Investment Rating - The report maintains a "Buy" rating for the semiconductor testing equipment industry, indicating a favorable outlook for investment opportunities in this sector [1]. Core Insights - The semiconductor testing equipment industry is experiencing a critical phase characterized by "value reassessment, demand surge, and accelerated domestic substitution," which presents significant investment opportunities [5][6]. - The testing equipment is essential throughout the semiconductor manufacturing process, with ATE (Automatic Test Equipment) leading in value contribution, while probe stations and handlers work in synergy to enhance testing efficiency [11][20]. - The demand for testing equipment is driven by three main factors: AI computing power, advanced packaging, and automotive electronics, which collectively create a favorable environment for growth [5][6]. Summary by Sections 1. Testing Equipment's Role in Manufacturing - Semiconductor testing equipment is a core component of the integrated circuit industry, covering wafer testing, packaging testing, and functional verification [11]. - Testing occurs in two main phases: Circuit Probing (CP) and Final Test (FT), which are crucial for ensuring product quality and cost efficiency [11][15]. 2. Demand Drivers - The complexity of AI computing chips is increasing, leading to longer testing cycles and higher equipment demand [6]. - Advanced packaging techniques are creating new testing requirements, such as KGD (Known Good Die) and SLT (System Level Test), which further drive the need for testing equipment [6]. - The automotive sector is also contributing to demand growth, with a significant increase in the number of chips required for smart vehicles, necessitating rigorous testing standards [5][6]. 3. Global Market Dynamics - The testing equipment market is dominated by a few key players, particularly in the ATE segment, where companies like Advantest and Teradyne hold over 90% market share [5][6]. - The report highlights the importance of platform integration and vertical consolidation as strategies for leading companies to maintain competitive advantages [5][6]. 4. Domestic Substitution Opportunities - The report identifies a clear path for domestic manufacturers to increase their market share, particularly in the SoC and storage testing segments, where current domestic production rates are low [5][6]. - Companies such as Changchuan Technology, Huafeng Measurement Control, and Xidian Co. are highlighted as key players with potential for growth in the domestic market [5][6].

Group 1: Report Industry Investment Rating No information provided in the content. Group 2: Report's Core View - The bond market experienced a "poor start" at the beginning of 2026 due to multiple factors such as the strong performance of the equity and commodity markets, large - scale government bond issuance at the beginning of the year, and increased redemption pressure on funds. Although some policies are beneficial to the bond market, the market still has concerns about the bond market's performance in January and 2026 [1][2][11]. - The commodity market shows a "re - inflation" trading logic at the beginning of the year, but the sustainability of the commodity price increase remains to be observed. If the actual situation does not meet expectations, it may bring trading opportunities for the bond market [3][39]. - For the bond market strategy, the 10y Treasury bond is close to the high point of the shock range, and the leverage strategy is still effective. The allocation of Tier 2 and perpetual bonds of banks is better than trading [3][4]. Group 3: Summary According to the Directory 1. The bond market experienced a "poor start" - **Reason 1: The strong performance of the equity and commodity markets suppresses the bond market** - The PMI in December rebounded counter - seasonally, and policies were introduced, boosting the opening - year macro - expectations. The Shanghai Composite Index stood above 4000 points, and the Wind All - A Index rose 5.1%. - The expectation of continued fiscal efforts and investment recovery in 2026 led to the warming of re - inflation trading. The Nanhua Industrial Products Index increased by 2.5% month - on - month, with metal varieties being relatively strong [1][12][14]. - **Reason 2: The large - scale issuance of government bonds at the beginning of the year raises concerns about supply** - The issuance scale of key - term government bonds at the beginning of the year was significantly larger than that of the same period last year, causing supply concerns. The current government bond issuance is in line with the neutral issuance speed under a 4% deficit ratio, and there may be room for acceleration in the future. - The bidding for local bonds in the first week of January was not good, and the spread between local bonds and government bonds has exceeded 20bp. Future policies to control bond - issuing costs need attention [19][21][24]. - **Reason 3: Increased redemption pressure and continuous net selling by funds** - At the beginning of the year, the funds for fund volume - boosting flowed back, and the scale of credit bond ETFs decreased rapidly after the New Year. - Since the beginning of the year, affected by factors such as the stock - bond seesaw effect, inflation expectations, and supply concerns, funds have continuously sold bonds net, mainly old - term policy financial bonds within 10 years and inter - bank certificates of deposit [26]. 2. Is the commodity market trading re - inflation? - The commodity market shows a "re - inflation" logic, with strong performance in non - precious metals and mid - upstream sectors such as non - ferrous and black metals. The driving forces include policy - induced macro - expectation improvement, the capital effect of precious metals, and the resonance of risk preferences during the equity spring rally. - Specific factors include the repair of undervalued sectors by speculative funds, the tightening of coal supply, the early - stage production of industrial products after the holiday, and the bottoming - out and recovery of inflation expectations. However, the current trading is mainly at the expectation level, and the sustainability of the commodity price increase remains to be observed [30][33][34]. 3. Bond market strategy: The 10y Treasury bond is close to the high point, the leverage strategy is still effective, and the allocation of Tier 2 and perpetual bonds is better than trading - **The 10y Treasury bond is close to the high point of the shock range, and the 1.9% level has allocation value** - It is expected that the 10y Treasury bond is close to the high point of the shock range, and the 1.9% level is worth allocating. It can be gradually built according to the liability situation. - The 10y Treasury bond fluctuates around OMO + 30 - 50bp as the core range, with an additional 5bp of possible extreme fluctuations. - The first quarter may be the high - point period of the bond market shock, so the current 1.9% level has allocation value [38][43]. - **Can the leverage strategy continue?** - At the beginning of the year, the funds are relatively stable and loose, and the bond market leverage level has increased significantly. The carry - trade spread is still at a relatively high level compared with the same period last year, so the leverage strategy is still effective. - In the middle and late ten - days, factors such as the tax period and government bond payment may cause fluctuations in capital prices, but it is unlikely to tighten significantly. The marginal change of certificate of deposit pricing can be observed, and the leverage level can be adjusted flexibly if necessary [44][47][49]. - **How to participate in the current Tier 2 and perpetual bonds of banks?** - **From the allocation perspective**: Currently, Tier 2 and perpetual bonds within 2 years have no obvious advantages compared with medium - term notes of the same rating. For 2 - 3y bonds, some city and rural commercial bank entities can be appropriately selected for bottom - position allocation. Institutions with stable liability ends can participate in the allocation of 4 - 5y bonds. - **From the trading perspective**: If the holding period is less than 1 month, the 10y interest - rate bond is better than the 5y Tier 2 and perpetual bonds. If the holding period is 3 months, the 5y Tier 2 and perpetual bonds can better reflect the coupon and riding value. Considering the current headwinds in the bond market, the trading strategy is recommended to prioritize 10y interest - rate bonds, and the trading of Tier 2 and perpetual bonds should wait for a favorable market [53][58]. 4. Review of the interest - rate bond market: The stock - bond seesaw and supply concerns lead to a steeper yield curve - **Funding situation**: The central bank conducted net reverse - repurchase withdrawals, and the funding situation was stable and balanced [69]. - **Primary issuance**: The net financing of government bonds, local bonds, and inter - bank certificates of deposit increased, while the net financing of policy financial bonds decreased [74]. - **Benchmark changes**: The term spread of government bonds widened, and the term spread of China Development Bank bonds narrowed [81].

Economic Indicators - The Huachuang Macro WEI index rose to 6.05% as of January 4, 2026, an increase of 0.46 percentage points from the previous week[2] - Subway passenger volume in 26 cities increased by 6% year-on-year in the first week of January, while domestic flight operations averaged 12,400 flights per day, down 0.6% year-on-year[2] - Container throughput at Chinese ports rebounded slightly, with a week-on-week increase of 6.3% as of January 5, 2026, and a year-on-year increase of 7.7% over the past four weeks[2] Real Estate and Construction - Residential property sales in 67 cities saw a year-on-year decline of 43% in the first ten days of January, compared to a 24% decline in December 2025[3] - The average land premium rate in 100 cities fell to 0.45% as of January 4, 2026, down from 1.64% in December 2025[3] - Cement shipment rates dropped to 29% as of January 2, 2026, a decrease of 2.4 percentage points from the previous week[3] Commodity Prices - Gold prices rose to $4,473 per ounce, an increase of 3.6%, while copper prices reached $12,990 per ton, up 3.8%[2] - Crude oil prices increased, with WTI at $59.1 per barrel (up 3.1%) and Brent at $63.3 per barrel (up 4.3%)[2] - Lithium carbonate prices surged by 15.6% in the latest trading session[2] Financial Markets - The stock-bond Sharpe ratio difference stood at 4.25, indicating a high relative value for equities compared to bonds[9] - New special bond issuance in early January totaled 874 billion yuan, significantly higher than zero in the same period last year[4] - Interest rates fell post-year-end, with DR001 at 1.2727% and DR007 at 1.4727%, reflecting decreases of 5.98 and 50.94 basis points respectively since December 31, 2025[4]

Economic Data Review - In December, the ADP employment number in the U.S. was below expectations, with a growth of 41,000 jobs compared to an expected 50,000[9] - The October trade deficit narrowed to $29.4 billion, the lowest since mid-2009, with a previous deficit of $48.1 billion revised from $52.8 billion[9] - The ISM Services PMI rose significantly to 54.4 in December, exceeding the expected 52.2, while the ISM Manufacturing PMI fell to 47.9, indicating continued contraction[9] Employment Trends - The initial jobless claims rose to 208,000 in the week of January 3, up from 200,000 the previous week[24] - The continuing jobless claims increased to 1.914 million, compared to 1.858 million the prior week[24] - The number of job vacancies increased, with the INDEED job vacancy index averaging 104.8 in December, up from 103.1 in November[28] Consumer and Retail Activity - The Redbook retail sales year-on-year growth rate fell to 7.1% for the week of January 3, down from 7.6% the previous week[16] - The 30-year mortgage rate in the U.S. rose to 6.16% as of January 8, compared to 6.15% the previous week[19] - The MBA market composite index, reflecting mortgage applications, increased to 270.8, a 0.3% rise from the previous week[19] Financial Conditions - The Bloomberg Financial Conditions Index for the U.S. was 0.863 on January 9, up from 0.795 the previous week, indicating a loosening of financial conditions[35] - The offshore dollar liquidity showed improvement for the yen against the dollar, while the euro against the dollar deteriorated[39] - The 10-year U.S.-Eurozone government bond yield spread widened to 126.8 basis points, compared to 121.5 basis points the previous week[42]

宏观研究 证 券 研 究 报 告 【宏观快评】2025 年 12 月非农数据点评 10W！或是美国降息的就业分水岭 主要观点 ❖ 2025 年 12 月份非农数据简述 1、新增非农低于预期，前两个月数据明显下修。新增非农就业 5 万，预期 7 万。私人部门新增非农就业 3.7 万，预期 7.5 万。10-11 月新增就业合计下修 7.6 万。就业增长集中在教育保健服务（+4.1 万，前值+5.9 万）、休闲酒店（+4.7 万，前值-0.3 万）。零售、建筑、制造业、专业和商业服务等行业就业萎缩。 2、失业率意外回落，录得 4.4%（4.375%），预期 4.5%，前值 4.5%（4.536%）。 劳动参与率从 62.46%降至 62.40%，预期 62.4%。失业率下行主要源于就业增 长和供给小幅收缩，前者影响约 0.14 个百分点，后者影响约 0.03 个百分点。 3、时薪增速符合预期，但周工时下滑。私人行业时薪环比 0.3%，预期 0.3%， 同比增速 3.8%，预期 3.6%。周工时从 34.3 小时降至 34.2 小时，仍处于 2015 年以来的低位水平。周薪环比持平，并未增长（时薪是周薪和周工时的倒 ...

Investment Rating - The report maintains a "Buy" recommendation for the transportation industry, particularly focusing on the low-altitude economy and drone sectors [2]. Core Insights - The report emphasizes the growing importance of drones in modern warfare, highlighting their low cost and high efficiency, with global military drone spending expected to grow from $14.9 billion in 2025 to $28.6 billion by 2034, at a CAGR of 7.5% [4][8]. - It suggests a focus on companies involved in drone manufacturing and military applications, such as Aerospace Rainbow and Zhongyun Drone, as well as industrial drone representatives like Zongheng Co. and Green Energy Huichong [4][13]. - The report also discusses the urgent need for anti-drone systems, estimating a global market potential of $63 billion by 2025, with a CAGR of 11-13% from 2025 to 2030 [15][16]. Summary by Sections Industry Overview - The transportation industry includes 121 listed companies with a total market capitalization of ¥34,170.25 billion, representing 2.69% of the overall market [2]. - The absolute performance of the industry over the past 12 months is 9.0%, while relative performance has decreased by 16.9% [2]. Drone Warfare and Anti-Drone Systems - Drones are increasingly recognized as a new force in modern warfare, with significant applications in recent conflicts [5][6]. - The report highlights the successful test flights of new drone models, such as the Rainbow-7 and the "Jiutian" drone, showcasing advancements in China's drone capabilities [11][12]. - The anti-drone market is driven by both military and civilian needs, with a focus on protecting critical infrastructure [15][16]. Aviation Industry and Engine Manufacturing - The report identifies the aviation engine sector as a critical area for investment, noting that China is still in the early stages of developing its civil aviation engines, with a market penetration of less than 1% [19][20]. - It recommends focusing on the commercial aviation engine supply chain, including key players like Aero Engine Corporation of China and its suppliers [21][24]. Market Performance - The Huachuang Transportation Low Altitude 60 Index increased by 7.6% over the past week and year, outperforming major indices like the CSI 300 [28][30]. - Notable stock performances include Aerospace Electronics, which saw a 35% increase, and Haige Communication, which rose by 27% [33][34]. Investment Recommendations - The report suggests a multi-faceted approach to investment, focusing on various segments of the low-altitude economy, including manufacturers, supply chains, and digital infrastructure [38][39]. - Key companies to watch include Wan Feng Ao Wei, Xie Rui, and Zhongyun Drone, among others, as they are positioned to benefit from the growth in low-altitude applications and infrastructure [39][46].

Investment Rating - The report maintains a "Recommended" rating for the mechanical industry, with a focus on AI equipment and consumables, as well as engineering machinery [1]. Core Insights - The mechanical industry is expected to benefit from the acceleration of AI applications, particularly in high-performance servers and GPU demand, driven by the rapid iteration of AI models and smart hardware [7]. - The excavator market is projected to exceed expectations in both domestic and international sales, with a forecasted 17% year-on-year growth in 2025, supported by government policies and infrastructure projects [7]. - The report emphasizes the potential for a new recovery cycle in the equipment industry, driven by monetary and fiscal policy support, and suggests focusing on key companies across various segments [7]. Summary by Sections Key Company Earnings Forecast, Valuation, and Investment Ratings - Companies such as 汇川技术 (Inovance Technology), 法兰泰克 (Falan Tech), and 信捷电气 (Xinjie Electric) are rated as "Strong Buy" with projected EPS growth and favorable PE ratios [2][8]. - For example, 汇川技术 is expected to have an EPS of 2.11元 in 2025, with a PE ratio of 37.13, indicating strong growth potential [2]. Industry and Company Investment Views - The report highlights the AI equipment and consumables sector as a key area for investment, with significant growth expected in the PCB market driven by AI infrastructure needs [9]. - The engineering machinery sector is also highlighted, with companies like 三一重工 (Sany Heavy Industry) and 徐工机械 (XCMG) expected to benefit from increased domestic demand and international market recovery [7][9]. Key Data Tracking - The report provides macroeconomic data indicating a total market capitalization of 70,956.73 billion yuan for the mechanical industry, with 636 listed companies [4]. - The mechanical sector has shown strong performance, with a 5.7% increase in the sector index over the past week, outperforming major indices [11][14].

Investment Rating - The report maintains a "Buy" rating for the non-ferrous metals sector, highlighting the initiation of a spring rally with significant price increases in metals [2]. Core Views - The spring rally is believed to have started, with aluminum prices showing strong elasticity. As of January 9, the SHFE aluminum closing price was 24,385 CNY/ton, a 6.4% increase from December 31, 2025. The report anticipates that aluminum prices may rise further due to rigid supply constraints and increasing demand in new sectors [3][4]. - The report emphasizes the positive outlook for the electrolytic aluminum sector, predicting average profits to exceed 7,500 CNY/ton, supported by improved cash flow and stable profitability among companies [4]. - A strike at the Mantoverde copper mine in Chile could impact copper production, potentially exacerbating supply tightness in 2026 [5]. Summary by Sections Industrial Metals - **Aluminum Market**: The report notes a significant increase in aluminum prices and a rise in profits, driven by supply constraints and new demand areas. The global aluminum inventory remains low, providing strong support for prices [3]. - **Copper Market**: The report highlights a rise in copper inventories and recommends several companies in the copper sector, including Zijin Mining and Western Mining [6]. New Energy Metals and Minor Metals - **Cobalt Market**: The report indicates that cobalt exports from the Democratic Republic of Congo are delayed, leading to a potential price increase. The average price of electrolytic cobalt rose to 460,000 CNY/ton, a 1.1% increase from December 31, 2025 [7][12]. - **Company Performance**: Huayou Cobalt's 2025 earnings forecast exceeds market expectations, with a projected net profit increase of 40.8% to 55.2% year-on-year [14]. Industry Data - **Market Performance**: The non-ferrous metals sector has shown strong absolute and relative performance over the past year, with a 110.2% increase over 12 months [9]. - **Stock Market Data**: The total market capitalization of the sector is approximately 457.86 billion CNY, with 126 listed companies [8].

- The report introduces a "Total Heat Index" indicator, defined as the sum of browsing, self-selection, and click counts for individual stocks, normalized by their market share on the same day, and multiplied by 10,000. The indicator range is [0,10000][7] - A rotation strategy is constructed based on the weekly heat index change rate (MA2). At the end of each week, the strategy buys the broad-based index with the highest MA2 change rate. If the "Others" group has the highest change rate, the strategy remains in cash. The annualized return since 2017 is 8.74%, with a maximum drawdown of 23.5%. In 2026, the strategy achieved a return of 7.9%[13][16] - A concept-based strategy is developed by selecting the top 5 concepts with the highest weekly heat index change rate. Stocks within these concepts are filtered by excluding the bottom 20% in terms of market capitalization. Two portfolios are constructed: the "TOP" portfolio holds the top 10 stocks with the highest heat index within each concept, while the "BOTTOM" portfolio holds the bottom 10 stocks. The "BOTTOM" portfolio historically achieved an annualized return of 15.71% with a maximum drawdown of 28.89%. In 2026, the "BOTTOM" portfolio returned 6.4%[32][34]

Quantitative Models and Construction Methods 1. Model Name: Volume Model - **Construction Idea**: The model uses trading volume data to predict market trends[1][13] - **Construction Process**: The model analyzes the trading volume of various broad-based indices to generate buy or sell signals[1][13] - **Evaluation**: The model is effective in capturing short-term market movements[1][13] 2. Model Name: Feature Dragon Tiger List Institutional Model - **Construction Idea**: This model uses institutional trading data from the Dragon Tiger List to predict market trends[1][13] - **Construction Process**: The model analyzes the trading activities of institutions listed on the Dragon Tiger List to generate buy or sell signals[1][13] - **Evaluation**: The model is useful for understanding institutional trading behavior and its impact on the market[1][13] 3. Model Name: Feature Volume Model - **Construction Idea**: This model uses specific volume characteristics to predict market trends[1][13] - **Construction Process**: The model analyzes specific volume patterns to generate buy or sell signals[1][13] - **Evaluation**: The model is effective in identifying significant volume changes that precede market movements[1][13] 4. Model Name: Intelligent Algorithm CSI 300 Model - **Construction Idea**: This model uses intelligent algorithms to predict the CSI 300 index trends[1][13] - **Construction Process**: The model employs machine learning algorithms to analyze historical data and generate buy or sell signals for the CSI 300 index[1][13] - **Evaluation**: The model leverages advanced algorithms to improve prediction accuracy[1][13] 5. Model Name: Intelligent Algorithm CSI 500 Model - **Construction Idea**: This model uses intelligent algorithms to predict the CSI 500 index trends[1][13] - **Construction Process**: The model employs machine learning algorithms to analyze historical data and generate buy or sell signals for the CSI 500 index[1][13] - **Evaluation**: The model leverages advanced algorithms to improve prediction accuracy[1][13] 6. Model Name: Limit Up and Down Model - **Construction Idea**: This model uses the occurrence of limit up and down events to predict market trends[1][13] - **Construction Process**: The model analyzes the frequency and context of limit up and down events to generate buy or sell signals[1][13] - **Evaluation**: The model is effective in capturing extreme market movements[1][13] 7. Model Name: Up and Down Return Difference Model - **Construction Idea**: This model uses the difference between upward and downward returns to predict market trends[1][13] - **Construction Process**: The model calculates the difference between upward and downward returns to generate buy or sell signals[1][13] - **Evaluation**: The model provides insights into market momentum and potential reversals[1][13] 8. Model Name: Calendar Effect Model - **Construction Idea**: This model uses calendar-based patterns to predict market trends[1][13] - **Construction Process**: The model analyzes historical data to identify recurring calendar-based patterns and generate buy or sell signals[1][13] - **Evaluation**: The model is useful for identifying seasonal trends in the market[1][13] 9. Model Name: Long-term Momentum Model - **Construction Idea**: This model uses long-term momentum to predict market trends[1][14] - **Construction Process**: The model analyzes long-term price momentum to generate buy or sell signals[1][14] - **Evaluation**: The model is effective in capturing long-term market trends[1][14] 10. Model Name: A-Share Comprehensive Weapon V3 Model - **Construction Idea**: This model combines multiple factors to predict market trends[1][15] - **Construction Process**: The model integrates various indicators and models to generate a comprehensive buy or sell signal[1][15] - **Evaluation**: The model provides a holistic view of the market by combining multiple factors[1][15] 11. Model Name: A-Share Comprehensive Guozheng 2000 Model - **Construction Idea**: This model combines multiple factors to predict the Guozheng 2000 index trends[1][15] - **Construction Process**: The model integrates various indicators and models to generate a comprehensive buy or sell signal for the Guozheng 2000 index[1][15] - **Evaluation**: The model provides a holistic view of the market by combining multiple factors[1][15] 12. Model Name: Turnover Rate Inverse Volatility Model - **Construction Idea**: This model uses the inverse relationship between turnover rate and volatility to predict market trends[1][16] - **Construction Process**: The model analyzes the turnover rate and its inverse relationship with volatility to generate buy or sell signals[1][16] - **Evaluation**: The model is effective in identifying periods of high market uncertainty[1][16] Model Backtesting Results 1. Volume Model - **Indicator Value**: All broad-based indices are bullish[1][13] 2. Feature Dragon Tiger List Institutional Model - **Indicator Value**: Bullish[1][13] 3. Feature Volume Model - **Indicator Value**: Bullish[1][13] 4. Intelligent Algorithm CSI 300 Model - **Indicator Value**: Bullish[1][13] 5. Intelligent Algorithm CSI 500 Model - **Indicator Value**: Bullish[1][13] 6. Limit Up and Down Model - **Indicator Value**: Bullish[1][13] 7. Up and Down Return Difference Model - **Indicator Value**: All broad-based indices are bullish[1][13] 8. Calendar Effect Model - **Indicator Value**: Neutral[1][13] 9. Long-term Momentum Model - **Indicator Value**: Some broad-based indices are bullish[1][14] 10. A-Share Comprehensive Weapon V3 Model - **Indicator Value**: Bullish[1][15] 11. A-Share Comprehensive Guozheng 2000 Model - **Indicator Value**: Bullish[1][15] 12. Turnover Rate Inverse Volatility Model - **Indicator Value**: Bearish[1][16]