華爾街逆風而行,市場前景如何?




**華爾街面對PPI數據及摩根大通盈利挑戰:這位策略師預期市場表現正面,但回報或有限**

美國指數期貨顯示週五開市可能輕微下滑,交易員希望批發價格有好消息。週四消費者價格通脹數據略高於預期,令市場氣氛整天受壓,主要指數最終輕微下跌。隨著通脹數據公佈,Harris Financial Group管理合夥人Jamie Cox表示:「通脹減速持續,但任何認為聯儲局會在11月再降息0.50個基點的人都是錯的。」

他補充說:「當利率不足以壓低增長時,也不足以完全抑制通脹。聯儲局會降低利率,但步伐會謹慎。」

Tesla的自動駕駛出租車活動未能推動其股價上升。摩根大通將開啟大型銀行盈利季,其盈利被視為衡量該行業健康狀況的指標。

**期貨表現(+/-)**
– 納斯達克100:-0.32%
– 標普500:-0.19%
– 道瓊斯:-0.16%
– Russell 2000:-0.43%

根據Benzinga Pro數據,週五盤前交易中,SPDR標普500 ETF Trust下跌0.10%至575.53美元,Invesco QQQ ETF下跌0.20%至491.60美元。

**前一交易日的啟示:**

由於通脹數據略高於預期,加上颶風海倫引致的失業申請達到一年多來的最高水平,週四股市低開。這些報告令債券收益率大幅上升。

30隻股票組成的道瓊斯工業平均指數整天處於下跌狀態,而科技股主導的納斯達克綜合指數及更廣泛的標普500指數在整天大部分時間低於平盤。

在此過程中,道指和標普500指數從其歷史高位回落。

除了三個標普500行業類別外,其餘均以紅色收盤,這三個例外是能源、IT和材料股。

**指數表現(+/-)**
– 納斯達克綜合指數:-0.05%(18,282.05)
– 標普500指數:0.21%(5,780.05)
– 道瓊斯工業指數:-0.14%(42,454.12)
– Russell 2000:-0.55%(2,188.42)

**分析師的見解:**

LPL首席技術策略師Adam Turnquist對即將完成兩年的牛市發表了看法。自那時以來,標普500指數上漲了62%,並創下44次歷史新高。

這位策略師表示,低波動性是這次牛市的一個受歡迎的特徵。自2022年10月12日的收盤低點以來,標普500的最大回撤僅為10.3%,低於所有牛市的平均最大回撤-14.2%。

展望未來,Turnquist表示,大多數牛市在其第三年內仍保持牛市。自1950年以來,牛市的平均持續時間為61個月,不包括當前的牛市,最短的持續時間為21個月,從2020年3月到2022年1月。

他說,當前27.2%的年化回報率相對於其他牛市來說較高。「歷史表明,如果這次牛市持續,投資者應該預期未來的年化回報會是正面的,但可能會較為平淡。」

**即將公佈的經濟數據**

勞工部預定於東部時間早上8:30公佈9月份的生產者價格通脹報告。9月份的總體和核心生產者價格可能分別上升0.1%和0.2%。相比之下,8月份的增幅為0.2%和0.3%。總體和核心生產者價格通脹的年率預期分別為1.6%和2.7%,8月份則為1.7%和2.4%。

週五發言的聯儲局官員包括:
– 芝加哥聯儲主席Austan Goolsbee:上午9:45
– 達拉斯聯儲主席Lorie Logan:上午10:45
– 聯邦儲備理事會理事Michelle Bowman:下午1:10

密歇根大學10月份的消費者信心指數初值將於上午10點公佈。預計消費者信心指數將從9月份的70.1上升至10月份的71。交易員可能還會關注一年的、兩年的和五年的通脹預期數據。

**關注的股票:**

Tesla在公司的自動駕駛出租車活動後,盤前交易中下跌5.60%。提供叫車服務的Uber和Lyft股價亦受到影響。

即將公佈季度業績的知名公司包括BlackRock、摩根大通、富國銀行、Fastenal Company和紐約梅隆銀行。

**商品、債券及全球股市:**

原油期貨在週四強勁上漲後回落,而黃金期貨則走強。比特幣交易價格接近61,000美元。10年期國債收益率變動不大,為4.092%。

由於美國通脹數據意外上升,亞洲市場情緒低迷,中國股市大幅下跌。香港市場因公眾假期休市。

歐洲市場表現不一,交易員對英國公佈的多數疲弱數據作出反應。

**編者評論:**

在這個背景下,市場似乎處於一個微妙的平衡點。雖然牛市仍然持續,但較高的年化回報率和即將公佈的經濟數據可能會令投資者更加謹慎。聯儲局的利率策略將成為市場未來走向的關鍵因素。隨著摩根大通等大型銀行即將公佈業績,這將進一步提供市場健康狀況的指標。至於Tesla等個別股票的波動,反映出市場對於未來科技發展的期望和現實之間的落差。投資者需保持靈活,密切關注即將公佈的重要經濟數據和企業業績。

以上文章由特價GPT API根據網上資料所翻譯及撰寫,過程中沒有任何人類參與 🙂

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