Investment Strategy - The report emphasizes that Xinjiang is benefiting from two major strategic shifts: the transition from coastal economies to the Belt and Road Initiative, positioning Xinjiang as a frontier hub with geographical advantages. The balance is shifting towards energy security and dual carbon environmental goals, making coal chemical industry a focal point for Xinjiang's resource advantages [7][8][10] - The report highlights the importance of coal chemical development in Xinjiang, noting that external conditions are now favorable for this sector. Factors include rising coal prices, alignment with China's resource endowments, and supportive industrial policies [7][8][9] - The report suggests focusing on two main investment lines: coal chemical investments and state-owned enterprise reforms. Key companies to watch include Tebian Electric Apparatus, Baofeng Energy, and Guanghui Energy, among others [11][12] Xinjiang Index Situation - The Xinjiang index stands at 104.9, down 0.46% week-on-week, while the coal chemical investment index is at 99.7, down 2.77%. The state-owned enterprise reform index is at 110.8, up 0.86% [14] - The top three gainers this week include: - Zhun Oil Co., Ltd. (002207.SZ) up 40.23% - Beiken Energy (002828.SZ) up 20.22% - International Industry (000159.SZ) up 13.34% - The top three decliners include: - Beixin Road and Bridge (002307.SZ) down 6.73% - Fosda (603173.SH) down 7.58% - Huijia Times (603101.SH) down 11.07% [14] Key Data Tracking - Key prices in Xinjiang include: - Q5000 mixed coal at 100 CNY/ton, unchanged week-on-week - Q5200 mixed coal at 197 CNY/ton, unchanged week-on-week - Main焦煤 at 780 CNY/ton - Methanol price at 1605 CNY/ton, with a price difference of -1180 CNY/ton compared to East China - Urea price at 1681 CNY/ton, with a price difference of -139 CNY/ton compared to Shandong [19] - In May 2025, coal railway shipments from key state-owned coal mines reached 3.308 million tons, a year-on-year increase of 16.6%. The raw coal production in Xinjiang was 46.651 million tons, a year-on-year increase of 23.44% [19] Key News and Company Announcements - On June 13, the National Development and Reform Commission approved the 2 billion cubic meters/year coal-to-natural gas project by Xinjiang Tianchi Energy Co., Ltd. The total investment for this project is 17.04 billion CNY [37][39] - Recent updates on key coal chemical projects include: - Tebian Electric's coal-to-gas project approved with a capacity of 20 billion cubic meters/year - National Energy Group's coal-to-gas project with a capacity of 40 billion cubic meters/year is progressing with equipment tenders [41]

Investment Rating - The report maintains a "Recommend" rating for the wind power industry, indicating an expectation of growth exceeding the benchmark index by more than 5% in the next 3-6 months [3][35]. Core Insights - The report highlights significant developments in offshore wind projects, with Guangdong's offshore wind project winning a bid of 0.8GW at an average price of 2506 CNY/kW [1][9]. - The total bidding for wind power in 2025 has reached 43.2GW, with offshore and onshore projects accounting for 3.6GW and 39.7GW respectively [9][11]. - The report emphasizes three main investment themes: high domestic offshore wind project reserves, robust onshore wind bidding in 2024, and regional growth in overseas installations [18][21]. Summary by Sections Industry Basic Data - The industry comprises 301 listed companies with a total market capitalization of 49,118.76 billion CNY and a circulating market value of 42,780.41 billion CNY [4]. Company Profit Forecasts and Valuations - Key companies and their investment ratings include: - Dongfang Cable: EPS forecast of 2.29 CNY for 2025, PE of 21.21, rated "Recommend" [3]. - Zhongtian Technology: EPS forecast of 1.04 CNY for 2025, PE of 13.00, rated "Recommend" [3]. - Mingyang Smart Energy: EPS forecast of 0.71 CNY for 2025, PE of 15.01, rated "Strong Recommend" [3]. - Times New Material: EPS forecast of 0.92 CNY for 2025, PE of 13.65, rated "Recommend" [3]. Wind Power Bidding Data - The report details the bidding activity for wind power, with 4.2GW awarded this week, including 0.8GW offshore and 3.4GW onshore [11][14]. - The average bidding price for offshore wind was 2506 CNY/kW, while onshore wind averaged 1552 CNY/kW [14]. Investment Recommendations - The report suggests focusing on companies involved in offshore wind projects, onshore wind manufacturing, and those expanding into international markets [18][21].

Economic Focus - The central government is emphasizing infrastructure development, "trade-in" policies for consumer goods, and foreign trade, particularly in economically strong provinces like Jiangsu[1] - Recent surveys in Jiangsu highlighted the need for high-standard project execution and the importance of Jiangsu's role in national economic contributions[1] Industrial Development - The government is focusing on technological advancements and new production capabilities, with significant attention on sectors like engineering machinery, AI, and clean energy[2] - Regulatory measures are being reinforced in the platform economy to combat issues like false advertising and unfair competition practices[2] Financial Initiatives - The establishment of an offshore financial service reform pilot in Shanghai is aimed at enhancing international trade finance capabilities[4] - A digital RMB international operation center is being set up to facilitate cross-border payments and enhance the global use of the RMB[4] International Cooperation - The recent China-Central Asia summit resulted in the signing of multiple cooperation agreements, marking a significant milestone in regional diplomatic relations[9] - The summit emphasized the importance of mutual trust and support among participating nations, with a focus on high-quality development along the Belt and Road Initiative[10] Financial Market Reforms - The China Securities Regulatory Commission (CSRC) is set to introduce a growth tier on the Sci-Tech Innovation Board to better support innovative companies[21] - Plans to expand the Qualified Foreign Institutional Investor (QFII) program to include 100 tradable futures and options products are underway, enhancing foreign investment opportunities[5]

Quantitative Models and Construction 1. Model Name: Heston Model - **Model Construction Idea**: The Heston model is used to calculate the implied volatility of near-month at-the-money options, serving as a market fear index. Implied volatility reflects market participants' expectations of future volatility [8]. - **Model Construction Process**: The Heston model is a stochastic volatility model where the variance of the asset price follows a mean-reverting square-root process. The model is defined by the following equations: $ dS_t = \mu S_t dt + \sqrt{v_t} S_t dW_t^1 $ $ dv_t = \kappa (\theta - v_t) dt + \sigma \sqrt{v_t} dW_t^2 $ Here: - \( S_t \): Asset price - \( v_t \): Variance - \( \mu \): Drift rate - \( \kappa \): Mean reversion speed - \( \theta \): Long-term variance - \( \sigma \): Volatility of variance - \( W_t^1, W_t^2 \): Correlated Wiener processes [8] 2. Model Name: Multi-Sector Timing Model (Scissor Difference Strategy) - **Model Construction Idea**: This model uses the difference in the number of bullish and bearish signals among sector constituents to construct a timing strategy. If no bullish or bearish signals are present, the scissor difference is set to zero. The model aims to outperform sector indices [16]. - **Model Construction Process**: - Count the number of bullish and bearish signals for each sector's constituent stocks daily. - Compute the scissor difference as the difference between bullish and bearish signals. - If both counts are zero, the scissor difference is set to zero. - Construct a timing strategy based on the scissor difference ratio [16]. - **Model Evaluation**: The model historically outperformed all sector indices, demonstrating excellent backtesting performance [16]. --- Model Backtesting Results 1. Heston Model - **Implied Volatility Results**: - SSE 50: 11.85% (down 0.88% WoW) - SSE 500: 14.35% (down 1.59% WoW) - CSI 1000: 18.06% (down 0.42% WoW) - CSI 300: 12.64% (down 0.73% WoW) [10] 2. Multi-Sector Timing Model - **Sector Outperformance**: The model outperformed all sector indices, achieving a 100% success rate in backtesting [16]. --- Quantitative Factors and Construction 1. Factor Name: Shape-Based Timing Signals - **Factor Construction Idea**: Shape-based signals are derived from historical K-line patterns, including bullish patterns (e.g., "Golden Needle Bottom," "Rocket Launch," "Manjianghong") and bearish patterns (e.g., "Hanging Line," "Paradise Line," "Dark Cloud Cover"). These patterns indicate potential price reversals [24]. - **Factor Construction Process**: - Identify specific K-line patterns based on predefined criteria. - Evaluate the historical performance of these patterns in predicting price movements. - Use the patterns to generate timing signals for individual stocks [24]. - **Factor Evaluation**: Bullish patterns like "Golden Needle Bottom" and "Rocket Launch" demonstrated strong positive predictive power [24]. --- Factor Backtesting Results 1. Shape-Based Timing Signals - **Signal Statistics**: - Positive signals: 2,699 occurrences, with an average future high-point success rate of 28.25% - Negative signals: 3,525 occurrences, with an average future low-point success rate of 71.88% [13] 2. Sector Timing Signals - **Bullish Sectors**: Home Appliances, Comprehensive, Communication, Textile & Apparel, Consumer Services, Transportation, Petrochemicals [19] 3. Stock-Specific Signals - **Consecutive Bullish Signals**: - 5-day signals: Stocks like Kailong Co. and Shipu Testing [21] - 4-day signals: Stocks like Jiangnan Chemical, Beijing-Shanghai High-Speed Railway, and Nandu Property [22][23] - **Special Bullish Patterns**: - Stocks like Retired Longyu ("Arrow on the String") and Suotong Development ("Manjianghong") [25][26] 4. Broker Gold Stock Signals - **Highlighted Stocks**: BYD, Feilihua, Wancheng Group, Sichuan Road & Bridge, Wolong Electric Drive, Lansheng Co., PetroChina, Dongpeng Beverage [29][33]

Quantitative Models and Construction Methods 1. Model Name: Broad-based Index Heat Rotation Strategy - **Model Construction Idea**: The strategy is based on the weekly heat change rate (MA2) of broad-based indices. By identifying the index with the highest heat change rate, the strategy aims to capture short-term market sentiment shifts[7][13][16] - **Model Construction Process**: 1. Group all A-share stocks into five categories: CSI 300, CSI 500, CSI 1000, CSI 2000, and "Others" 2. Calculate the total heat indicator for each group by summing the heat indicators of constituent stocks 3. Compute the weekly heat change rate for each group and apply a 2-week moving average (MA2) for smoothing 4. At the end of each week, invest in the index with the highest heat change rate (MA2). If the "Others" group has the highest rate, remain in cash[8][11][13] - **Model Evaluation**: The strategy demonstrates the ability to capture short-term sentiment-driven opportunities in the market[13] --- Backtesting Results of Models 1. Broad-based Index Heat Rotation Strategy - **Annualized Return**: 8.74% since 2017[16] - **Maximum Drawdown**: 23.5%[16] - **Cumulative Return (2025)**: 9.6%[16] --- Quantitative Factors and Construction Methods 1. Factor Name: Total Heat Indicator - **Factor Construction Idea**: The total heat indicator is used as a proxy for market sentiment, aggregating the attention metrics of individual stocks[7] - **Factor Construction Process**: 1. Define the total heat indicator for individual stocks as the sum of browsing, watchlist additions, and click counts 2. Normalize the indicator by dividing it by the total market value on the same day 3. Multiply the normalized value by 10,000 to scale the indicator within the range [0, 10,000][7] - **Factor Evaluation**: The factor effectively captures market sentiment at the stock level and can be aggregated to broader categories like indices, industries, or concepts[7] 2. Factor Name: Weekly Heat Change Rate (MA2) - **Factor Construction Idea**: This factor measures the short-term change in market sentiment by tracking the weekly variation in the total heat indicator[13] - **Factor Construction Process**: 1. Calculate the weekly change rate of the total heat indicator for each stock or group 2. Apply a 2-week moving average (MA2) to smooth out short-term fluctuations[13][20] - **Factor Evaluation**: The MA2 smoothing enhances the stability of the factor, making it suitable for identifying trends in market sentiment[13] 3. Factor Name: Concept Heat Ranking - **Factor Construction Idea**: This factor identifies the hottest and coldest concepts based on their weekly heat change rates, enabling the construction of sentiment-driven portfolios[31] - **Factor Construction Process**: 1. Rank concepts by their weekly heat change rates 2. Select the top 5 concepts with the highest heat change rates 3. Construct two portfolios: - **TOP Portfolio**: Select the top 10 stocks with the highest total heat within each concept - **BOTTOM Portfolio**: Select the bottom 10 stocks with the lowest total heat within each concept[31] - **Factor Evaluation**: The factor highlights the potential for excess returns by exploiting sentiment-driven mispricing in concept stocks[31] --- Backtesting Results of Factors 1. Total Heat Indicator - **No specific backtesting results provided** 2. Weekly Heat Change Rate (MA2) - **No specific backtesting results provided** 3. Concept Heat Ranking - **BOTTOM Portfolio Annualized Return**: 15.71%[33] - **BOTTOM Portfolio Maximum Drawdown**: 28.89%[33] - **BOTTOM Portfolio Cumulative Return (2025)**: 18%[33]

Policy Deployment - In October 2024, the Ministry of Finance announced a debt limit of CNY 1.2 trillion to support local governments in resolving hidden debts and settling overdue payments to enterprises[11] - The 2025 government work report proposed issuing CNY 4.4 trillion in special bonds, focusing on investment, land acquisition, and settling overdue payments[12] Recent Progress - Yunnan Province allocated CNY 356 billion for overdue payments, accounting for approximately 37% of its annual special bond limit[14] - Hunan Province designated CNY 200 billion for settling overdue payments, representing about 14% of its annual special bond limit[14] - The total amount confirmed for overdue payments across provinces is CNY 556 billion, with expectations for the total to exceed CNY 1 trillion for the year[18] Economic Observations - The Huachuang Macro WEI index rose to 7.94% as of June 15, 2025, up 1.59 percentage points from June 8, driven by asphalt operating rates and retail sales of passenger cars[27] - Retail sales of passenger cars increased by 21% year-on-year in the first half of June, compared to 13.3% in May[32] - The average land premium rate remained low at 1.24% from June 2 to June 15, down from 4.93% in May[33] Construction and Trade - The operating rate of asphalt plants was 30.4% as of June 18, 2025, a decrease of 1.1% from the previous week[40] - Container throughput at monitored ports declined by 0.7% week-on-week as of June 15, with a four-week cumulative year-on-year decrease of 4.5%[45] Financial Indicators - As of June 20, 2025, CNY 2.09 trillion in new special bonds had been issued, achieving 47.5% of the annual target, higher than 33% in the previous year[7] - Interest rates for funds decreased, with DR001 at 1.3742% and DR007 at 1.4941% as of June 20, 2025[7]

行业研究 证 券 研 究 报 告 推荐（维持） 以伊冲突升级，本周油价上涨 基础化工 2025 年 06 月 23 日 华创证券研究所 证券分析师：杨晖 邮箱：yanghui@hcyjs.com 执业编号：S0360522050001 证券分析师：吴宇 邮箱：wuyu1@hcyjs.com 执业编号：S0360524010002 证券分析师：陈俊新 邮箱：chenjunxin@hcyjs.com 执业编号：S0360525040001 能源周报（20250616-20250622） 行业基本数据 | | | 占比% | | --- | --- | --- | | 股票家数(只) | 490 | 0.06 | | 总市值(亿元) | 42,481.40 | 4.23 | | 流通市值(亿元) | 37,730.76 | 4.79 | 相对指数表现 | % | 1M | 6M | 12M | | --- | --- | --- | --- | | 绝对表现 | -1.1% | -1.2% | 11.1% | | 相对表现 | 0.3% | 0.9% | 1.3% | -12% 0% 11% 23% 24/06 2 ...

Investment Rating - The report maintains a "Recommendation" rating for the computer industry, expecting the industry index to rise more than 5% over the next 3-6 months compared to the benchmark index [3][38]. Core Insights - The computer sector experienced a decline in the week of June 16-20, with the CITIC computer index dropping by 1.87%, the ChiNext index down by 1.66%, and the Shanghai Composite index falling by 0.51% [9][16]. - The report highlights the rapid advancements in AI, particularly in multimodal models, with significant developments from Google and Meta, indicating a promising future for the industry [9][20][23]. - The report notes that the market's focus is shifting from technology themes to performance realization and rapid industrial transformation as companies begin to disclose their earnings [9][12]. Summary by Sections Industry Weekly Viewpoint - The report discusses the performance of the computer sector, noting the top gainers and losers during the week, with notable increases in stocks like Chutianlong (up 36.59%) and Sifang Jingchuang (up 29.21%) [9][16]. - It emphasizes the ongoing innovations in AI, particularly the introduction of multimodal products that integrate visual and audio elements, which are gaining traction in the market [9][12]. Weekly Market Review - The report provides a detailed review of the market performance for the week, highlighting the overall decline in major indices and the net outflow of funds from the computer sector [16][19]. Funding Situation Review - The report indicates a total net outflow of 270 billion from all A-shares, with the computer sector experiencing a net outflow of 21 billion [19]. Progress in Multimodal Models - The report details the advancements in AI models, particularly Google's Veo 3 and Meta's Llama 4, which have achieved significant breakthroughs in video generation and multimodal capabilities [20][23]. - Veo 3 is noted for its ability to synchronize audio and visual elements seamlessly, while Llama 4 boasts a massive parameter scale and enhanced multimodal integration [20][23]. Investment Recommendations and Beneficiary Targets - The report suggests focusing on AI enterprise services and application scenarios, listing specific companies across various sectors such as office software, finance, education, and healthcare that are expected to benefit from these advancements [12][25].

1. Report Industry Investment Rating No information provided in the content. 2. Core Viewpoints of the Report - In the second quarter, the growth rate of fixed - asset investment slowed down. Given the external uncertainties in the second half of the year, the necessity of stabilizing investment has increased. The new policy - based financial instruments proposed in the April Politburo meeting have attracted high market attention. There is a high probability that the instruments will be implemented in the short term, and the third quarter may be the period for the implementation of broad - credit policies, which will affect the bond market sentiment [1][24]. - The risk of crossing the half - year is controllable, but the institutional fund arrangement is relatively slow. The large - bank net lending scale has significantly increased, and the inter - bank cross - quarter fund progress is relatively slow [3]. - Since June, the bond market's spread exploration has shifted from the mid - term to the ultra - long - term. However, investors should flexibly stop losses and realize profits [4]. - In the bond market this week, the LuJiaZui Conference did not meet expectations, and the yield fluctuated within a narrow range. The central bank's OMO continued net withdrawals, and the capital market was balanced and loose. The net financing of national bonds and policy - based financial bonds decreased, while that of local bonds and inter - bank certificates of deposit increased. The term spread of national bonds widened, and that of China Development Bank bonds narrowed [10][54]. 3. Summary According to the Directory 3.1 New Policy - based Financial Instruments: Progress - The necessity of stabilizing investment has increased due to the slowdown of fixed - asset investment growth in the second quarter and external uncertainties in the second half of the year. Since May, local governments have accelerated the project reserve of policy - based financial instruments, with a possible quota of 500 billion yuan, and the support for science and technology and consumption infrastructure construction may be prioritized [1][14]. - Referring to the experience in 2022, it took about two months from the release of the instrument quota to the completion of the investment, with a relatively fast pace. The policy - based financial supply in 2022 had a leverage ratio of over 4.7 times for credit and over 10 times for infrastructure investment [17]. - The third quarter may be the period for the implementation of broad - credit policies, and attention should be paid to the impact on the bond market sentiment [24]. 3.2 Cross - half - year Risk is Controllable, and Institutional Fund Arrangement is Slow - This week, the tax period passed smoothly. After the tax period, the capital sentiment tightened briefly, which may be related to the increase in the bond market leverage level. The central bank's operations remained relatively active, and the reverse - repurchase balance was at a seasonal high [3]. - The large - bank net lending scale has significantly increased, with the single - day net lending scale reaching 5.3 trillion yuan, a record high for the same period. As of June 20, the inter - bank cross - quarter fund progress was 12%, lower than the previous level. The cross - half - year risk is expected to be relatively controllable [28]. 3.3 Bond Market Strategy: Spread Exploration Shifts from the Mid - term to the Ultra - long - term, but Flexibly Stop Losses and Realize Profits - From April to May, the bond market fully explored the spreads of mid - term interest - rate varieties. The spread quantile of mid - term varieties decreased from 75% - 96% to 44% at the end of May, with limited room for further compression [34]. - In June, the spread exploration shifted to the ultra - long - term. The best - performing maturities since April have experienced two rounds of "short - term → mid - term → ultra - long - term" rotation. The recent ultra - long - term market, mainly driven by trading desks such as funds and other products, is due to the strong demand for capital gains in a low - interest - rate environment and the expected opening of the bond - allocation space for insurance companies in the third quarter [4][37]. - Investors should continue to pay attention to the cost - effectiveness of the ultra - long - term bonds and stop losses and realize profits at appropriate times, such as when the ultra - long - term spreads are fully explored, if the central bank announces bond purchases at the end of June, and in July [5]. 3.4 Bond Market Review: The LuJiaZui Conference did not Meet Expectations, and the Yield Fluctuated within a Narrow Range - **Funding**: The central bank's OMO continued net withdrawals, and the capital market was balanced and loose. The weighted price of DR001 fell back to around 1.37%, and the issuance price of 1 - year national - share bank certificates of deposit dropped to 1.63% [11]. - **Primary Issuance**: The net financing of national bonds and policy - based financial bonds decreased, while that of local bonds and inter - bank certificates of deposit increased [59]. - **Benchmark Changes**: The term spread of national bonds widened, and that of China Development Bank bonds narrowed. The short - term performance of national bonds was better than that of the long - term, while the long - term performance of China Development Bank bonds was better than that of the short - term [54].

Investment Rating - The report maintains a "Recommended" investment rating for the banking sector, expecting the industry index to outperform the benchmark index by over 5% in the next 3-6 months [24]. Core Insights - The new market risk regulations enhance operational efficiency for banks and establish a solid foundation for future business development [4]. - The regulations clarify the definition of market risk, separating it from interest rate risk, and emphasize the need for improved governance structures and responsibilities among the board, supervisors, and senior management [2][3]. - The report highlights the importance of the new regulations in strengthening banks' risk management capabilities amid increasing complexity in domestic and global trade [4]. Summary by Sections Market Risk Definition and Governance - The new regulations define market risk more rigorously, focusing on risks from adverse changes in interest rates, exchange rates, stock prices, and commodity prices [2]. - The governance structure is refined, specifying the responsibilities of the board, supervisors, and senior management in market risk management [3]. Market Risk Management Requirements - The report details enhanced requirements for risk identification, measurement, monitoring, control, and reporting, aligning with current market practices [3]. - Stricter requirements for the segregation of trading and non-trading activities are introduced, ensuring clearer roles and responsibilities [3]. Investment Opportunities - The report suggests that the banking sector is poised for increased capital inflows due to medium to long-term investments and public fund reforms, recommending a diversified investment strategy focusing on state-owned banks and quality regional banks [9]. - It emphasizes the potential for absolute returns in banks with high dividend yields and strong asset quality, particularly recommending banks like China Merchants Bank and CITIC Bank [9][10].