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在高波动中挖坑,主力已经不择手段!
Sou Hu Cai Jing·2025-05-06 04:06

Core Viewpoint - The market has experienced significant volatility since the sharp decline on April 7, leading to concerns among investors about the potential for recovery and strategies to navigate the turbulent environment [1] Group 1: Market Volatility - A-shares exhibit higher volatility compared to U.S. stocks, with A-shares experiencing a 16% fluctuation in individual stocks since April 7, while U.S. stocks have only seen a decline of over 30% eight times in the past 120 years [2][4] - Investors should embrace the high volatility of A-shares as it presents opportunities for excess returns, as stable markets do not typically reveal undervalued or panic-driven opportunities [4] Group 2: Investment Strategies - Ordinary investors are advised to adopt a trend-following approach rather than attempting to predict market movements, as retail investors are more susceptible to emotional influences compared to institutional investors [5] - The reliance on K-line patterns and financial news may obscure the true market dynamics, and utilizing big data technology can help uncover genuine trading intentions and market essence [5][12] Group 3: Institutional Behavior - The behavior of institutional funds is crucial in determining stock price movements, as seen in the example where a stock experiences a pullback followed by a rise, indicating potential new investment opportunities driven by institutional support [7] - Signals of "strong profit-taking" indicate that institutional investors are realizing profits, which may suggest a high risk for chasing prices upward despite subsequent minor increases [9][11] Group 4: Data Utilization - Professional big data tools are available to capture and analyze original trading data, allowing for the identification of abnormal trading signals that may not be visible to ordinary investors [12][14] - Active institutional inventory data often correlates with upward price momentum, while its absence can lead to downward trends, highlighting the limitations of solely relying on K-line analysis [14]