Metalworking: the winning rate of volume and price timing increased slightly, and the effectiveness of volatility factor improved
According to the short-term price volume industry configuration model of Dongxing metalworking, the industries worthy of attention in the coming week are coal, electric power and public utilities, construction, building materials, light industry manufacturing, agriculture, forestry, animal husbandry and fishery. ETF funds that can focus on relevant industries or themes.
As of last week, the annualized yield of the industry rotation strategy was 16.92% and the sharp ratio was 0.73, significantly higher than the benchmark portfolio. The annualized excess return rate of the industry rotation strategy is 9.17% and the information ratio is 0.97. The excess return rate last week was 0.08%, and the cumulative excess return rate since this year has reached 14.06%. The industry rotation strategy based on price and volume has performed well. The average income of the six industries recommended in the previous period was – 0.43%, slightly higher than the average income of 29 industries except comprehensive finance. Among them, the building materials and transportation industries ranked top this week, rising by 2.02% and 0.62% respectively, ranking third and eighth among the 30 industries.
As of last Friday, the average winning rate of the industry timing index had increased slightly compared with the previous period, reaching 50.63%. Specifically, timing indicators have a relatively high timing success rate in iron and steel, light industry manufacturing, construction, agriculture, forestry, animal husbandry and fishery, coal and other industries.
In terms of quantitative stock selection factors, it can be concluded from the IC results that among all a shares, the factors that performed better last week are volatility, value and technology factors; Among the 300 constituent stocks in Shanghai and Shenzhen, the factors that performed better last week were quality, value and market value; Among the CSI 500 constituent stocks, the factors that performed better last week were market value, quality and volatility. The overall performance of quantitative stock selection factor in CSI 500 is better than that in CSI 300. In addition, the quality factor performs well, and the performance in all a shares, CSI 300 constituent shares and CSI 500 constituent shares is generally better than other factors.
From the trend of long short net value of stock selection factors, the performance of value factors continued to shine, the quality and volatility factors rebounded strongly, and achieved significant positive returns in the three stock pools. The reversal factor failed to continue the previous performance, the growth factor also performed poorly, and the technical factor performed well in the all a stock pool. The overall sentiment of the market this week was general. The recent strong performance of small and medium-sized market capitalization stocks failed to continue, and the effectiveness of market capitalization factors decreased. In the recent market environment, the undervalued blue chip stocks with stable early trend were more favored by investors, and the value and volatility factors performed better. Considering the long-term and short-term conditions, we believe that the expectations are consistent Volatility and technical factors deserve investors’ attention.
In terms of convertible bond factors, last week’s convertible bond valuation, positive stock financial quality and positive stock value factors achieved significant long and short returns, while other factors performed generally. Recently, convertible bonds and low price convertible bonds corresponding to undervalued positive stocks have attracted market attention, and the effectiveness of positive stock value and convertible bond valuation factors has been improved. We maintain our previous view that investors should focus on the consistent expectation of positive stocks of convertible bonds and positive stock growth factors.
Risk warning: the above results are completed through historical data statistics, modeling and calculation. There is a risk that the model will fail when the policy and market environment change.
