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早盘创业板ETF天弘(159977)收涨2.26%、科创综指ETF天弘(589860)收涨1.65%、中证A500ETF天弘(159360)收涨1.29%
8月25日,市场早盘冲高回落,创业板指领涨,两市成交额放量明显,沪深两市半日成交额2.08万亿, 较上个交易日放量5678亿。 主流宽基ETF中,创业板ETF天弘(159977)早盘收涨2.26%,盘中价格再创阶段新高,且溢价交易明 显;成分股中,金力永磁盘中涨停,乐普医疗、中际旭创、协创数据等多股大涨。 此外,科创综指ETF天弘(589860)早盘收涨1.65%,成分股中,开普云20CM涨停,航天宏图冲击涨 停;中证A500ETF天弘(159360)收涨1.29%,罗博特科20CM涨停。 对于后市,华泰证券认为,充裕流动性仍是行情的主要基底,短期来看,判断市场顶部的意义和胜率都 不算高,配置上应保持仓位、顺势择线、适度内部高低切换;节奏上后续即便出现调整,幅度也不会太 深,市场进入上行趋势的共识在逐步增强。过往看国内基本面、国内流动性、海外流动性三者改善是市 场步入上行趋势的关键三支柱,当前三个因素都在汇聚积极变化,从量变到质变需要时间,蓄势充分后 期行情才有望走的更远。配置上,AI链、创新药、大金融仍是战略配置重点,内部适度高切低。 华宝证券认为,市场热情高涨,A股顺势而为。当前市场情绪保持高涨,增量资金 ...
华泰证券:AI链、创新药、军工、大金融仍是战略配置重点
Xin Lang Cai Jing· 2025-08-18 00:05
Group 1 - The core viewpoint is that the A-share market has seen a significant increase in trading volume, driven by active trading funds and ample market liquidity [1] - Financial data indicates a divergence in entity credit and M1 year-on-year, with traditional industries showing overall weakness; deposit data reflects signs of resident funds entering the market, suggesting that if the stock market can create a sustained profit effect, the liquid deposits could be a potential incremental source in the future [1] - Currently, the entry of resident funds into the market is primarily through leveraging existing funds, as evidenced by the continuous increase in the activity of leveraged funds, while the number of new accounts, public fund issuance, and private fund registrations have improved but with limited slope; ETFs have seen overall net outflows in the past month, with increasing industry differentiation [1] Group 2 - Foreign and insurance capital are also potential incremental funds worth monitoring, as their activity levels have recently increased [1] - The market trend is strong, and it is recommended to maintain a relatively high position; strategic allocations should focus on AI chains, innovative pharmaceuticals, military industry, and large financial sectors, with an internal adjustment to high and low positions [1] - Within AI, attention should be paid to domestic computing power and AI applications, while in pharmaceuticals, the focus should be on externally driven CDMO [1]