累计新增借款占比高达67% 西南证券拟定增募资60亿元背后，是公司巨额增长的有息负债。 根据公司近期发布的公告，截至2024年12月31日，西南证券经审计合并口径的净资产为258.11亿元，借款余额为356.37亿元。截至2025年12月31日，公司借 款余额为531.12亿元，累计新增借款金额为174.75亿元，累计新增借款占上年末净资产的比例为 67.7%，超过50%。 炒股就看金麒麟分析师研报，权威，专业，及时，全面，助您挖掘潜力主题机会！ 出品：新浪财经上市公司研究院 作者：图灵 春节前最后一个交易日，西南证券发布定增预案，拟募资不超过60亿元。 60亿元定增背后，是西南证券大幅增长的借款。截至2025年12月31日，公司借款余额高达531亿元；累计新增借款余额占上年末净资产的比例高达67.7%。 西南证券新增的借款主要是期限较短的卖出回购金融资产款以及收益凭证，但在资产端，公司新增的资产主要是交易性金融资产（主要是自营投资业务）以 及融出资金（主要包括两融业务），是否属于"短债长用"待考。 此次定增，西南证券计划将募资用于四大细分业务以及子公司投入、信息技术与合规风控建设、偿债补流等，可谓"雨露均沾 ...

Core Viewpoint - The article discusses various grassroots financial education activities organized by multiple securities firms during the Spring Festival, aiming to enhance investor awareness and participation in financial literacy while addressing the rise of illegal financial activities during this period [1][2]. Group 1: Financial Education Activities - Securities firms have organized community events such as Spring Festival garden parties, where residents engage in games like financial knowledge quizzes and anti-fraud knowledge contests to learn about financial concepts [2][4]. - Activities include interactive elements like writing Spring Festival couplets and financial knowledge spinning wheels, making the learning process enjoyable and culturally relevant [4][5]. - Over a dozen securities firms, including Dongwu Securities and Huabao Securities, have launched similar festive educational activities targeting grassroots communities since late January [4]. Group 2: Innovative Approaches - Some firms, like Kaisheng Securities, have integrated traditional crafts with financial education, creating themed events that promote anti-fraud awareness and rational investment concepts through hands-on activities [5]. - The use of MBTI personality tests in investment profiling has been introduced by firms like Zhongxin Jianshe Securities, allowing investors to receive personalized investment reports based on their preferences and behaviors [7][8]. Group 3: Online and Offline Integration - Firms are leveraging both online and offline channels to maximize the reach and impact of their educational initiatives, ensuring comprehensive coverage of their activities [9]. - Zhongxin Jianshe Securities has developed a mini-program for investment education, enhancing accessibility and engagement through digital platforms [7][9]. Group 4: Challenges and Future Directions - Despite the success of these initiatives, there are challenges in making financial education sustainable and effective, particularly in adapting content to meet the diverse needs of different community demographics [10][12]. - Suggestions for improvement include establishing fixed educational service points in community centers and enhancing collaboration among various stakeholders to create a more integrated approach to financial education [12].

Group 1 - The issuance of bank wealth management products has decreased recently, with a total of 633 new products launched last week, a decrease of 45 products compared to the previous week [1][8] - The performance benchmarks for newly issued products have declined, with both open-ended and closed-end products experiencing a drop [2][9] - The average performance benchmark for open-ended products was 1.79%, down 0.05 percentage points, while closed-end products had an average benchmark of 2.35%, down 0.03 percentage points [3][10] Group 2 - As of February 11, there were 40,898 existing wealth management products in the market, with fixed-income products making up 93.05% of the total [4][11] - The average annualized yield for existing open-ended fixed-income wealth management products (excluding current management) was 2.61%, down 0.68 percentage points from the previous month [4][11] Group 3 - Ningyin Wealth Management successfully participated in the IPO of the commercial aerospace company "Electric Science Blue Sky," with six products allocated shares, achieving a first-day closing increase of 596% [7][14] - The company has participated in 45 new stock subscriptions with a high allocation rate of 91%, accumulating over 18 million yuan in allocated funds [7][14] - Wealth management funds are increasingly participating in stock subscriptions as a means to achieve excess returns and expand into the equity market [7][14][15]

Group 1 - The report outlines a grid trading strategy that capitalizes on price fluctuations rather than predicting market trends, making it suitable for volatile markets [4][14] - Characteristics of suitable grid trading targets include being exchange-traded, having stable long-term trends, low transaction costs, good liquidity, and high volatility, with equity ETFs being particularly appropriate [4][14] - The report highlights specific ETFs for grid trading, including the Huashan Software ETF, which focuses on domestic software development and AI commercialization opportunities [5][15] Group 2 - The report discusses the E Fund Robotics ETF, which benefits from the dual drivers of smart manufacturing upgrades and accelerated penetration of the robotics industry, with significant growth in industrial and service robot production expected [5][18] - The E Fund Securities and Insurance ETF is noted for its short-term catalysts from January's strong market performance and long-term policy benefits from the "Financial Power" strategy and ongoing capital market reforms [6][20] - The report emphasizes the gaming ETF, which is supported by the normalization of game license approvals and the transformative impact of AI technology on the gaming industry, leading to significant revenue growth in both domestic and international markets [8][23]

Core Viewpoint - The article discusses the performance and potential of ETF grid strategies, particularly focusing on the securities and insurance sectors, as well as the gaming industry, highlighting favorable market conditions and regulatory support for growth [3][4][8]. Group 1: Securities and Insurance ETF - In January 2026, A-shares experienced 20 trading days, with the trading volume exceeding 30 trillion yuan on 8 days, indicating a strong "spring rally" market, benefiting brokerage and margin financing businesses [3]. - Multiple insurance companies reported strong sales during the "opening red" period, particularly in dividend insurance, which serves as a short-term catalyst for the industry [3]. - The article references a significant article by Xi Jinping emphasizing the construction of a "financial power" strategy, which aligns with ongoing capital market reforms, creating a favorable policy environment for the securities and insurance sectors [4]. - Comprehensive reforms, including the full registration system and the development of the "insurance + pension" third pillar, are expected to guide the long-term high-quality development of the securities and insurance industries [4]. Group 2: Gaming ETF - In January 2026, 177 domestic online games and 5 imported games were approved, with a total of 1,771 game licenses issued in 2025, marking a 20% increase from 2024 and the highest number in nearly 7 years [8]. - The domestic market for self-developed games generated actual sales revenue of 291.095 billion yuan in 2025, reflecting an 11.64% year-on-year increase, while overseas sales reached 20.455 billion USD, up 10.23% year-on-year [8]. - The gaming industry is undergoing an AI-driven transformation, with AI applications in game development and operations, which are expected to lower costs and enhance efficiency, thus sharing the benefits of industry innovation [8].

Report Industry Investment Rating - Not mentioned in the report Core Viewpoints - By leveraging ETFs, it is convenient to transform quantitative models or subjective viewpoints into practical investment strategies. The report presents several ETF - based strategy indices and tracks their performance and holdings on a weekly basis [12] Summary by Relevant Catalog 1. ETF Strategy Index Tracking - **Overall Performance**: The table shows the performance of various ETF strategy indices last week. The "Huabao Research Small and Large - Cap Rotation ETF Strategy Index" had a weekly return of - 2.57%, a benchmark return of - 1.72%, and an excess return of - 0.85%. The "Huabao Research Quantitative Fire - Wheel ETF Strategy Index" had a weekly return of - 2.71%, a benchmark return of - 1.72%, and an excess return of - 0.99%. The "Huabao Research Quantitative Balance Art ETF Strategy Index" had a weekly return of - 0.44%, a benchmark return of - 1.33%, and an excess return of 0.90%. The "Huabao Research SmartBeta Enhanced ETF Strategy Index" had a weekly return of - 5.17%, a benchmark return of - 1.72%, and an excess return of - 3.45%. The "Huabao Research Hot - Spot Tracking ETF Strategy Index" had a weekly return of - 4.02%, a benchmark return of - 1.56%, and an excess return of - 2.46%. The "Huabao Research Bond ETF Duration Strategy Index" had a weekly return of 0.14%, a benchmark return of 0.14%, and an excess return of 0.00% [13] 1.1 Huabao Research Small and Large - Cap Rotation ETF Strategy Index - **Strategy**: It uses multi - dimensional technical indicator factors and a machine - learning model to predict the return difference between the Shenwan Large - Cap Index and the Shenwan Small - Cap Index. The model outputs signals weekly to predict the strength of the indices in the next week and determines holdings accordingly to obtain excess returns relative to the market [14][3] - **Performance**: As of February 6, 2026, the excess return since 2024 was 27.39%, the excess return in the past month was 1.49%, and the excess return in the past week was - 0.85%. The recent week's return was - 2.57%, the recent month's return was 0.06%, and the return since 2024 was 66.67%. The benchmark (CSI 800) had a recent - week return of - 1.72%, a recent - month return of - 1.43%, and a return since 2024 of 39.28% [14][18] - **Holdings**: As of February 6, 2026, it held 50% of the "CSI 500ETF" (fund code 159922.SZ) and 50% of the "CSI 1000ETF" (fund code 512100.SH) [18] 1.2 Huabao Research SmartBeta Enhanced ETF Strategy Index - **Strategy**: It uses price - volume indicators to time self - built Barra factors and maps timing signals to ETFs based on their exposures to 9 major Barra factors to achieve returns exceeding the market. The selected ETFs cover mainstream broad - based index ETFs and some style and strategy ETFs [17][18] - **Performance**: As of February 6, 2026, the excess return since 2024 was 14.21%, the excess return in the past month was - 3.36%, and the excess return in the past week was - 3.45%. The recent week's return was - 5.17%, the recent month's return was - 4.79%, and the return since 2024 was 53.50%. The benchmark (CSI 800) had a recent - week return of - 1.72%, a recent - month return of - 1.43%, and a return since 2024 of 39.28% [18][19] - **Holdings**: As of February 6, 2026, it held 25.28% of the "Western Capital Growth Enterprise Market Large - Cap ETF" (fund code 159814.SZ), 25.10% of the "Huaxia Science and Technology Innovation Comprehensive Index ETF" (fund code 589000.SH), 24.82% of the "Science and Technology Innovation 50ETF" (fund code 588000.SH), and 24.80% of the "E Fund Science and Technology Innovation and Growth Enterprise Market ETF" (fund code 159781.SZ) [18][21] 1.3 Huabao Research Quantitative Fire - Wheel ETF Strategy Index - **Strategy**: It starts from a multi - factor perspective, including the grasp of medium - and long - term fundamental dimensions, the tracking of short - term market trends, and the analysis of the behaviors of various market participants. It uses valuation and crowding signals to indicate industry risks and multi - dimensionally digs potential sectors to obtain excess returns relative to the market [21][4] - **Performance**: As of February 6, 2026, the excess return since 2024 was 48.59%, the excess return in the past month was 5.45%, and the excess return in the past week was - 0.99%. The recent week's return was - 2.71%, the recent month's return was 4.02%, and the return since 2024 was 87.87%. The benchmark (CSI 800) had a recent - week return of - 1.72%, a recent - month return of - 1.43%, and a return since 2024 of 39.28% [21][23] - **Holdings**: As of February 6, 2026, it held 20.66% of the "E Fund Securities and Insurance ETF" (fund code 512070.SH), 20.05% of the "Steel ETF" (fund code 515210.SH), 19.97% of the "Penghua Petroleum ETF" (fund code 159697.SZ), 19.66% of the "Electronic ETF" (fund code 159997.SZ), and 19.65% of the "Chemical Industry ETF" (fund code 159870.SZ) [26] 1.4 Huabao Research Quantitative Balance Art ETF Strategy Index - **Strategy**: It uses a multi - factor system including economic fundamentals, liquidity, technical aspects, and investor behavior factors to build a quantitative timing system for trend analysis of the equity market. It also establishes a prediction model for the market's small - and large - cap styles to adjust the equity market position distribution and comprehensively obtains excess returns relative to the market through timing and rotation [25] - **Performance**: As of February 6, 2026, the excess return since 2024 was - 8.96%, the excess return in the past month was 2.38%, and the excess return in the past week was 0.90%. The recent week's return was - 0.44%, the recent month's return was - 0.04%, and the return since 2024 was 26.37%. The benchmark (CSI 300) had a recent - week return of - 1.33%, a recent - month return of - 2.42%, and a return since 2024 was 35.34% [25][26] - **Holdings**: As of February 6, 2026, it held 9.11% of the "10 - Year Treasury Bond ETF" (fund code 511260.SH), 6.50% of the "500ETF Enhanced" (fund code 159610.SZ), 6.26% of the "CSI 1000ETF" (fund code 512100.SH), 32.94% of the "Guotai CSI 300 Enhanced ETF" (fund code 561300.SH), 22.64% of the "Policy - Financial Bond ETF" (fund code 511520.SH), and 22.55% of the "Haifutong Short - Term Financing ETF" (fund code 511360.SH) [28] 1.5 Huabao Research Hot - Spot Tracking ETF Strategy Index - **Strategy**: It uses strategies such as market sentiment analysis, industry major event tracking, investor sentiment and professional opinions, policy and regulatory changes, and historical deduction to track and dig hot - spot index target products in a timely manner, constructing an ETF portfolio that can capture market hotspots in time to provide investors with references for short - term market trends and help them make more informed investment decisions [28][5] - **Performance**: As of February 6, 2026, the excess return in the past month was 2.05%, and the excess return in the past week was - 2.46%. The recent week's return was - 4.02%, the recent month's return was 1.15%. The benchmark (CSI All - Share Index) had a recent - week return of - 1.56% and a recent - month return of - 0.90% [28][31] - **Holdings**: As of February 6, 2026, it held 41.13% of the "Huitianfu Non - Ferrous Metals ETF" (fund code 159652.SZ), 23.13% of the "Bosera Hong Kong Stock Dividend ETF" (fund code 513690.SH), 18.44% of the "E Fund Hong Kong - Stock Connect Pharmaceutical ETF" (fund code 513200.SH), and 17.30% of the "Haifutong Short - Term Financing ETF" (fund code 511360.SH) [31][32] 1.6 Huabao Research Bond ETF Duration Strategy Index - **Strategy**: It uses bond market liquidity indicators and price - volume indicators to screen effective timing factors and predicts bond yields through machine learning. When the expected yield is below a certain threshold, it reduces the long - duration positions in the bond investment portfolio to improve the portfolio's long - term returns and drawdown control ability [32] - **Performance**: As of February 6, 2026, the excess return in the past month was 0.29%, and the excess return in the past week was 0.00%. The recent week's return was 0.14%, the recent month's return was 0.76%, the return since 2024 was 9.76%, and the return since its establishment was 23.95%. The benchmark (ChinaBond Aggregate Index) had a recent - week return of 0.14%, a recent - month return of 0.47%, a return since 2024 of 3.26%, and a return since its establishment of 7.55% [32][33] - **Holdings**: As of February 6, 2026, it held 50.03% of the "10 - Year Treasury Bond ETF" (fund code 511260.SH), 24.99% of the "Policy - Financial Bond ETF" (fund code 511520.SH), and 24.98% of the "5 - to 10 - Year Treasury Bond ETF" (fund code 511020.SH) [32][35]

Quantitative Models and Construction Methods 1. Model Name: "Risk Preference-Concentration-Turnover" Three-Dimensional Label Classification System - **Model Construction Idea**: The model aims to classify multi-asset fund advisory products based on three dimensions: risk preference, concentration, and turnover rate, to better understand their risk-return characteristics and performance differentiation[3][32] - **Model Construction Process**: - **Risk Preference**: Classified based on the proportion of income-generating assets and growth assets in the portfolio. If income-generating assets exceed 70%, it is classified as debt-oriented; if growth assets exceed 70%, it is equity-oriented; otherwise, it is balanced[34] - **Concentration**: Measured using the Herfindahl-Hirschman Index (HHI), calculated as $ \sum_{i} w_{i}^{2} $, where $w_{i}$ represents the weight of each asset class. Thresholds are set as follows: HHI > 0.5 is high concentration, HHI < 0.25 is low concentration, and values in between are medium concentration[34] - **Turnover Rate**: Measures the timing adjustment ability of multi-asset fund advisory products at the asset class level. Annualized one-sided turnover rate is used, with thresholds defined as follows: turnover rate > 2 is high turnover, < 1 is low turnover, and values in between are medium turnover[34] - **Model Evaluation**: The model effectively captures the heterogeneity in multi-asset fund advisory products and provides insights into their risk-return characteristics and strategic differences[3][34] --- Model Backtesting Results 1. "Risk Preference-Concentration-Turnover" Three-Dimensional Label Classification System - **Risk Preference**: - Equity-oriented products: 2025 annualized return 18.5%, 2024 annualized return 10.5%, 2023 annualized return -1.0%[37][39] - Debt-oriented products: 2025 annualized return 7.4%, 2024 annualized return 5.9%, 2023 annualized return 3.9%[37][39] - Balanced products: 2025 annualized return 15.7%, 2024 annualized return 8.8%, 2023 annualized return -4.7%[37][39] - **Concentration**: - Low concentration (HHI < 0.25): 2025 annualized return 17.7%, 2024 annualized return 8.2%, 2023 annualized return 0.4%[37][39] - Medium concentration (0.25 ≤ HHI ≤ 0.5): 2025 annualized return 13.0%, 2024 annualized return 6.9%, 2023 annualized return -4.0%[37][39] - High concentration (HHI > 0.5): 2025 annualized return 7.8%, 2024 annualized return 6.9%, 2023 annualized return 3.9%[37][39] - **Turnover Rate**: - Low turnover (< 1): 2025 annualized return 15.6%, 2024 annualized return 8.8%, 2023 annualized return 1.7%[37][39] - Medium turnover (1 ≤ turnover ≤ 2): 2025 annualized return 10.6%, 2024 annualized return 7.3%, 2023 annualized return 0.5%[37][39] - High turnover (> 2): 2025 annualized return 11.2%, 2024 annualized return 7.6%, 2023 annualized return -5.4%[37][39] --- Quantitative Factors and Construction Methods 1. Factor Name: Brinson Attribution Model - **Factor Construction Idea**: The model decomposes the excess return of multi-asset fund advisory products into two components: allocation return and selection return, to evaluate the sources of excess returns[42][46] - **Factor Construction Process**: - **Allocation Effect**: Measures the timing and allocation ability of fund managers across major asset classes. The formula is: $$ R_{allocation} = \sum_{i} (w_{i}^{actual} - w_{i}^{benchmark}) \times r_{i}^{asset} $$ where $w_{i}^{actual}$ is the actual weight of asset $i$, $w_{i}^{benchmark}$ is the benchmark weight, and $r_{i}^{asset}$ is the return of asset $i$[42][46] - **Selection Effect**: Reflects the ability to select superior funds within each asset class. The formula is: $$ R_{selection} = R_{excess} - R_{allocation} $$ where $R_{excess}$ is the total excess return relative to the benchmark[42][46] - **Factor Evaluation**: The model provides a clear decomposition of excess returns, helping to identify whether returns are driven by strategic asset allocation or fund selection[42][46] --- Factor Backtesting Results 1. Brinson Attribution Model - **Equity-Oriented Products**: - Example: "Guotai Global Allocation" achieved 2025 allocation return of 10.5% and selection return of 6.3%[48][49] - Example: "招商海外掘金" achieved 2025 allocation return of -0.8% and selection return of 14.5%[48][49] - **Debt-Oriented Products**: - Example: "嘉实百灵全天候策略" achieved 2025 allocation return of 3.8% and selection return of 0.5%[56][58] - Example: "全球固收+" achieved 2025 allocation return of 2.6% and selection return of 1.3%[56][58] - **Balanced Products**: - Example: "时光旅行者" achieved 2025 allocation return of 15.6% and selection return of -10.3%[65][66] - Example: "绘盈长投计划" achieved 2023 allocation return of 10.1%, providing a strong safety net during a bear market[65][66]

2月5日，国投白银LOF（161226）开盘再度跌停，这已是该基金自2月2日复牌以来连续第四个交易日开盘即跌停。各大平台基金评论区充斥着投资者的愤怒 声讨，其中被"闷杀"的投资者不在少数，这些之前并不了解LOF基金操作规则的投资者，多是被自媒体的"套利教程"吸引而来。 其中最典型的是一个名叫"猫笔叨拓展笔记"的自媒体博主（小号"猫笔刀啊"），自去年12月起就在多个平台上发布名为"白银基金的套利教程"的系列文章， 文章中不仅详细指导如何在华宝智投APP进行"一拖六"账户绑定，还附带了VIP付费咨询群的二维码，其中干货最集中的一篇"猫笔刀说的白银基金怎么套 利"已经删除。 理财自媒体的套利狂欢 "一拖六"是指通过一个主账户关联多个子账户（通常为3个深圳A股股东账户和3个深圳封闭式基金账户），通过这些账户同时进行LOF基金的申购、赎回或 买卖操作来实现套利。 在华宝证券APP上，类似操作确实有其技术可行性，有投资者登录华宝证券交易APP，在"账户管理"中找到"多账户关联"功能，按照提示将主账户与最多6个 子账户进行关联。一位投资者在社区分享了自己"组装拖拉机"的过程：通过华宝证券APP的"业务办理-股东账户管理"功 ...

Core Viewpoint - The article discusses the valuation crisis faced by the Guotou Ruijin Silver Fund, highlighting the extreme volatility in the international silver market and the implications for fund valuation methods, disclosure timeliness, and investor trust [4]. Group 1: Valuation Fluctuations - The fund experienced a dramatic net value drop of 31.5% on February 2, marking a record in public fund history, which was not solely due to market conditions but a one-time correction of accumulated risks [6]. - The fund's valuation is based on the Shanghai Futures Exchange silver futures settlement price, but the recent historic drop in international silver prices necessitated an adjustment to avoid misleading net asset values [6][12]. - On January 30, COMEX silver futures fell by 25.5%, creating a significant discrepancy between domestic and international prices due to the trading limits on the domestic market [6]. Group 2: Communication and Disclosure Issues - Guotou Ruijin's failure to announce the valuation adjustment in advance led to strong investor criticism regarding their right to information and the timeliness of disclosures [8]. - The fund's management explained that the extreme market conditions and liquidity issues prevented them from predicting price movements accurately, which justified the lack of prior announcement [9]. - Concerns arose that an early announcement could have been misinterpreted as an attempt to prevent redemptions, potentially causing panic among investors [9]. Group 3: Valuation Logic and Investor Trust - The valuation adjustment was intended to protect investor interests, but the lack of clarity on the conditions triggering such adjustments raised fundamental questions about the fund's valuation logic [11]. - The management prioritized liquidity over tracking international silver prices, which led to further investor skepticism when the fund did not adjust valuations in line with rising prices [12]. - The incident highlighted the need for improved communication and transparency from fund companies, especially during extreme market conditions, to maintain investor trust [18]. Group 4: Market Reactions and Social Media Impact - Misinformation regarding the need for prior announcements of valuation changes spread on social media, leading to investor confusion and potential legal actions against the fund [15]. - The fund had previously attracted speculative interest on social media platforms, which amplified negative sentiment when the valuation adjustment occurred [16]. - The article emphasizes the importance of clear communication and understanding of the product's nature, as well as the risks associated with speculative trading in volatile markets [19].

Core Viewpoint - The recent performance of Guotou Silver LOF (161226.SZ) has raised significant concerns among investors, leading to a three-day trading halt and a 10% daily drop, attributed to valuation adjustments by Guotou Ruijin Fund Management Company [2][4]. Group 1: Fund Performance and Market Reaction - Guotou Silver LOF is the only public fund in China tracking silver futures, and on February 4, 2026, it experienced a one-day net value drop exceeding 30%, marking a record decline for public funds [3][4]. - As of February 3, 2026, the fund's net value was 2.3238 yuan, with a daily growth rate of 3.31%, while the previous day saw a net value of 2.2494 yuan, reflecting a staggering daily decline of 31.50% [4][12]. - The fund's market price on February 4 was 3.825 yuan, significantly lower than its previous market price of 4.722 yuan, indicating a substantial premium risk for investors [4][5]. Group 2: Valuation Adjustment and Investor Concerns - Guotou Ruijin announced a valuation adjustment for the fund due to significant fluctuations in international silver prices, which diverged from domestic market prices, aiming to protect investors' interests [5][6]. - Investors have raised questions regarding the lack of prior announcement about the valuation adjustment, particularly why it was made only after a price drop rather than during price increases [5][6]. - The company justified the adjustment by stating that the international silver market's pricing is crucial for accurately reflecting the fund's underlying asset value, especially during abnormal market conditions [5][6]. Group 3: Arbitrage Opportunities and Market Dynamics - The incident has highlighted arbitrage opportunities within the LOF structure, where discrepancies between market prices and net asset values can be exploited [10][11]. - Prior to the trading halt, the market price of Guotou Silver LOF was significantly higher than its net value, creating a situation ripe for arbitrage [10][11]. - Various social media platforms have discussed arbitrage strategies related to LOF funds, raising concerns about potential regulatory violations if brokers collaborate with influencers [11].