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In-depth Analysis of US Market Intraday Fluctuations: Grasping Market Pulse, Seizing Investment Opportunities

In-depth Analysis of US Market Intraday Fluctuations: Grasping Market Pulse, Seizing Investment Opportunities

In-depth Analysis of US Market Intraday Fluctuations: Grasping Market Pulse, Seizing Investment Opportunities

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In today's high-speed financial markets, US market intraday fluctuations have become a focal point for investors. Behind these seemingly random fluctuations often lie subtle changes in market sentiment, shifts in capital flows, and immediate reactions to macroeconomic data. This article will delve into the causes, types, and impacts of US market intraday fluctuations on investment decisions, helping investors seize opportunities in the ever-changing market.

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Definition and Importance of US Market Intraday Fluctuations

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US market intraday fluctuations refer to sudden, unexpected significant movements in stock prices or indices during normal trading hours. These fluctuations may manifest as sudden surges or plunges in individual stocks, or as collective movements across entire sectors or the market. From a time perspective, intraday fluctuations can occur in the first 30 minutes after opening, during midday sessions, or in the final 30 minutes before closing, with fluctuations in each period often carrying different market implications.

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For short-term traders and institutional investors, intraday fluctuations are important signals for capturing market opportunities. According to statistics, the average intraday fluctuation range of the Nasdaq index reached 0.8% in the first half of 2026, with fluctuation ranges exceeding 2% during key periods on individual trading days. These fluctuations often contain significant investment opportunities but also come with corresponding risks.

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Main Causes of US Market Intraday Fluctuations

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The causes of US market intraday fluctuations are complex and diverse, mainly including the following aspects:

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  • Macroeconomic Data Releases: Regularly published employment, GDP, inflation and other data from US government departments such as the Department of Labor and Department of Commerce often trigger market reactions. For example, unexpected changes in non-farm employment data may lead to adjustments in Federal Reserve monetary policy expectations, causing significant intraday fluctuations in US stocks.
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  • Corporate Earnings Surprises or Disappointments: Earnings reports from tech giants like Apple, Microsoft, Google, etc., often trigger chain reactions in related sectors and the entire market. In the second quarter of 2026 earnings season, several AI-related companies reported better-than-expected earnings, pushing the Nasdaq to rise by over 2% at one point during the session.
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  • Geopolitical Events: Sudden changes in international situations, such as escalation of Middle East conflicts or adjustments in trade policies, often lead to increased risk aversion, causing capital to flow from risky assets to safe-haven assets, resulting in sharp intraday declines in US stocks.
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  • Central Bank Policy Signals: Speeches by Federal Reserve officials, policy statements, or changes in the dot plot directly affect market expectations for interest rate paths, leading to intraday fluctuations in US stocks. In July 2026, hawkish remarks by Federal Reserve Chair Powell caused the Dow to fall by over 400 points during the session.
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  • Algorithmic and Program Trading: As the proportion of quantitative trading continues to increase, algorithmic trading has become an important driver of intraday fluctuations. According to statistics, about 70% of trading volume in the US stock market now comes from program trading. These trading systems can trigger chain reactions under specific conditions, amplifying market volatility.
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  • Large Institutional Trading Activities: Portfolio adjustments by large institutions such as pension funds and hedge funds, especially large transactions involving billions of dollars, can often have a significant impact on stock prices in a short period.
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How to Interpret US Market Intraday Fluctuation Signals

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Accurately interpreting intraday fluctuation signals is key to investment success. Investors should analyze from the following dimensions:

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1. Fluctuation Magnitude and Duration

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The magnitude of fluctuations is an important indicator for judging the strength of market reactions. Generally, individual stock fluctuations exceeding 5% or index fluctuations exceeding 1% in a single day warrant close attention. At the same time, the duration of fluctuations is also crucial: brief pulse-like fluctuations may be short-term reactions to market sentiment, while persistent fluctuations may signal the formation of a trend.

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2. Volume Changes

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Volume is a key indicator for verifying the authenticity of fluctuations. Abnormal fluctuations accompanied by significant volume increases usually indicate real capital inflows and outflows; while fluctuations without volume may be market manipulation or technical false breakouts. In early August 2026, a biotech stock surged 30% during the session due to FDA approval news, but trading volume only increased by 50%, followed by a rapid decline, indicating this might be speculative trading rather than fundamental changes.

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3. Market Breadth Analysis

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Fluctuations in individual stocks may be caused by company-specific factors, while widespread fluctuations across sectors or the market reflect systemic factors. By analyzing market breadth indicators such as the number of advancing and declining stocks, and the number of new highs and lows, investors can determine whether a fluctuation is a local phenomenon or an overall trend.

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4. Technical Pattern Analysis

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Intraday fluctuations often occur near key technical levels. For example, accelerated upward movement after a stock breaks through key resistance levels, or panic selling after breaking through important support levels, can trigger technical fluctuations. By combining technical indicators such as moving averages, RSI, and MACD, investors can more accurately determine the technical significance of fluctuations.

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Different Types of Intraday Fluctuations and Their Market Implications

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Based on the nature and triggering factors, US market intraday fluctuations can be divided into the following main types:

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1. News-driven Fluctuations

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These fluctuations are triggered by sudden news at the company or industry level, such as mergers and acquisitions, product launches, regulatory policy changes, etc. For example, in July 2026, an electric vehicle manufacturer announced a breakthrough in battery technology, causing its stock to rise by over 15% at one point during the session. Such fluctuations typically have sudden and persistent characteristics, and investors should focus on the authenticity and long-term impact of the news, avoiding chasing highs.

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2. Capital Flow-driven Fluctuations

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These fluctuations are mainly caused by concentrated large-scale capital inflows and outflows, usually manifested as abnormal volume increases and rapid price movements. For example, in early August 2026, a hedge fund significantly reduced its holdings of tech stocks, triggering sharp declines in related sectors during the session. Such fluctuations often have persistence, and investors should pay attention to changing trends in capital flows.

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3. Algorithmic Trading-driven Fluctuations

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With the popularization of quantitative trading, algorithmic trading-induced intraday fluctuations have become increasingly frequent. These fluctuations typically manifest as flash crashes or rapid rebounds, with short duration but high volatility. For example, in May 2026, an index futures triggered program trading stop-loss mechanisms, causing the S&P 500 to fall by 1.5% within 5 minutes before rebounding quickly. Such fluctuations pose greater risks to ordinary investors and should be approached with caution.

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4. Market Sentiment-driven Fluctuations

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These fluctuations are mainly caused by collective shifts in market sentiment, such as panic selling or greedy chasing of gains. For example, in June 2026, influenced by higher-than-expected inflation data, market panic sentiment intensified, causing all three major US indices to fall by over 2% during the session. Such fluctuations often have contagion and amplification effects, and investors should remain rational and avoid emotional trading.

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Investor Response Strategies

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Facing US market intraday fluctuations, investors should adopt the following strategies:

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1. Establish a comprehensive fluctuation monitoring system

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Investors should use professional trading software to establish an intraday fluctuation monitoring system, set warning thresholds for key indicators such as price, volume, and volatility, to promptly identify potential trading opportunities or risks. For example, set alerts for individual stocks fluctuating by more than 3% within 5 minutes, or for sector trading volume suddenly increasing by 50%.

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2. Differentiate between fluctuation types and respond accordingly

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Different types of fluctuations require different response strategies. For news-driven fluctuations, quickly evaluate the authenticity and impact of the news; for capital flow-driven fluctuations, pay attention to the direction and persistence of large-scale capital flows; for algorithmic trading-driven fluctuations, avoid short-term chasing highs and selling lows; for market sentiment-driven fluctuations, remain rational and avoid herd mentality.

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3. Strict Risk Management

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Intraday fluctuations often come with high risks, and investors should strictly set stop-loss levels and control single-trade risks. Generally, single-trade risks should not exceed 2% of total capital. At the same time, avoid full-position operations during intraday fluctuations, retaining sufficient capital to respond to subsequent volatility.

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4. Combine multi-time period analysis

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Intraday fluctuations should not be viewed in isolation but should be analyzed in conjunction with longer timeframes such as daily and weekly charts. For example, a pullback during the session for a stock in an upward daily trend might be a buying opportunity, while a rebound during the session for a stock in a downward trend might be a selling opportunity.

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5. Pay attention to changes in market microstructure

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Investors should pay attention to changes in market microstructure indicators such as order book depth and bid-ask spreads, which often can predict the direction and intensity of intraday fluctuations in advance. For example, a sudden large accumulation of buy orders above the ask price may indicate an impending upward movement.

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Conclusion

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US market intraday fluctuations are normal phenomena in market operations, representing both risks and opportunities. Investors should establish a scientific framework for fluctuation analysis, accurately identify fluctuation types, grasp the market logic behind fluctuations, while strictly controlling risks. In the era of information explosion, the frequency and intensity of intraday fluctuations may further increase. Only investors with keen insight and strict discipline can seize opportunities in the ever-changing market and achieve long-term stable investment returns.

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With the widespread application of artificial intelligence, big data and other technologies in the financial sector, future intraday fluctuations may exhibit more new features. Investors need to continuously learn and adapt, combining technical and fundamental analysis to navigate the US stock market with ease. As investment legend Warren Buffett said: "Be fearful when others are greedy, and greedy when others are fearful." Amid the noise of intraday fluctuations, maintaining calm and rationality is the ultimate secret to investment success.

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  1. CONNECT:[ UseTime:0.001518s ] mysql:host=127.0.0.1;port=3306;dbname=cjgpcs;charset=utf8mb4
  2. SHOW FULL COLUMNS FROM `g3ys_config` [ RunTime:0.005223s ]
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  30. SELECT `id` FROM `g3ys_record` WHERE `subsite_id` = '38' AND `type` = 'article' AND `url` = 'https://www.cninsgx.com/us-market-intraday-movements-analysis' AND `create_time` >= 1786223063 AND ( `visitor_id` = 'ed95b246297c9da9893c77af9b6b1ea1' OR `session_id` = '2fc65968c1f64ef65804b04560da41df' ) LIMIT 1 [ RunTime:0.002871s ]
  31. INSERT INTO `g3ys_record` SET `subsite_id` = '38' , `uid` = '0' , `visitor_id` = 'ed95b246297c9da9893c77af9b6b1ea1' , `session_id` = '2fc65968c1f64ef65804b04560da41df' , `type` = 'article' , `target_id` = '6355' , `target_type` = 0 , `category_id` = '1464' , `title` = 'In-depth Analysis of US Market Intraday Fluctuations: Grasping Market Pulse, Seizing Investment Opportunities' , `url` = 'https://www.cninsgx.com/us-market-intraday-movements-analysis' , `path` = '/us-market-intraday-movements-analysis' , `query_string` = '' , `referer` = '' , `referer_domain` = '' , `source_type` = 'direct' , `source_domain` = '' , `search_engine` = '' , `search_keyword` = '' , `utm_source` = '' , `utm_medium` = '' , `utm_campaign` = '' , `utm_term` = '' , `utm_content` = '' , `ip` = '216.73.217.6' , `user_agent` = 'Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)' , `device_type` = 'pc' , `browser` = '其他' , `browser_version` = '' , `os` = '其他' , `os_version` = '' , `language` = '' , `is_spider` = 0 , `spider_name` = '' , `status_code` = 200 , `country` = '' , `province` = '' , `city` = '' , `district` = '' , `isp` = '' , `region_code` = '' , `geo_status` = 0 , `geo_time` = 0 , `create_time` = 1786223123 , `update_time` = 1786223123 [ RunTime:0.008982s ]
  32. SHOW FULL COLUMNS FROM `g3ys_comment` [ RunTime:0.004460s ]
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  36. SHOW TABLES LIKE 'g3ys_paragraph' [ RunTime:0.003568s ]
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  38. SHOW TABLES LIKE 'g3ys_gallery' [ RunTime:0.003525s ]
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  40. SHOW TABLES LIKE 'g3ys_video' [ RunTime:0.005918s ]
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  42. SHOW TABLES LIKE 'g3ys_faq' [ RunTime:0.005597s ]
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  50. SHOW TABLES LIKE 'g3ys_videos' [ RunTime:0.007008s ]
  51. SHOW TABLES LIKE 'g3ys_videos_lang' [ RunTime:0.003642s ]
  52. SHOW TABLES LIKE 'g3ys_audios' [ RunTime:0.004476s ]
  53. SHOW TABLES LIKE 'g3ys_audios_lang' [ RunTime:0.005698s ]
  54. SHOW TABLES LIKE 'g3ys_files' [ RunTime:0.005896s ]
  55. SHOW TABLES LIKE 'g3ys_files_lang' [ RunTime:0.004078s ]
  56. SHOW TABLES LIKE 'g3ys_richmedia' [ RunTime:0.006305s ]
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  60. SHOW FULL COLUMNS FROM `g3ys_gallery` [ RunTime:0.007283s ]
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  62. SHOW FULL COLUMNS FROM `g3ys_video` [ RunTime:0.003409s ]
  63. SELECT * FROM `g3ys_video` WHERE `document_id` = 6355 AND `subsite_id` = 38 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.002396s ]
  64. SHOW FULL COLUMNS FROM `g3ys_faq` [ RunTime:0.005280s ]
  65. SELECT * FROM `g3ys_faq` WHERE `document_id` = 6355 AND `subsite_id` = 38 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001314s ]
  66. SHOW FULL COLUMNS FROM `g3ys_blockquote` [ RunTime:0.004194s ]
  67. SELECT * FROM `g3ys_blockquote` WHERE `document_id` = 6355 AND `subsite_id` = 38 AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.002483s ]
  68. SHOW FULL COLUMNS FROM `g3ys_cards` [ RunTime:0.004424s ]
  69. SELECT * FROM `g3ys_cards` WHERE `document_id` = 6355 AND `subsite_id` = '38' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.002085s ]
  70. SHOW FULL COLUMNS FROM `g3ys_objects` [ RunTime:0.004198s ]
  71. SELECT * FROM `g3ys_objects` WHERE `document_id` = 6355 AND `subsite_id` = '38' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001660s ]
  72. SHOW FULL COLUMNS FROM `g3ys_videos` [ RunTime:0.004045s ]
  73. SELECT * FROM `g3ys_videos` WHERE `document_id` = 6355 AND `subsite_id` = '38' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.003952s ]
  74. SHOW FULL COLUMNS FROM `g3ys_audios` [ RunTime:0.004021s ]
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  76. SHOW FULL COLUMNS FROM `g3ys_files` [ RunTime:0.005327s ]
  77. SELECT * FROM `g3ys_files` WHERE `document_id` = 6355 AND `subsite_id` = '38' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.003003s ]
  78. SHOW FULL COLUMNS FROM `g3ys_richmedia` [ RunTime:0.004182s ]
  79. SELECT * FROM `g3ys_richmedia` WHERE `document_id` = 6355 AND `subsite_id` = '38' AND `status` = 1 ORDER BY `sort` ASC,`id` ASC [ RunTime:0.001325s ]
  80. SELECT * FROM `g3ys_document` WHERE `category_id` = 1464 AND `subsite_id` = 38 AND `pid` = '0' AND `status` = '1' AND ( ( sort > 0) or ( sort = 0 and id < 6355) ) ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.003913s ]
  81. SELECT * FROM `g3ys_document` WHERE `category_id` = 1464 AND `subsite_id` = 38 AND `pid` = '6297' AND `status` = '1' ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.001663s ]
  82. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '38' AND `lang` = 'en-US' AND `document_id` = '6297' [ RunTime:0.014402s ]
  83. SELECT * FROM `g3ys_document` WHERE `category_id` = 1464 AND `subsite_id` = 38 AND `pid` = '6355' AND `status` = '1' AND `document_type` = 0 ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.002404s ]
  84. SELECT * FROM `g3ys_document` WHERE `category_id` = 1464 AND `subsite_id` = 38 AND `pid` = '0' AND `status` = '1' AND `document_type` = 0 AND ( ( sort>0 and sort <= 0 and id!=6355) or ( sort = 0 and id > 6355) ) ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.002055s ]
  85. SHOW FULL COLUMNS FROM `g3ys_file` [ RunTime:0.007048s ]
  86. SELECT * FROM `g3ys_file` WHERE `status` = 1 AND `id` = 4726 LIMIT 1 [ RunTime:0.003060s ]
  87. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001293s ]
  88. SELECT * FROM `g3ys_total` WHERE `target_id` = '6355' LIMIT 1 [ RunTime:0.001131s ]
  89. SHOW FULL COLUMNS FROM `g3ys_ad_location` [ RunTime:0.003858s ]
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  91. SHOW FULL COLUMNS FROM `g3ys_ad` [ RunTime:0.005448s ]
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  94. SELECT * FROM `g3ys_ad_lang` WHERE `ad_id` = 74 AND `subsite_id` = '38' AND `lang` = 'en-US' [ RunTime:0.003606s ]
  95. SHOW FULL COLUMNS FROM `g3ys_ad_lang` [ RunTime:0.003171s ]
  96. SHOW FULL COLUMNS FROM `g3ys_tags` [ RunTime:0.004628s ]
  97. SELECT `title`,`color`,`description`,`seotitle`,`keyword`,`name`,`id` FROM `g3ys_tags` WHERE `id` IN (447,434,437,439,438,446,423,425) AND `status` = 1 [ RunTime:0.001266s ]
  98. SHOW FULL COLUMNS FROM `g3ys_tags_lang` [ RunTime:0.003418s ]
  99. SELECT * FROM `g3ys_tags_lang` WHERE `tags_id` IN (447,434,437,439,438,446,423,425) AND `subsite_id` = 38 AND `lang` = 'en-US' [ RunTime:0.001939s ]
  100. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000880s ]
  101. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000916s ]
  102. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000862s ]
  103. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000844s ]
  104. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000935s ]
  105. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000861s ]
  106. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000881s ]
  107. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001512s ]
  108. SELECT * FROM `g3ys_ad_location` WHERE `name` = 'ad-right' AND `subsite_id` = '38' AND `status` = 1 LIMIT 1 [ RunTime:0.001364s ]
  109. SELECT * FROM `g3ys_ad` WHERE `subsite_id` = '38' AND `ad_location_id` = '76' AND `status` = 1 AND `device` IN ('all','pc') AND ( `start_time` = 0 OR `start_time` <= 1786223123 ) AND ( `end_time` = 0 OR `end_time` >= 1786223123 ) ORDER BY `sort` DESC,`id` DESC [ RunTime:0.001625s ]
  110. SELECT * FROM `g3ys_ad_lang` WHERE `ad_id` = 76 AND `subsite_id` = '38' AND `lang` = 'en-US' [ RunTime:0.000900s ]
  111. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000843s ]
  112. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000949s ]
  113. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001120s ]
  114. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000948s ]
  115. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000884s ]
  116. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.002597s ]
  117. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000869s ]
  118. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000925s ]
  119. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '38' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001292s ]
0.987419s