2026年08月13日 Thursday Insight into China-Singapore Capital Markets, Deep Diving into Global Asset Allocation
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Fed Policy Direction: Rate Hike vs. Rate Cut Debate

Fed Policy Direction: Rate Hike vs. Rate Cut Debate
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Strong Rate Hike Expectations but Undercurrents of Rate Cuts – Deep Divergence on Fed Policy Direction

Introduction

The current mainstream expectation on Wall Street for Fed monetary policy is a rate hike, but beneath this seemingly solid consensus, the voice of the "rate-cut camp" is quietly gaining strength. According to the CME FedWatch Tool, investors see a 77% probability of a 25-basis-point or larger rate hike by the end of this year. However, a minority of analysts, led by Andrew Hollenhorst, Chief US Economist at Citi Research, firmly believe that the Fed's next interest rate move will be a cut. This divergence is not merely a clash of opinions but reflects deep structural contradictions in the US economic recovery—coexisting inflation pressure and weak growth, intertwined global geopolitical shocks and domestic demand softness. This article will deeply analyze the core logic of both camps and explore the real intention behind Fed Chair Kevin Warsh's "hawkish debut."

Rate Hike Camp's Logic: Inflation Pressures and Data Support

Wall Street's mainstream rate hike expectation is built on solid data and event support. First, the oil price surge triggered by the US-Iran war has receded after the recent ceasefire, but US gasoline prices remain well above pre-war levels, and the pass-through of energy costs to consumption has not stopped. Second, the AI boom has caused severe chip shortages, pushing up consumer electronics prices and further intensifying upward price pressure.

Meanwhile, US GDP data has been revised upward, the labor market is stabilizing, and massive fundraising by tech giants suggests that current monetary policy has not tightened substantially. More critically, Fed Chair Kevin Warsh displayed a clear hawkish stance in his "debut," explicitly citing high inflation as a core consideration in policy choices and vowing to achieve price stability. Analysts at Bank of America predict that after five consecutive years of inflation above the 2% target, policymakers will take more decisive action, with three rate hikes this year.

Rate Cut Camp's Rationale: Economic Weakness and Structural Risks

However, the "rate-cut camp," represented by Hollenhorst, deconstructs the truth behind the data from a different dimension. He clearly points out that market pricing for rate hikes is severely disconnected from the real economy.

The oil market has shifted from shortage to surplus, and the key upside risk driving inflation is being eliminated. Although first-quarter GDP growth was stronger than initial estimates, Hollenhorst notes that real consumer spending has been revised down to multi-year lows. More alarmingly, the AI boom masks uneven growth—excluding investment in computers, electronic products, and intellectual property, US economic growth is only 0.5%. This means that behind the seemingly robust GDP data lies a weak real economy.

A sluggish housing market could push inflation down faster. Hollenhorst expects core CPI to fall below 2.5% in August, down from 2.9% in May. On the labor market front, he expects job growth to lose momentum this summer, starting with the upcoming June employment report. Weekly initial jobless claims are already trending upward, often a leading indicator of a deteriorating job market. "It may take a rise in the unemployment rate for the market to reprice rate cuts, but weak employment data and an unchanged unemployment rate should at least rule out rate hikes," he adds.

Key Variable: Is Warsh's Hawkishness a Show or Genuine Intent?

Fed Chair Kevin Warsh's stance is undoubtedly the biggest uncertainty for the current policy direction. Known as a "hawkish king" during his first tenure as a Fed governor, he showed dovish tendencies during the Trump administration's search for a new chair. However, at this month's press conference following the FOMC decision, he launched a fierce attack on inflation, emphasizing that high inflation is a choice of Fed policy, seemingly implying previous tightening was insufficient.

But Robin Brooks, Senior Fellow at the Brookings Institution, disagrees. He directly states that Warsh's actions at the FOMC meeting were largely theatrical: "He had to show a hawkish stance to distance himself from the White House." Brooks believes that market expectations for a rate hike are unreasonable because oil prices have already fallen back to pre-Iran-war levels. He predicts that the June CPI report, due July 14, will start changing investors' minds—the deflationary effect of lower oil prices will remind everyone that the Fed will not hike, and if any rate change occurs, the next step should be a cut.

Conclusion: Data Will Ultimately Decide the Policy Path

The current Fed policy debate is essentially a "data game." The rate hike camp focuses on inflation stickiness, employment stability, and the AI-driven investment boom; the rate cut camp focuses on weak consumption, housing downturn, and structural growth imbalances. The divergence is not about who is right or wrong, but about different weightings of the same set of data.

Worryingly, if Warsh is indeed "putting on a show" as Brooks suggests, rate hike expectations could quickly reverse when the June CPI data comes in below expectations. Conversely, if inflation remains stubborn, the probability of a rate hike will continue to rise. In any case, investors should not be swept away by a single market consensus and must closely monitor upcoming employment and inflation data. As Hollenhorst puts it, weak data should at least rule out rate hikes—and that step might be the beginning of the return of rate cut expectations.

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  1. CONNECT:[ UseTime:0.001118s ] mysql:host=127.0.0.1;port=3306;dbname=cjgpcs;charset=utf8mb4
  2. SHOW FULL COLUMNS FROM `g3ys_config` [ RunTime:0.002452s ]
  3. SELECT `value` FROM `g3ys_config` WHERE `name` = 'timezone' AND `subsite_id` = '38' LIMIT 1 [ RunTime:0.000644s ]
  4. SHOW FULL COLUMNS FROM `g3ys_route` [ RunTime:0.002787s ]
  5. 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:0.000798s ]
  6. SHOW FULL COLUMNS FROM `g3ys_theme` [ RunTime:0.002829s ]
  7. SELECT `paginator` FROM `g3ys_theme` WHERE `module` = 'home' AND `name` = 'slogan' AND `subsite_id` = '38' LIMIT 1 [ RunTime:0.000768s ]
  8. SHOW FULL COLUMNS FROM `g3ys_lang` [ RunTime:0.003797s ]
  9. SELECT * FROM `g3ys_lang` WHERE `subsite_id` = 38 AND ( ( LOWER(name) = 'en-us' ) OR `subtag` = 'en-us' ) AND `status` = 1 ORDER BY `id` ASC LIMIT 1 [ RunTime:0.001792s ]
  10. SHOW FULL COLUMNS FROM `g3ys_member` [ RunTime:0.004252s ]
  11. SELECT * FROM `g3ys_member` WHERE `id` = 0 AND `subsite_id` = '38' LIMIT 1 [ RunTime:0.000950s ]
  12. SHOW FULL COLUMNS FROM `g3ys_document` [ RunTime:0.003948s ]
  13. SELECT `id`,`document_type` FROM `g3ys_document` WHERE `subsite_id` = 38 AND `name` = 'fed-rate-hike-vs-cut-divergence' AND `status` IN ('1','2') LIMIT 1 [ RunTime:0.001340s ]
  14. SELECT * FROM `g3ys_document` WHERE ( `name` = '5272' OR `id` = '5272' ) AND `subsite_id` = 38 LIMIT 1 [ RunTime:0.003086s ]
  15. SHOW TABLES LIKE 'g3ys_document_article' [ RunTime:0.002412s ]
  16. SHOW FULL COLUMNS FROM `g3ys_document_article` [ RunTime:0.001762s ]
  17. SELECT * FROM `g3ys_document_article` WHERE `document_id` = '5272' LIMIT 1 [ RunTime:0.000779s ]
  18. SHOW FULL COLUMNS FROM `g3ys_total` [ RunTime:0.002169s ]
  19. SELECT * FROM `g3ys_total` WHERE `target_id` = '5272' LIMIT 1 [ RunTime:0.000745s ]
  20. SHOW TABLES LIKE 'g3ys_document_article_lang' [ RunTime:0.002279s ]
  21. SHOW FULL COLUMNS FROM `g3ys_document_article_lang` [ RunTime:0.002024s ]
  22. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '38' AND `lang` = 'en-US' AND `document_id` = '5272' [ RunTime:0.006498s ]
  23. SHOW FULL COLUMNS FROM `g3ys_document_article_lang` [ RunTime:0.002393s ]
  24. SHOW TABLES LIKE 'g3ys_category_lang' [ RunTime:0.002393s ]
  25. SHOW FULL COLUMNS FROM `g3ys_category_lang` [ RunTime:0.001919s ]
  26. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '38' AND `category_id` = '1461' AND `lang` = 'en-US' LIMIT 1 [ RunTime:0.000788s ]
  27. SELECT * FROM `g3ys_total` WHERE `target_id` = '5272' LIMIT 1 [ RunTime:0.000760s ]
  28. UPDATE `g3ys_total` SET `view_total` = `view_total` + 1 WHERE `target_id` = '5272' [ RunTime:0.002524s ]
  29. SHOW FULL COLUMNS FROM `g3ys_record` [ RunTime:0.003847s ]
  30. SELECT `id` FROM `g3ys_record` WHERE `subsite_id` = '38' AND `type` = 'article' AND `url` = 'https://www.cninsgx.com/fed-rate-hike-vs-cut-divergence' AND `create_time` >= 1786626650 AND ( `visitor_id` = '9d03df70787593d65bdb0e40fffd079b' OR `session_id` = '9bdec6c5c68cdf61109f395d5ce5cc46' ) LIMIT 1 [ RunTime:0.002006s ]
  31. INSERT INTO `g3ys_record` SET `subsite_id` = '38' , `uid` = '0' , `visitor_id` = '9d03df70787593d65bdb0e40fffd079b' , `session_id` = '9bdec6c5c68cdf61109f395d5ce5cc46' , `type` = 'article' , `target_id` = '5272' , `target_type` = 0 , `category_id` = '1461' , `title` = 'Fed Policy Direction: Rate Hike vs. Rate Cut Debate' , `url` = 'https://www.cninsgx.com/fed-rate-hike-vs-cut-divergence' , `path` = '/fed-rate-hike-vs-cut-divergence' , `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` = '216.73.217.117' , `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` = 1786626710 , `update_time` = 1786626710 [ RunTime:0.002960s ]
  32. SHOW FULL COLUMNS FROM `g3ys_comment` [ RunTime:0.003810s ]
  33. SELECT COUNT(*) AS think_count FROM `g3ys_comment` WHERE `target_id` = '5272' AND `pid` = '0' [ RunTime:0.000785s ]
  34. SELECT * FROM `g3ys_document` WHERE `category_id` = 1461 AND `subsite_id` = 38 AND `pid` = '0' AND `status` = '1' AND ( ( sort > 0) or ( sort = 0 and id < 5272) ) ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.001675s ]
  35. SELECT * FROM `g3ys_document` WHERE `category_id` = 1461 AND `subsite_id` = 38 AND `pid` = '5271' AND `status` = '1' ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.001118s ]
  36. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '38' AND `lang` = 'en-US' AND `document_id` = '5271' [ RunTime:0.006694s ]
  37. SELECT * FROM `g3ys_document` WHERE `category_id` = 1461 AND `subsite_id` = 38 AND `pid` = '5272' AND `status` = '1' AND `document_type` = 0 ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.001587s ]
  38. SELECT * FROM `g3ys_document` WHERE `category_id` = 1461 AND `subsite_id` = 38 AND `pid` = '0' AND `status` = '1' AND `document_type` = 0 AND ( ( sort>0 and sort <= 0 and id!=5272) or ( sort = 0 and id > 5272) ) ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.001247s ]
  39. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '38' AND `lang` = 'en-US' AND `document_id` = '5585' [ RunTime:0.006041s ]
  40. 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:0.001318s ]
  41. SELECT * FROM `g3ys_total` WHERE `target_id` = '5272' LIMIT 1 [ RunTime:0.000752s ]
  42. SHOW FULL COLUMNS FROM `g3ys_ad_location` [ RunTime:0.002502s ]
  43. SELECT * FROM `g3ys_ad_location` WHERE `name` = 'ad-detail-full' AND `subsite_id` = '38' AND `status` = 1 LIMIT 1 [ RunTime:0.000935s ]
  44. SHOW FULL COLUMNS FROM `g3ys_ad` [ RunTime:0.002620s ]
  45. SELECT * FROM `g3ys_ad` WHERE `subsite_id` = '38' AND `ad_location_id` = '74' AND `status` = 1 AND `device` IN ('all','pc') AND ( `start_time` = 0 OR `start_time` <= 1786626710 ) AND ( `end_time` = 0 OR `end_time` >= 1786626710 ) ORDER BY `sort` DESC,`id` DESC [ RunTime:0.001043s ]
  46. SHOW FULL COLUMNS FROM `g3ys_ad_lang` [ RunTime:0.001948s ]
  47. SELECT * FROM `g3ys_ad_lang` WHERE `ad_id` = 74 AND `subsite_id` = '38' AND `lang` = 'en-US' [ RunTime:0.000756s ]
  48. SHOW FULL COLUMNS FROM `g3ys_ad_lang` [ RunTime:0.001732s ]
  49. 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:0.001316s ]
  50. 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:0.001014s ]
  51. 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:0.000910s ]
  52. 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:0.000898s ]
  53. 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:0.000707s ]
  54. 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:0.000694s ]
  55. 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:0.000680s ]
  56. 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:0.000736s ]
  57. SELECT * FROM `g3ys_ad_location` WHERE `name` = 'ad-right' AND `subsite_id` = '38' AND `status` = 1 LIMIT 1 [ RunTime:0.000856s ]
  58. 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` <= 1786626710 ) AND ( `end_time` = 0 OR `end_time` >= 1786626710 ) ORDER BY `sort` DESC,`id` DESC [ RunTime:0.000988s ]
  59. SELECT * FROM `g3ys_ad_lang` WHERE `ad_id` = 76 AND `subsite_id` = '38' AND `lang` = 'en-US' [ RunTime:0.000658s ]
  60. 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:0.000788s ]
  61. 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:0.000675s ]
  62. 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:0.000921s ]
  63. 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:0.000719s ]
  64. 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:0.000734s ]
  65. 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:0.000732s ]
  66. 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:0.000890s ]
  67. 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:0.000658s ]
  68. 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:0.000691s ]
0.416288s