2025-08-05 03:16Investment Rating - The report maintains a neutral stance on the stock market, cautious on bonds, and optimistic on commodities [2][4]. Core Insights - The report highlights that the PPI was below expectations while social financing and CPI exceeded expectations, leading to a neutral outlook for the stock market. GDP growth was above expectations, putting pressure on the bond market, while the commodity market outlook remains optimistic [1][2]. - The industry rotation model for August recommends sectors such as comprehensive, comprehensive finance, media, agriculture, forestry, animal husbandry, fishery, telecommunications, and light industry manufacturing, indicating a shift from real estate and consumer services [4][12]. - The small-cap growth style is expected to continue its dominance, supported by macroeconomic indicators and investor sentiment [5][6]. Summary by Sections Economic Indicators - As of the end of July, PPI was below expectations, while social financing and CPI were above expectations, leading to a neutral view on the stock market. GDP growth was consistently above expectations, negatively impacting the bond market [2][4]. Industry Recommendations - The August industry rotation model recommends comprehensive, comprehensive finance, media, agriculture, forestry, animal husbandry, fishery, telecommunications, and light industry manufacturing, while excluding real estate and consumer services [4][12]. Investment Strategies - The best-performing strategy in July was the new stock strategy, achieving a monthly return of 11.3%, significantly outperforming major small-cap indices [8]. - The growth trend resonance stock selection strategy yielded a return of 7.9%, while the XG Boost growth selection strategy achieved a return of 5.8% [9]. - For August, the report suggests focusing on small-cap combinations and dividend/valued selections, while not recommending growth strategies due to ongoing valuation declines [11][12]. Quantitative Models - The report discusses advancements in quantitative models, particularly deep learning models that have outperformed benchmarks significantly [13][14].