1月14日，烽火通信涨5.03%，截至发稿，报46.55元/股，成交82.68亿元，换手率14.79%，总市值632.23 亿元。烽火通信股价已经连续5天上涨，区间累计涨幅25.62%。 资料显示，烽火通信科技股份有限公司位于湖北省武汉市东湖新技术开发区高新四路6号，成立日期 1999年12月25日，上市日期2001年8月23日，公司主营业务涉及网络信息安全产品和移动信息化产品的 研发、生产和销售。主营业务收入构成为：通信系统设备78.51%，光纤线缆18.02%，数据网络产品 1.98%，其他(补充)1.49%。 从基金十大重仓股角度 数据显示，富国基金旗下1只基金重仓烽火通信。富国中证科技50策略ETF（515750）三季度减持6.38 万股，持有股数77.47万股，占基金净值比例为2.67%，位居第七大重仓股。根据测算，今日浮盈赚取约 172.76万元。连续5天上涨期间浮盈赚取700.32万元。 富国中证科技50策略ETF（515750）成立日期2019年11月15日，最新规模7.98亿。今年以来收益 9.62%，同类排名833/5520；近一年收益58.68%，同类排名998/4203；成立以来收益9 ...

Group 1: Macro Timing Strategy - The macro timing strategy has an annualized return of 7.67% as of October 31, 2025, with a Sharpe ratio of 1.45 and a Calmar ratio of 1.67, indicating a maximum drawdown of -4.60% [2][4][5] - The latest portfolio allocation includes 7.01% in CSI 300 ETF, 7.99% in CSI 500 ETF, 55.94% in government bond ETF, 11.63% in soybean meal ETF, 5.02% in non-ferrous ETF, 7.40% in gold ETF, and 5.00% in currency ETF, with no allocation to S&P 500 ETF and corporate bond ETF [7][8] Group 2: Momentum Strategy - The momentum strategy has an annualized return of 18.25% since January 2020, with a Sharpe ratio of 0.88 and a Calmar ratio of 0.64, experiencing a maximum drawdown of -28.72% [9][10] - The latest portfolio allocation includes 27.01% in Huatai-PB CSI Telecom Theme ETF, 24.92% in Fuguo CSI Tourism Theme ETF, 21.52% in Xinhua CSI Cloud Computing 50 ETF, 16.38% in Huatai-PB CSI Smart Car ETF, and 8.17% in Huaxia CSI Artificial Intelligence ETF [13][14] Group 3: Sector Rotation Strategy - The sector rotation strategy has an annualized return of 10.00% since 2020, with an excess return of 7.27% relative to CSI 300, and a maximum drawdown of -42.98% [15] - The latest portfolio includes home appliance ETF, green power ETF, steel ETF, new energy vehicle ETF, financial ETF, and agricultural ETF, while excluding non-ferrous metals ETF and transportation ETF [18][19] Group 4: Copula-Based Second-Order Stochastic Dominance Strategy - The Copula-based second-order stochastic dominance strategy has an annualized return of 14.41% since January 2020, with a Sharpe ratio of 0.68 and a maximum drawdown of -42.62% [20][24] - The latest portfolio allocation includes 5.00% in Huaxia CSI Petrochemical Industry ETF, 85.00% in Fuguo CSI 800 Bank ETF, 5.00% in Fuguo CSI All-Index Securities Company ETF, and 5.00% in Bosera CSI Oil and Gas Resources ETF [23][25] Group 5: Quantile Random Forest Technology ETF Allocation Strategy - The quantile random forest technology ETF allocation strategy has an annualized return of 13.54% since 2020, with a Sharpe ratio of 0.76 and a maximum drawdown of -29.89% [26] - The latest portfolio allocation consists of 95.63% in technology ETFs, including 4.78% in Jiahua National Communication ETF, 4.78% in Tianhong CSI Photovoltaic Industry ETF, 4.78% in Huabao CSI Military Industry ETF, 76.51% in Ping An CSI Consumer Electronics Theme ETF, and 4.78% in Fuguo CSI Technology 50 Strategy ETF [29][30]

Group 1: Report Overview - The report focuses on the construction methods and performance of various ETF portfolios in November 2025, including macro-based, macro + momentum, core - satellite, and trinity style rotation portfolios [2] Group 2: ETF Portfolio Construction Methods Based on Macro Approach - Calculate macro - sensitivity of indices tracked by broad - based, industry - themed, and Smart Beta ETFs according to economic, liquidity, and credit variables, and select ETFs monthly. Also consider adding momentum indicators. Traditional cyclical industries are suitable for economic up - periods, TMT for weak - economic but liquid - abundant times, and consumption benefits from credit expansion. Three ETF portfolios are constructed and rebalanced monthly [5] Trinity Style Rotation - Build a mid - to long - term style rotation model centered on macro - liquidity, compared with the CSI 300 index. Combine three models (growth/value, market - cap, and quality) to get 8 style preference results, then screen target - style - exposed ETFs with controlled industry exposure and set allocation limits [6] Group 3: Macro Industry Portfolio - Select industry - themed ETFs with over 1 - year establishment and over 200 million current scale. Calculate sensitivity scores, adjust according to economic, liquidity, and credit indicators, and select the top 6 industry - themed indices. Currently, with economic indicators rising and liquidity/credit tightening, the portfolio turns to value with high bank and cyclical proportions. November holdings are mainly bank and energy - related ETFs, each with a 16.67% weight. The portfolio has large fluctuations and was close to the CSI 300 in October [7][9][11] Group 4: Macro + Momentum Industry Portfolio - Combine macro and momentum methods to address the left - side bias of macro - based strategies. Use clustering to select one product with the highest 6 - month gain from each of 6 industry - themed groups. The portfolio includes many pro - cyclical industries. November holdings have multiple ETFs, with weights like 16.67% for some and 8.33% for others. The portfolio performed well this year and was close to the CSI 300 in October [12][14][15] Group 5: Core - Satellite Portfolio - Designed to address the high volatility and fast industry rotation of industry - themed ETFs. Use the CSI 300 as the core. Construct three sub - portfolios (broad - based, industry, and Smart Beta) and combine them at 50%, 30%, and 20% respectively. November holdings are mainly mid - to large - cap biased. The portfolio performed steadily this year, outperforming the index almost every month, including in October [16][17][21] Group 6: Trinity Style Rotation ETF Portfolio - The model favors small - cap growth + high - quality segments this period. The portfolio's factor exposure and historical performance are provided. November holdings include ETFs such as Southern CSI 500 ETF and Southern CSI 1000 ETF. The portfolio had significant fluctuations in monthly returns and outperformed the index in most months this year, including in October [22][23][26]