Investment Rating - The communication sector maintains a "Buy" rating for key stocks such as Tianfu Communication, Ruijie Network, China Mobile, and China Telecom, while China Unicom is rated as "Overweight" [3][5][61]. Core Insights - In Q2 2025, the communication sector's fund holdings increased to 3.61%, up by 1.31 percentage points, indicating a shift from underweight to overweight status [2][15]. - The communication sector's TTM P/E ratio as of July 24, 2025, is 35.71x, which is at the 37.5% historical percentile since early 2011 [2][15]. - Key areas of focus include the domestic computing power and its supporting industrial chain, particularly in optical modules and related technologies [1][14]. Summary by Sections Market Performance - The communication index fell by 0.77% last week, while the Shanghai Composite Index rose by 1.67% and the Shenzhen Component Index increased by 2.33% [1][14]. Fund Holdings - Q2 2025 saw a rise in the communication sector's fund holdings, with a notable increase in the allocation towards optical modules and military communications, while reducing exposure to data centers and wireless equipment [2][15]. Recommended Stocks - Key recommended stocks include: - Tianfu Communication (300394 CH) with a target price of 119.12 and a "Buy" rating - Ruijie Network (301165 CH) with a target price of 88.70 and a "Buy" rating - China Mobile (600941 CH) with a target price of 126.40 and a "Buy" rating - China Telecom (601728 CH) with a target price of 9.13 and a "Buy" rating - China Unicom (600050 CH) with a target price of 7.62 and an "Overweight" rating [5][61]. Key Stock Performance - The top five stocks with increased fund holdings in Q2 2025 include: - Xinyi Technology (300502 SZ) with a total market value increase of 191.65 billion - Zhongji Xuchuang (300308 SZ) with an increase of 182.70 billion - Tianfu Communication (300394 SZ) with an increase of 29.69 billion - Yuanjie Technology (688498 SH) with an increase of 16.90 billion - Haige Communication (002465 SZ) with an increase of 11.01 billion [25][26].

Investment Rating - The report maintains a "Buy" rating for the company with a target price of HKD 1,200 [6][7]. Core Views - The company is expected to achieve a revenue of approximately RMB 120-125 billion in the first half of 2025, representing a year-on-year growth of about 241%-255% [1][2]. - The adjusted net profit is projected to be around RMB 23-23.6 billion, reflecting a year-on-year increase of approximately 282%-292% [2][3]. - The strong performance is attributed to contributions from both online and offline stores, as well as the opening of new large stores in key locations [1][4]. Summary by Sections Revenue Growth - The company anticipates sales performance (including tax revenue) of about RMB 138-143 billion in 1H25, which is a year-on-year increase of approximately 240%-252% [2]. - The revenue growth is driven by the rapid expansion of brand influence, continuous product innovation, and significant growth in both online and offline channels [2][3]. Profitability - The expected adjusted net profit margin for 1H25 is around 19%, an increase of approximately 1.3 percentage points compared to 2024 [2]. - The improvement in net profit margin is primarily due to operational leverage optimization, which has led to a significant reduction in expense ratios [2][3]. Product Innovation - The company continues to innovate on traditional craftsmanship, launching new products such as "Seven Sons Gourd" and "Cross Diamond Pendant" in 1H25, which have received positive market feedback [3]. - The introduction of these new products enhances the diversity of gold jewelry offerings and broadens the customer base [3]. Channel Expansion - The company has made significant breakthroughs in both domestic and international high-end markets, opening stores in premium locations such as Shenzhen, Shanghai, and Singapore [4]. - The ongoing optimization of store locations, member operations, and brand building is expected to further enhance single-store performance [4]. Financial Forecast - The report maintains net profit forecasts for 2025-2027 at RMB 49.1 billion, RMB 62.1 billion, and RMB 75.8 billion respectively [5]. - The target price of HKD 1,200 corresponds to a PE ratio of 38.5 times for 2025, reflecting the company's strong growth momentum and high-end brand positioning [5].

Quantitative Models and Construction Methods 1. Model Name: Commodity Term Structure Strategy - **Model Construction Idea**: This strategy utilizes the roll yield factor to capture the contango or backwardation state of commodities, dynamically going long on commodities with high roll yields and shorting those with low roll yields[51] - **Model Construction Process**: - The roll yield factor is calculated based on the term structure of commodity futures prices - The strategy dynamically adjusts positions to go long on commodities with high roll yields and short on those with low roll yields[51] - **Model Evaluation**: The strategy is designed to exploit the carry factor in commodity markets, providing a systematic approach to capturing term structure-related returns[51] 2. Model Name: Commodity Time-Series Momentum Strategy - **Model Construction Idea**: This strategy uses multiple technical indicators to capture medium- to long-term trends in domestic commodities, dynamically going long on assets with upward trends and shorting those with downward trends[51] - **Model Construction Process**: - Technical indicators such as moving averages and momentum signals are used to identify trends - Positions are dynamically adjusted based on the identified trends, with long positions in upward-trending assets and short positions in downward-trending assets[51] - **Model Evaluation**: The strategy systematically captures momentum effects in commodity markets, leveraging trend-following behavior[51] 3. Model Name: Commodity Cross-Sectional Inventory Strategy - **Model Construction Idea**: This strategy uses inventory factors to capture changes in the fundamentals of domestic commodities, dynamically going long on assets with declining inventories and shorting those with increasing inventories[51] - **Model Construction Process**: - Inventory data is used to construct factors reflecting supply-demand dynamics - Positions are dynamically adjusted to go long on commodities with declining inventories and short on those with increasing inventories[51] - **Model Evaluation**: The strategy effectively captures fundamental changes in commodity markets, providing a systematic approach to exploiting inventory-related signals[51] 4. Model Name: Commodity Fusion Strategy - **Model Construction Idea**: This strategy combines the above three sub-strategies (term structure, time-series momentum, and cross-sectional inventory) using equal weighting to create a diversified commodity investment approach[49] - **Model Construction Process**: - The three sub-strategies are equally weighted to form a composite strategy - The combined strategy dynamically adjusts positions based on the signals from the sub-strategies[49] - **Model Evaluation**: The fusion strategy aims to diversify risk and enhance returns by integrating multiple sources of alpha in commodity markets[49] --- Model Backtesting Results 1. Commodity Term Structure Strategy - **Two-Week Return**: -1.39%[54] - **Year-to-Date Return**: 1.38%[56] 2. Commodity Time-Series Momentum Strategy - **Two-Week Return**: 1.99%[54] - **Year-to-Date Return**: -1.97%[61] 3. Commodity Cross-Sectional Inventory Strategy - **Two-Week Return**: -0.26%[54] - **Year-to-Date Return**: 4.00%[68] 4. Commodity Fusion Strategy - **Two-Week Return**: 0.12%[49] - **Year-to-Date Return**: 1.14%[49] --- Quantitative Factors and Construction Methods 1. Factor Name: Roll Yield Factor - **Factor Construction Idea**: Measures the contango or backwardation state of commodity futures markets[51] - **Factor Construction Process**: - Calculated based on the difference between near-month and far-month futures prices - Positive roll yield indicates backwardation, while negative roll yield indicates contango[51] 2. Factor Name: Momentum Factor - **Factor Construction Idea**: Captures the trend-following behavior in commodity prices[51] - **Factor Construction Process**: - Derived from technical indicators such as moving averages and momentum signals - Positive momentum indicates an upward trend, while negative momentum indicates a downward trend[51] 3. Factor Name: Inventory Factor - **Factor Construction Idea**: Reflects supply-demand dynamics in commodity markets[51] - **Factor Construction Process**: - Based on changes in inventory levels - Declining inventories indicate tightening supply, while increasing inventories indicate loosening supply[51] --- Factor Backtesting Results 1. Roll Yield Factor - **Performance**: Contributed positively to the term structure strategy, with key contributors being iron ore, ethylene glycol, and methanol[58] 2. Momentum Factor - **Performance**: Contributed positively to the time-series momentum strategy, with key contributors being hot-rolled coil, rebar, and zinc[67] 3. Inventory Factor - **Performance**: Contributed positively to the cross-sectional inventory strategy, with key contributors being PVC, zinc, and rubber[73]

Quantitative Models and Construction Methods 1. Model Name: Genetic Programming Industry Rotation Model - **Model Construction Idea**: This model directly extracts factors from industry indices' price-volume and valuation data, updating the factor library at the end of each quarter. It selects the top five industries with the highest multi-factor composite scores for equal-weight allocation on a weekly basis[3][32] - **Model Construction Process**: - Factor extraction is performed on industry indices based on price-volume and valuation data - The factor library is updated quarterly - Weekly rebalancing is conducted, selecting the top five industries with the highest composite scores for equal-weight allocation[3][32] - **Model Evaluation**: The model achieved strong absolute and relative returns but exhibited rapid industry rotation, leading to slight underperformance against the benchmark in the previous week[3][32] 2. Model Name: Absolute Return ETF Simulated Portfolio - **Model Construction Idea**: Asset allocation weights are determined based on recent trends, with stronger-trending assets assigned higher weights. Equity allocation within the portfolio follows the monthly views of an industry rotation model[4][37] - **Model Construction Process**: - Asset classes are weighted based on recent trend strength - Equity allocation is determined by a monthly industry rotation model - The portfolio includes equity ETFs (e.g., dividend, healthcare, metals) and commodity ETFs (e.g., energy, soybean meal)[4][39] - **Model Evaluation**: The portfolio demonstrated stable performance with a focus on trend-following and diversification[4][37] --- Model Backtesting Results 1. Genetic Programming Industry Rotation Model - **Annualized Return**: 31.87% - **Annualized Volatility**: 18.18% - **Sharpe Ratio**: 1.75 - **Maximum Drawdown**: -19.63% - **Calmar Ratio**: 1.62 - **Year-to-Date (YTD) Return**: 28.68% - **Weekly Performance**: 3.03%[35] 2. Absolute Return ETF Simulated Portfolio - **Annualized Return**: 6.53% - **Annualized Volatility**: 3.82% - **Maximum Drawdown**: -4.65% - **Sharpe Ratio**: 1.71 - **Calmar Ratio**: 1.41 - **Year-to-Date (YTD) Return**: 5.58% - **Weekly Performance**: 0.33%[38] --- Quantitative Factors and Construction Methods 1. Factor Name: Market Intrinsic Momentum Indicators - **Factor Construction Idea**: These indicators measure the internal momentum of the market by analyzing the distribution of individual stock performance[18][19] - **Factor Construction Process**: - **Indicator 1**: Daily turnover difference between rising and falling stocks, normalized by total turnover $ \text{Indicator 1} = \frac{\text{Turnover of rising stocks - Turnover of falling stocks}}{\text{Total turnover}} $ - **Indicator 2**: Monthly high-low turnover difference, normalized by total turnover $ \text{Indicator 2} = \frac{\text{Turnover of stocks hitting monthly highs - Turnover of stocks hitting monthly lows}}{\text{Total turnover}} $ - **Indicator 3**: Six-month high-low turnover difference, normalized by total turnover $ \text{Indicator 3} = \frac{\text{Turnover of stocks hitting six-month highs - Turnover of stocks hitting six-month lows}}{\text{Total turnover}} $ - **Indicator 4**: Annual high-low turnover difference, normalized by total turnover $ \text{Indicator 4} = \frac{\text{Turnover of stocks hitting annual highs - Turnover of stocks hitting annual lows}}{\text{Total turnover}} $[18][19] - **Factor Evaluation**: These indicators effectively capture short-term and long-term market strength and provide strong signals for market trends[19] --- Factor Backtesting Results 1. Market Intrinsic Momentum Indicators - All four indicators showed upward trends in recent periods, aligning with the market's upward trajectory, indicating strong internal momentum supporting the index's rise[19]

Quantitative Models and Construction Methods - **Model Name**: AI Industry Rotation Model **Construction Idea**: The model uses full-spectrum price-volume fusion factors to score 32 primary industries and constructs a weekly rebalancing strategy by selecting the top 5 industries for equal-weight allocation [2][23][16] **Construction Process**: 1. **Industry Pool**: Includes 32 primary industries, excluding comprehensive and comprehensive finance sectors. Certain industries are split into subcategories (e.g., food and beverage split into food, beverage, and liquor) [23] 2. **Factor**: Full-spectrum price-volume fusion factor, derived from industry constituent stocks' factor scores [23][16] 3. **Strategy Rules**: - Select the top 5 industries with the highest scores on the last trading day of each week - Equal-weight allocation - Buy at the closing price of the first trading day of the following week - Weekly rebalancing, no transaction costs considered [23] **Evaluation**: The model leverages AI's feature extraction capabilities to fully explore patterns in multi-frequency price-volume data, complementing top-down strategies [16] - **Model Name**: AI Thematic Index Rotation Model **Construction Idea**: The model uses full-spectrum price-volume fusion factors to score 133 thematic indices and constructs a weekly rebalancing strategy by selecting the top 10 indices for equal-weight allocation [3][9][15] **Construction Process**: 1. **Index Pool**: Based on Wind's ETF fund classification, selects indices tracked by thematic ETFs, forming a pool of 133 thematic indices [9] 2. **Factor**: Full-spectrum price-volume fusion factor, derived from thematic index constituent stocks' factor scores [9][15] 3. **Strategy Rules**: - Select the top 10 indices with the highest scores on the last trading day of each week - Equal-weight allocation - Buy at the opening price of the first trading day of the following week - Weekly rebalancing, transaction costs set at 0.04% for both sides [9][15] **Evaluation**: The model effectively identifies high-performing thematic indices using AI-driven factor scoring [15] - **Model Name**: AI Concept Index Rotation Model **Construction Idea**: The model uses full-spectrum price-volume fusion factors to score 72 concept indices and constructs a weekly rebalancing strategy by selecting the top 10 indices for equal-weight allocation [11][15][32] **Construction Process**: 1. **Index Pool**: Selects 72 popular concept indices from Wind [15] 2. **Factor**: Full-spectrum price-volume fusion factor, derived from concept index constituent stocks' factor scores [15][32] 3. **Strategy Rules**: - Select the top 10 indices with the highest scores on the last trading day of each week - Equal-weight allocation - Buy at the opening price of the first trading day of the following week - Weekly rebalancing, transaction costs set at 0.04% for both sides [15][32] **Evaluation**: The model efficiently captures trends in concept indices using AI-driven factor scoring [32] - **Model Name**: AI CSI 1000 Enhanced Portfolio **Construction Idea**: The portfolio is constructed using full-spectrum fusion factors to enhance the CSI 1000 index [1][27][29] **Construction Process**: 1. **Factor**: Full-spectrum fusion factor, combining high-frequency deep learning factors and low-frequency multi-task factors [26][29] 2. **Portfolio Construction Rules**: - Stock weight deviation limit: 0.8 - Barra exposure limit: 0.3 - Weekly turnover rate capped at 30% - Weekly rebalancing, transaction costs set at 0.4% for both sides [29] **Evaluation**: The portfolio demonstrates strong tracking and enhancement capabilities relative to the CSI 1000 index [27] - **Model Name**: Text FADT_BERT Stock Selection Portfolio **Construction Idea**: The portfolio is based on the forecast_adjust_txt_bert factor, which upgrades text factors under earnings forecast adjustment scenarios [32][33][36] **Construction Process**: 1. **Factor**: Forecast_adjust_txt_bert factor, derived from text-based analysis of earnings forecast adjustments [32][33] 2. **Portfolio Construction Rules**: - Enhances the long-side base stock pool - Constructs a top 25 active quantitative stock selection portfolio [32][33] **Evaluation**: The portfolio effectively integrates text-based AI factors for stock selection [36] Model Backtesting Results - **AI Industry Rotation Model**: - Annualized return: 25.69% - Annualized excess return: 20.23% - Maximum drawdown of excess return: 12.43% - Excess Sharpe ratio: 1.96 - YTD return: 14.11% - YTD excess return: 0.14% [22] - **AI Thematic Index Rotation Model**: - Annualized return: 16.65% - Annualized excess return: 12.19% - Maximum drawdown of excess return: 16.55% - Excess Sharpe ratio: 0.96 - YTD return: 16.97% - YTD excess return: 6.87% [8] - **AI Concept Index Rotation Model**: - Annualized return: 23.67% - Annualized excess return: 12.20% - Maximum drawdown of excess return: 17.96% - Excess Sharpe ratio: 1.03 - YTD return: 23.94% - YTD excess return: 7.06% [13] - **AI CSI 1000 Enhanced Portfolio**: - Annualized return: 18.95% - Annualized excess return: 22.36% - Annualized tracking error: 6.04% - Maximum drawdown of excess return: 7.55% - Information ratio: 3.70 - Calmar ratio: 2.96 [30] - **Text FADT_BERT Stock Selection Portfolio**: - Annualized return: 39.73% - Annualized excess return: 31.34% - Maximum drawdown: 48.69% - Sharpe ratio: 1.38 - Calmar ratio: 0.82 [36]

Profit Trends - In June, industrial enterprises' profits declined by 4.3% year-on-year, a slight improvement from May's 9% drop, primarily driven by a significant rebound in automotive profits[1] - Excluding the automotive sector, June's industrial profits fell by 9.1%, worsening from May's -7.1%[1] - The profit growth rate for industrial enterprises in Q2 dropped to -3.7%, down from 0.8% in Q1, indicating the impact of tariff policies on profits and orders[1] Price and Revenue Insights - The Producer Price Index (PPI) in June also showed a decline of 3.6%, compared to May's -3.3%[1] - Industrial enterprises' revenue growth slowed to 1.7% in Q2 from 3.4% in Q1, with June's revenue growth slightly improving to 1.6% from May's 0.8%[1] Sector Performance - Upstream industries saw a profit decline of 36.3% year-on-year in Q2, with coal mining profits worsening from -56.8% in May to -63% in June, contributing approximately 5.2 percentage points to the overall profit decline[3] - In contrast, oil and gas extraction and black metal mining showed recovery, with profits improving from -23.8% and -46.2% in May to -17% and 14.9% in June, respectively[3] Ownership Structure - In June, profits for state-owned and foreign enterprises improved, with state-owned enterprises rising from -18.1% in May to -8.3%, and foreign enterprises increasing from -7.3% to 11%[5] - Private enterprises, however, saw a decline in profit growth from 0.8% in May to -4.9% in June[5] Economic Outlook - The "anti-involution" policies are expected to support prices and profits in certain sectors in the second half of the year, although uncertainties remain regarding exports due to tariff disruptions[2] - The real estate cycle continues to show weakness, with property sales in major cities declining by 20% year-on-year in July, worsening from an 8.4% drop in June[3]

Investment Rating - The report maintains an "Overweight" rating for the oil and gas sector [5]. Core Views - The demand for oil has been supported by the traditional peak season in the Northern Hemisphere, with oil prices remaining relatively high since July [1][11]. - The report indicates that the actual tightness in the oil market may be greater than the IEA's supply-demand balance suggests, highlighting the importance of OPEC+'s production adjustments and seasonal consumption trends [1][4]. - Long-term, high-dividend energy companies with the ability to increase production and reduce costs, as well as those with growing natural gas operations, are expected to present investment opportunities [4][66]. Demand Side Summary - Global oil demand growth slowed significantly in Q2 2025, dropping from 1.1 million barrels per day in Q1 to 0.55 million barrels per day in Q2 [2][17]. - China's commercial crude oil inventory saw a record quarterly increase, which is crucial for long-term energy security [2][23]. - The traditional peak season for travel and electricity demand in Q3 is expected to further tighten the market, with historical data indicating a combined increase of 900,000 barrels per day in oil demand for power generation from May to August [2][23]. Supply Side Summary - Global oil supply is projected to increase by 2.1 million barrels per day in 2025 and 1.3 million barrels per day in 2026, with OPEC+ accelerating production [3][38]. - In June, oil exports from the Gulf region surged, driven by concerns over supply disruptions due to geopolitical tensions [3][43]. - OPEC+ has raised its production targets for August, indicating a significant reduction in voluntary production cuts implemented since 2023, which could lead to an oversupply in the market [3][43][66]. Key Recommendations - The report recommends investing in high-dividend energy companies with the capacity to increase production and reduce costs, specifically highlighting China National Offshore Oil Corporation (CNOOC) and China Petroleum [4][66]. - The forecast for Brent crude oil prices is set at $68 and $62 per barrel for 2025 and 2026, respectively, with Q3 and Q4 2025 prices expected to be $68 and $63 per barrel [4][66].

Investment Rating - The investment rating for Sands China Ltd. is maintained as "Buy" with a target price of HKD 21.20 [1][10]. Core Views - The recovery of Gross Gaming Revenue (GGR) for Sands China is lagging behind the industry average, with GGR at USD 1.72 billion, reflecting a year-on-year increase of 0.3% and a quarter-on-quarter increase of 6.5%, recovering to 81% of the levels seen in Q2 2019, compared to the industry average of 83% [1][4]. - The company is overly reliant on hotel hardware appeal, which has affected performance due to insufficient customer incentives [1][4]. - The management is optimistic about the refurbishment of The Londoner, which is expected to enhance business through improved customer incentive mechanisms [1][5]. - The parent company has increased its stake in Sands China to 73.4% and plans to gradually restore dividends to pre-pandemic levels, with a projected total dividend of HKD 0.50 in 2025 [1][10]. Summary by Sections Financial Performance - Sands China's adjusted EBITDA for Q2 2025 was USD 566 million, a year-on-year increase of 1% and a quarter-on-quarter increase of 6%, recovering to 74% of the levels seen in Q2 2019 [5]. - The company’s revenue forecast for 2025-2027 has been adjusted downwards to HKD 578 billion, HKD 622 billion, and HKD 653 billion respectively [10]. Market Dynamics - The recovery of VIP and mass market segments is below industry standards, with VIP gross revenue at USD 156 million, recovering to only 28% of 2019 levels, while mass market revenue is at USD 1.376 billion, recovering to 99% of 2019 levels [4][10]. - The company has seen strong visitor traffic to Macau, but increased market competition and insufficient customer incentives have hindered performance [4][6]. Non-Gaming Initiatives - Sands China is expanding its non-gaming offerings, including hosting concerts and events to attract diverse customer demographics, with notable performances scheduled for the second half of 2025 [5][32]. - The introduction of various entertainment events is expected to enhance customer engagement and drive GGR recovery [6][32].

Investment Rating - The investment rating for the company is maintained as "Buy" with a target price of RMB 8.35 [1][3]. Core Insights - The company reported a revenue of RMB 6.7 billion for 1H25, a year-over-year decrease of 11.20%, while the net profit attributable to shareholders was RMB 502 million, reflecting a year-over-year increase of 20.85% [1]. - The second quarter revenue was RMB 3.39 billion, down 23.27% year-over-year but up 2.53% quarter-over-quarter, with net profit reaching RMB 278 million, a year-over-year increase of 25.30% and a quarter-over-quarter increase of 23.73% [1]. - The increase in profitability is attributed to rising metal prices and improved capacity utilization in the resource recycling segment [1]. - The company plans to repurchase shares worth RMB 100-150 million, indicating confidence in future business growth and intrinsic value [2]. Summary by Sections Financial Performance - In 1H25, the resource recycling segment's revenue decreased by 8.3% to RMB 5.205 billion, while the gross margin improved by 5 percentage points to 13.41% [1]. - The engineering segment's revenue fell by 40.04% to RMB 592 million, with a gross margin decrease of 4.26 percentage points to 12.35% [1]. Cash Flow and Share Buyback - The operating cash flow increased by 214% year-over-year to RMB 347 million, primarily due to improved operational performance and credit policy optimization [2]. - The company reported a net inflow of RMB 133 million from investment activities, contrasting with a net outflow of RMB 634 million in 1H24 [2]. Earnings Forecast - The forecast for net profit attributable to shareholders for 2025 is adjusted to RMB 712.62 million, with EPS estimates of RMB 0.47 [3]. - The company is expected to achieve a PE ratio of 17.8x for 2025, leading to a target price of RMB 8.35, up from the previous estimate of RMB 7.60 [3].

Investment Rating - The investment rating for the company is maintained as "Buy" with a target price of 360,000 KRW [3][12]. Core Insights - The company reported revenue and profit that exceeded expectations, with a significant increase in HBM sales and pricing [8][10]. - The company is positioned to benefit from the growing demand for high-end HBM products, particularly with major clients like NVIDIA [29][31]. - The report highlights the uncertainty surrounding tariffs imposed by the U.S. government on products from Japan and Korea, which could impact future operations [11]. Financial Performance - For Q2 2025, the company reported revenue of 22.23 trillion KRW, a year-on-year increase of 35% and a quarter-on-quarter increase of 26%, surpassing Bloomberg consensus estimates [8]. - Operating profit for the same period was 9.21 trillion KRW, reflecting a year-on-year increase of 68% and a quarter-on-quarter increase of 24% [8]. - The gross margin was reported at 53.9%, while the operating margin was 41.4% [8]. Product Performance - The company has seen strong growth in HBM sales, with expectations to double HBM sales in 2025 [9]. - The DRAM segment reported revenue of 17.12 trillion KRW for Q2 2025, a year-on-year increase of 58% and a quarter-on-quarter increase of 21% [10]. - NAND revenue for Q2 2025 was 4.67 trillion KRW, showing a year-on-year decrease of 8% but a quarter-on-quarter increase of 47% [10]. Market Position - The company has surpassed Samsung in DRAM market share, achieving 39% compared to Samsung's 36% [10]. - The report indicates that the company is one of only three suppliers in the HBM market, which positions it favorably against competitors like Micron and Samsung [31]. Valuation and Forecast - The target price has been raised to 360,000 KRW, reflecting a price-to-book ratio of 1.8x for FY26E [12][30]. - Revenue estimates for 2025, 2026, and 2027 have been adjusted to 98 trillion KRW, 120 trillion KRW, and 132 trillion KRW respectively, while net profit estimates have been slightly increased [30].