- The report tracks the performance of Guosen Financial Engineering's index enhancement portfolios, which are constructed based on benchmarks such as CSI 300, CSI 500, CSI 1000, and CSI A500 indices, aiming to consistently outperform their respective benchmarks [11][12][14] - The construction process of the index enhancement portfolios includes three main components: return prediction, risk control, and portfolio optimization [12] - The report monitors the performance of common stock selection factors across different stock selection spaces, including CSI 300, CSI 500, CSI 1000, CSI A500, and public fund heavy-holding indices, by constructing single-factor Maximized Factor Exposure (MFE) portfolios and tracking their relative excess returns [11][15][42] - The MFE portfolio construction process involves optimizing the portfolio to maximize single-factor exposure while controlling for various constraints such as industry exposure, style exposure, stock weight deviation, turnover rate, and component stock weight proportion [42][43][44] - The optimization model for MFE portfolios is expressed as follows: $\begin{array}{ll}max&f^{T}\ w\\ s.t.&s_{l}\leq X(w-w_{b})\leq s_{h}\\ &h_{l}\leq H(w-w_{b})\leq h_{h}\\ &w_{l}\leq w-w_{b}\leq w_{h}\\ &b_{l}\leq B_{b}w\leq b_{h}\\ &\mathbf{0}\leq w\leq l\\ &\mathbf{1}^{T}\ w=1\end{array}$ where `f` represents factor values, `w` is the stock weight vector, and constraints include style factor deviation, industry deviation, stock weight deviation, component stock weight proportion, and stock weight limits [42][43] - The report provides detailed performance tracking of single-factor MFE portfolios across different stock selection spaces, highlighting factors such as SP, SPTTM, EP, and others that performed well in specific indices like CSI 300, CSI 500, CSI 1000, CSI A500, and public fund heavy-holding indices [15][18][20][22][24][26] - The report also tracks the excess returns of public fund index enhancement products, including CSI 300, CSI 500, CSI 1000, and CSI A500, with detailed statistics on maximum, minimum, and median excess returns over different time periods [28][32][35][38][41]

- The report discusses a rotation model for micro-cap stocks, which uses the relative net value of micro-cap stocks to the "Mao Index" as a key indicator. If the relative net value is above its 243-day moving average, it suggests investing in micro-cap stocks; otherwise, it suggests investing in the Mao Index. Additionally, the 20-day closing price slope of both indices is used to determine the direction of rotation, favoring the index with a positive slope when the directions differ [19][24][26] - A timing indicator is constructed based on the 10-year government bond yield (threshold: 0.3) and the volatility congestion rate of micro-cap stocks (threshold: 0.55). If either indicator reaches its threshold, a closing signal is triggered to manage risk [19][24][20] - The report evaluates eight major stock selection factors across different stock pools (All A-shares, CSI 300, CSI 500, and CSI 1000). Among these, the value factor (20.46%), volatility factor (16.11%), and technical factor (13.68%) show strong IC mean performance, while the growth factor (-5.65%) and consensus expectation factor (-2.16%) perform relatively weakly [46][47][48] - The report highlights that defensive value factors and volume-price factors (volatility and technical) performed strongly in the past week, reflecting a shift in market style towards low-valuation defensive strategies amid a volatile environment. Growth and consensus expectation factors, which previously performed well, experienced a pullback [46][47][48] - For convertible bonds, the report constructs quantitative bond-picking factors, including equity-related factors and valuation factors such as parity and floor premium rates. Among these, equity consensus expectation, equity value, and convertible bond valuation factors achieved higher IC mean values in the past week [54][55][56]

- The report focuses on the performance of stock selection factors in 2025, highlighting the effectiveness of factors such as transaction count, liquidity, crowding, price stability, and reversal in stock selection across the market [1][5][15] - Factors are categorized into two main groups: volume-price factors and growth factors. Volume-price factors are further divided into two representative categories: price stability and reversal, while liquidity, crowding, and transaction count serve as average representatives of volume-price factors [6][24] - The construction of major factors involves market capitalization and industry neutrality, outlier removal, and standardization, followed by equal-weight synthesis into major factors [13] - Sub-factors are detailed with their calculation methods, such as residual volatility derived from the Fama-French three-factor model regression residual volatility, turnover rate variation coefficient calculated as turnover rate divided by the standard deviation over the mean, and entropy of transaction volume proportion using the entropy formula [13] - The report provides statistical data on the performance of major factors, including IC, ICIR, excess returns, maximum drawdowns, IR, long-short returns, long-short maximum drawdowns, and long-short Sharpe ratios. For example, liquidity factor achieved an IC of 9.72%, ICIR of 1.08, excess return of 23.67%, and IR of 3.43 [15][16] - Sub-factors with notable performance include short-term reversal (IC 6.27%, ICIR 1.21, excess return 4.86%), residual volatility (IC 9.42%, ICIR 1.22, excess return 1.53%), and turnover rate (IC 10.75%, ICIR 1.29, excess return 17.46%) [17] - The report highlights the time-series performance of factors, noting that the main profit periods for all factors were concentrated between January and November 2025, with significant drawdowns occurring between September and December 2025. Growth, SUE, and price stability factors had lower profit levels and higher drawdowns, while liquidity factors had higher profit levels and higher drawdowns [19][20][23] - The correlation analysis of excess returns among factors shows that price stability has a high correlation with other factors, while reversal has a low correlation with other factors. Liquidity, crowding, and transaction count factors exhibit low mutual correlation [21][24]

成长因子收益边际回升 金融工程周报 基金市场回顾： 权益市场风格 2025年12月15日 周度报告 操作评级 中信五风格-成长★☆☆ 金融工程组 张婧婕 Z0022617 010-58747784 gtaxinstitute@essence.com.cn 本报告版权属于国投期货有限公司 1 不可作为投资依据，转载请注明出处 截至2025/12/12当周，通联全A（沪深京）、中证综合债与南华 商品指数周度涨跌幅分别为0.26%、0.11%、-1.21% 。 公募基金市场方面，近一周纯债策略收益小幅回升；权益策略中 普通股票策略收益表现相对偏强，贵金属ETF收益继续走高，白 银期货ETF上涨9.27%，能源化工与豆粕ETF有所回撤。 中信五风格方面，上周成长风格收涨，其余风格收跌；风格轮动 图显示成长与金融风格相对强弱边际提升，稳定风格相对强弱动 量显著走低。公募基金池方面，近一周金融风格基金平均超额表 现相对偏弱，从基金风格系数走势来看市场对周期风格偏移度有 所下降；本周拥挤度指标相比上周小幅回升，当前周期风格基金 拥挤度上升至近一年以来偏高分位区间，而金融与消费风格拥挤 度位于近一年偏低分位区间。 中性策略方 ...

Core Viewpoint - The article discusses the shift in investment styles driven by fundamental factors, indicating a transition from growth to value investing as economic indicators improve and market trends are confirmed [3][5][67]. Group 1: Factor Performance - Growth factors have shown strong performance this year, with cumulative returns of 37.93% in the CSI 300 index, while momentum and dividend factors have underperformed [8][11]. - Low volatility factors have performed poorly in the CSI 300, reflecting the high volatility characteristics of the market this year [10][12]. - The performance of long-term momentum factors has been weak, indicating rapid rotation among industries and sectors [10][14]. Group 2: Macro Quantitative Framework - The macroeconomic cycle has been switching more frequently in the past three years compared to before 2020, with economic indicators suggesting a downturn in the first half of 2025 followed by a recovery towards the end of the year [32][38]. - The liquidity indicators have shown a weak overall trend, with market trading rates rising, indicating a correction in liquidity expected in the second half of 2025 [40][46]. - Credit indicators have shown a preference for expansion in the first half of 2025, aligning with social financing, but are expected to shift towards contraction in the second half [53][48]. Group 3: 2026 Equity Quantitative Outlook - The investment strategy for 2026 is expected to be driven by fundamental factors, with a focus on value before growth as economic conditions improve [5][54]. - The market is currently in a consolidation phase, with a trend confirmation expected to benefit value and long-term momentum factors, while growth factors are anticipated to perform better in a volatile environment [75][80]. - Industry rotation speed has slowed down, indicating potential for the formation of main lines in the market, with a focus on industries with low crowding and emerging trends [82][85].

========= Content: --------- <doc id='2'>任瞳 S1090519080004 rentong@cmschina.com.cn 刘凯 S1090524120001 liukai11@ cmschina.com.cn 杨航 S1090523010004 yanghang4@cmschina.com.cn 证券研究报告 | 金融工程 2025 年 11 月 15 日 专题报告 ❑ 成长因子表现：以招商证券量化团队因子库中的成长因子为例，对其有效 性进行测试。综合来看，标准化预期外盈利因子（SUE）表现较为优异。 除此以外，单季度 ROE 同比因子表现同样较优。相关性方面，净利润同 比加速度因子、标准化预期外收入因子与其他因子的相关性相对较低。 ❑ 假设已知下一期上市公司的净利润增速，从而构建净利润增长的投资组 合，先验测算该组合的业绩表现。已知未来成长确定性的未来成长组合能 够稳定的战胜历史增长组合，2010 年以来每年均能战胜历史成长组合。 ❑ 通过上市公司业绩增长的转移矩阵可以发现，当前的业绩高增速仅能部分 反映公司当前的成长性，而未来的成长性仍有较大的不确定性。按照双变 量分组的方法，我们发现部分指标能够提升对下一期业绩增速的预期，包 括单季度 ROE、单季度 ROE 斜率、单季度净利润同比增速斜率、SUE、 单季度营业收入同比增速、单季度经营性现金流净额。 ❑ 综合筛选出的基本面指标构建成长预期组合，区间年化收益接近 26%，夏 普比率 0.95，卡玛比率 0.59。相对比中证 500 指数，超额年化收益接近 19%，从 2012 年以来每年均能战胜中证 500 指数。自 2012 年以来该组合 平均持仓 175 只，平均单边换手约为 32%。 ❑ 进一步地，探究什么样的量价指标可以进一步提升成长预期组合表现。1） 盈余公告次日开盘超额较高的股票组合，其业绩表现是受到市场认可的， 未来业绩表现更好；2）换手率均线标准差较小的组合表现较为优异；3） Amihud 非流动性大的组合业绩表现则较为亮眼。 ❑ 运用上述指标构建技术面精选成长预期组合，回测区间年化收益超过 40%，夏普比率（1.45）与卡玛比率（1.07）均超过 1。相比中证 500 指 数，组合超额年化收益高达 33%。从 2012 年以来每年均能战胜中证 500 指数，且每年超额均在 10%以上。组合平均单边换手约为 67%，各期平均 市值为 113 亿元。</doc> <doc id='22'>资料来源：招商证券、Wind 我们以招商证券量化团队因子库中的成长因子为例，对其有效性进行测试。 表 1 中我们列出了因子回测的框架。回测区间为 2010 年 1 月 1 日至 2025 年 6 月 30 日，每个月最后一个交易日进行调仓，股票权重为等权方式，股票样本池 为全市场，剔除上市不足 180 天、停牌、涨跌停、ST 股票。如无特殊说明，本 文的因子测试均采用此因子回测框架。</doc> <doc id='23'>表 1：因子回测框架 | 项目 | 内容 | | --- | --- | | 回测区间 | 2010.1.1-2025.6.30 | | 调仓频率 | 月度 | | 调仓日 | 最后一个交易日 | | 样本空间 | 全市场 | | 股票筛选 | 剔除上市不足 天、停牌、涨停和 股票 180 ST | | 市值行业中性化 是 | | | IC 测试 IC | 指标为因子值与下一期股票收益率的秩相关系数 | | | 在每个月最后一个交易日后，根据因子值大小将样本空间内的股 | | 分组测试 | 票分成 10 组，每组组内进行等权配置计算各组历史表现。多头 | | | 组为因子值最大的组，空头组为因子值最小的组 | | 基准 | 样本空间内股票的等权组合 | | 交易费率 | 暂不考虑交易费率 | | 资料来源：Wind 资讯、招商证券 | | 如图 4 所示，招商证券量化团队因子库中涵盖单季度净利润同比增速、标准 化预期化盈利、单季度 ROE 同比、净利润增速加速度等指标。除此以外，还有 许多成长因子，正如我们上文所介绍的，但是由于该部分并不是本文研究的重点， 这里我们暂且不做一一展示，感兴趣的投资者欢迎与我们做进一步的交流。</doc> <doc id='24'>图 4：招商证券量化团队因子库成长因子概述 | 因子名称 | 构造方式 | 参考方向 | | --- | --- | --- | | 单李废净利润同比增速 | 单李度归母净利润同比增长率 | 正向 | | 单李度营业收入同比增速 | 单季度营业收入同比增长率 | 正向 | | 单季度营业利润同比增速 | 单率度营业利润同比增长率 | 正向 | | 标准化预期外盈利 | (当前李度归母净利润 -(去年同期单度归母净利润+过去 8个 李度单率归母净利润同比增长均值) / / 过去 8个季度的单 | 正向 | | | 李度归母净利润同比增长值的标准差 | | | 标准化预期外收入 | (当前李度营业收入 - (去年同期单度营业收入+过去 8个 李度单率度营业收入同比增长均值)/过去8个季度的单 | 正向 | | | 李营业收入同比增长值的标准差 | | | 单季度ROE同比 | ROE单季度同比变化 | 正向 | | 单季度ROA同比 | ROA单季度同比变化 | 正向 | | 净利润同比加速度 | 单率度营业利润同比增速的一阶差分 | 正向 | | 净利润TTM环比增速 | 净利润TTM环比增长率 | 正向 | 资料来源：招商证券 表 2 我们具体展示了净利润 TTM 环比增速因子的回测表现。净利润 TTM 环比增速因子在回测区间内的 IC 均值为 2.91%，ICIR 为 0.57，t 值为 7.8。从 分组测试来看，该因子在全 A 市场中分 10 组年化收益单调性一般，但多头组收 益最高，年化收益 15.14%，年化超额 6.28%。</doc> <doc id='25'>表 2：净利润 TTM 环比增速因子回测数据展示 | Rank_IC | Rank_IC 均值 | 胜率（%） | IC_IR | t 统计量 | 最大值 | 最小值 | | --- | --- | --- | --- | --- | --- | --- | | 数据 | 2.91% | 71.51 | 0.57 | 7.80 | 16.79% | -12.50% | | 多空组合 | 年化收益 | 多空卡玛 | 多头年化收益 | 多头年化超额 | 多头夏普 | 多头双边换手 | | | 10.28% | 0.60 | 15.14% | 6.28% | 0.54 | 5.46 | 资料来源：Wind，招商证券；2010/1/1-2025/6/30</doc> <doc id='30'>资料来源：Wind，招商证券；2010/1/1-2025/6/30 资料来源：Wind，招商证券；2010/1/1-2025/6/30 受篇幅限制，其他成长因子的因子测试结果我们就不一一列示，图 7 中我们 统一列出了其他成长因子的表现。综合来看，标准化预期外盈利因子（SUE） 表现较为优异。SUE 因子在回测区间内的 IC 均值为 3.06%，t 值为 6.65，较为 显著；多头组超额年化

Investment Strategy Overview - The report emphasizes a fundamental-driven style factor switch, awaiting confirmation of trend movements for 2026 [1][4][8] Factor Performance - Growth factors have shown strong performance, while low volatility and momentum factors have retreated, indicating a rapid rotation among market sectors and themes this year [4][10][12] - Year-to-date performance of various factors in different indices shows growth at 37.93% in CSI 300, while low volatility and liquidity factors have negative returns [10][12] Macro Quantitative Framework - The macroeconomic cycle has shifted more frequently in the past three years, with leading indicators suggesting a downturn in the first half of 2025, followed by a recovery signal towards the end of the year [4][38][43] - The liquidity indicators have shown a weak overall trend, with market trading rates rising, indicating a correction in liquidity for the second half of 2025 [50][54][60] - Credit indicators have shown a preference for expansion in the first half of 2025, transitioning to contraction by November [65][66] 2026 Equity Quantitative Outlook - The report anticipates a fundamental-driven style switch, with a focus on economic fundamentals becoming the key driver, transitioning from liquidity concerns to economic and inflation factors [4][86][91] - Market trends indicate a shift to a consolidation phase since August, with an increasing probability of trend confirmation from late October [92][97] - Emotional indicators have shown a supportive trend since July, with overall sentiment remaining warm and moderate [102][105] Industry Rotation and Focus - The speed of industry rotation has slowed down in 2025, with potential for a main trend to form, particularly in sectors with lower crowding and emerging trends [106][112] - Key sectors to watch include electronics and computing, which have shown lower crowding and are in a trend initiation phase [113][116]

Report Industry Investment Rating No relevant content provided. Core Viewpoints of the Report - In a unilateral rising market, the momentum factor can amplify returns by concentrating on strong-performing stocks, resulting in significant excess returns. When combined with the growth factor, it can capture trends while adding a fundamental safety net to the investment portfolio, making it suitable for medium-risk preference investors. The "growth + momentum" dual-factor investment logic is systematically implemented in the ChiNext Momentum Growth Index and its linked product, the Huaxia ChiNext Growth ETF [1][11]. Summary According to the Directory Product Fund - Huaxia ChiNext Growth ETF (159967) - **Investment Attributes and Returns**: The Huaxia ChiNext Growth ETF closely tracks the ChiNext Momentum Growth Index, serving as a passive investment tool for high-growth and strong-momentum portfolios on the ChiNext board. Since its establishment in June 2019, it has achieved a cumulative return of 113.97%, significantly outperforming broad-based indices such as the CSI 300. In the rising market since May 2025, it has shown outstanding performance with a six-month return of 46.51%, demonstrating its offensive nature in a bull market. However, it has high volatility, with a three-year return of 1.10% significantly trailing the CSI 300's 22.70% [2][11][14]. - **Fund Manager and Fund Company**: The fund is managed by Rong Ying, who manages 21 funds with a total scale of approximately 138.292 billion yuan. As of October 22, 2025, the Huaxia ChiNext Growth ETF has a scale of 30.39 billion yuan. Huaxia Fund, the fund manager, has a total public fund management scale of 2041.571 billion yuan as of October 22, 2025, with 114 ETFs worth 896.351 billion yuan and 13 money market funds worth 774.607 billion yuan, consolidating its leading position in public offering index investment [15][19]. Tracking Index - ChiNext Momentum Growth Index (399296.SZ) - **Index Composition and Calculation**: The index is compiled by Guozheng Index Company, selecting 50 listed company securities with good growth ability and obvious momentum effects from the ChiNext board. It uses a Paasche weighting method with a single stock weight cap of 15% and adjusts samples and weights quarterly. The sample selection involves screening stocks based on liquidity and then using growth and momentum factors to calculate scores and determine the final 50 stocks [20][21][27]. - **Performance and Returns**: Since its release in 2019, the index has achieved a cumulative return of 157.46%, significantly higher than mainstream broad-based indices. In 2020, it had a return of 97.14%, showing high growth elasticity. In the period from May 1 to October 22, 2025, it had a cumulative return of 40.24%, also outperforming major broad-based indices [4][31][35]. - **Weighted Stocks and Industry Distribution**: The top ten component stocks account for 76.63% of the total weight, with high concentration in the technology growth sector. The top four industries (communications, power equipment, electronics, and non-bank finance) account for nearly 80% of the total weight, highlighting the index's focus on the technology growth sector [3][37][52]. - **Valuation and Earnings**: As of October 22, 2025, the index's PE TTM is 40.83 times, slightly lower than the historical median of 44.73 times, indicating a reasonable valuation. From 2019 to 2024, the index's component stocks showed strong growth in revenue and net profit, and it is expected to maintain double-digit growth from 2025 to 2026 [61][64]. - **Sources of High Growth and Excess Returns**: The index's high growth elasticity and excess returns stem from its precise sample screening, factor tilt weighting, high-growth and high-elasticity asset characteristics, and regular dynamic adjustments [71]. Sample Space - ChiNext Composite Index - **Market Value and Industry Structure**: The index shows a pattern where small-cap stocks dominate in number and large-cap stocks dominate in weight. The industry structure has been evolving towards power equipment, electronics, and communications, with the power equipment industry's weight increasing from 13.89% in 2020 to 23.46% in 2025, and the communications industry's weight rising from 2.90% to 9.69% [76][78]. - **Growth and Profitability**: The index has shown strong growth momentum in revenue, with its growth rate consistently higher than that of major market indices from 2020 to 2024. Its average net profit growth rate from 2020 to 2024 was 11.73%, significantly higher than that of mainstream broad-based indices. The average ROE in the past five years was 6.86%, indicating relatively good profitability [79][81][83]. - **Industry Focus and New Productivity Layout**: The index's industry structure focuses on technology growth, with a low financial sector weight and high weights in emerging technology fields such as communications and computers, reflecting the trend of new productivity development and industrial upgrading [88].

Report Industry Investment Rating - The operation rating for CITIC's five - style stability is ★☆☆, indicating a bullish bias but with limited operability in the market [4] Core Viewpoints - In the week ending November 7, 2025, the weekly returns of Tonglian All - A (Shanghai, Shenzhen, Beijing), ChinaBond Composite Bond, and Nanhua Commodity Index were 0.63%, - 0.01%, and - 0.47% respectively. In the public fund market, convertible bond products performed well, the common stock strategy index declined slightly, neutral strategy products mostly rose, non - ferrous metal ETFs weakened slightly, and soybean meal ETFs had better returns. Among CITIC's five styles, only the consumer style declined last Friday, while the stable and cyclical styles were strong. The style rotation chart showed that the relative strength of the growth style decreased, and the relative strength momentum of the financial style rebounded marginally. The average returns of various style funds in the public fund pool underperformed the benchmark index. The market's deviation towards the financial style decreased. The congestion index dropped, with the growth style congestion falling to the medium - percentile range of the past year. In the neutral strategy, the contract basis weakened slightly last week, with the current IH basis close to 1 standard deviation below the three - month average. The average premium rates of IC and IM corresponding index ETFs rebounded to the medium - percentile range of the past three months. The profit factor had a good return performance in the past week, with a weekly excess return of 0.97%, and the excess of the growth factor was significantly compressed. The win - rate of the residual momentum factor decreased, but the factor itself strengthened. The cross - section rotation speed of factors rebounded slightly this week, currently at the medium - percentile range of the past year. According to the latest scoring results of the style timing model, the financial style declined marginally this week, the consumer style strengthened slightly, and the current signal favored the stable style. The return of the style timing strategy last week was 1.85%, with an excess return of 0.97% compared to the benchmark balanced allocation [4] Summary by Relevant Catalogs Fund Market Review - The weekly returns of Tonglian All - A (Shanghai, Shenzhen, Beijing), ChinaBond Composite Bond, and Nanhua Commodity Index were 0.63%, - 0.01%, and - 0.47% respectively [4] - In the public fund market, convertible bond products performed well, the common stock strategy index declined slightly, neutral strategy products mostly rose, non - ferrous metal ETFs weakened slightly, and soybean meal ETFs had better returns [4] Equity Market Style - Among CITIC's five styles, only the consumer style declined last Friday, while the stable and cyclical styles were strong. The style rotation chart showed that the relative strength of the growth style decreased, and the relative strength momentum of the financial style rebounded marginally [4] - The average returns of various style funds in the public fund pool underperformed the benchmark index. The market's deviation towards the financial style decreased. The congestion index dropped, with the growth style congestion falling to the medium - percentile range of the past year [4] Neutral Strategy - The contract basis weakened slightly last week, with the current IH basis close to 1 standard deviation below the three - month average. The average premium rates of IC and IM corresponding index ETFs rebounded to the medium - percentile range of the past three months [4] Barra Factor - The profit factor had a good return performance in the past week, with a weekly excess return of 0.97%, and the excess of the growth factor was significantly compressed. The win - rate of the residual momentum factor decreased, but the factor itself strengthened. The cross - section rotation speed of factors rebounded slightly this week, currently at the medium - percentile range of the past year [4] Style Timing Model - According to the latest scoring results of the style timing model, the financial style declined marginally this week, the consumer style strengthened slightly, and the current signal favored the stable style. The return of the style timing strategy last week was 1.85%, with an excess return of 0.97% compared to the benchmark balanced allocation [4]

Core Insights - The article discusses the integration of macro quantification and factor momentum to identify resonant factors for investment strategies, emphasizing the importance of economic, liquidity, and credit indicators in shaping market expectations [1][3]. Group 1: Factor Scores and Market Indicators - The macroeconomic indicators show signs of recovery, with economic growth expected to improve, while liquidity is slightly weak and credit conditions are tightening [3][4]. - Value factors have seen a significant increase in scores, becoming resonant factors in the CSI 300 index, while growth factors have declined [4][6]. - The article presents a table of factor scores across different indices, indicating a preference for value and low volatility factors in the current market environment [4]. Group 2: Economic Outlook and Leading Indicators - The economic leading indicators model suggests that the economy is in a rising cycle since September 2025, with a slight upward trend expected in the coming months [6][9]. - Specific indicators such as PMI and fixed asset investment are analyzed, showing a mixed outlook with some indicators in a rising phase while others are nearing a peak [11][12]. - The article highlights the importance of monitoring leading indicators to anticipate future economic cycles and potential downturns [9][10]. Group 3: Liquidity and Credit Conditions - The liquidity environment is assessed as slightly loose despite some tightening in interest rates, with a focus on the net monetary supply and excess reserve rates [12][16]. - Credit indicators show a mixed picture, with overall credit volume and structure remaining low, but some signs of recovery are noted [17][18]. - The article suggests a cautious approach to credit-sensitive investments due to the ongoing tightening in credit conditions [17]. Group 4: Asset Allocation and Market Focus - The asset allocation strategy is adjusted to reflect a neutral to positive stance on A-shares, while reducing exposure to gold and bonds due to changing market dynamics [18]. - The focus on PPI and liquidity as key market drivers indicates a shift in investor sentiment towards these macroeconomic variables [19]. - The article emphasizes the importance of selecting industries that are sensitive to economic changes but less affected by credit conditions, with a preference for sectors like utilities and coal [21].