in summer disrupt logistics in China, causing temporary supply shortages [18] - Ethylene Glycol: Cold waves in North America lead to reduced imports [19] - LPG: Severe drought in Panama Canal region raises shipping costs, significantly increasing domestic LPG prices [21] Non-Ferrous & New Energy - Copper: Extreme weather poses risks to copper mining operations, with 19% of mines facing such threats [23] - Zinc: Production at McArthur River mine was halted due to hurricane-related rainfall, resulting in a significant decrease in output [24] - Aluminum: Seasonal rainfall fluctuations in Yunnan affect production costs and capacity [25] - Nickel: Rainy seasons in the Philippines impact shipment volumes, leading to price spikes [27][28] Black Metals - Iron Ore: Weather events in Australia and Brazil, such as cyclones and heavy rainfall, restrict shipments, significantly affecting supply [33]