【阿里AI殺入歐洲?】蔡崇信巴黎發聲:美國雲巨頭之外的 Plan B|阿里巴巴9988 BABA|技術分析

Brief Summary

This video discusses the transformation of Alibaba from an e-commerce platform to an AI-focused company, highlighting its valuation model, market strategies, and financial pressures. It explores the underlying business logic driving AI's potential $50 trillion market, the full-stack strategy involving chips, cloud services, and large models, as well as the implications of AI becoming a virtual labor force rather than traditional software. The narrative also covers Alibaba's initiatives in Europe, addressing data sovereignty and regulatory compliance, while questioning the future dynamics of the AI market and its potential monopolization.

  • Alibaba presents AI as a $50 trillion opportunity while facing cash flow issues.
  • The shift from e-commerce to AI-focused business models includes full-stack strategies and the implications for the workforce.

Opening: $50 Trillion AI Vision vs Free Cash Flow Pressures

Alibaba at the Paris BFAtech conference proclaims the AI sector could hold a $50 trillion market potential. However, their financials reveal a concerning reality, with cash flow dropping significantly over the past year, exposing challenges in pursuing this ambitious AI vision. The speaker emphasizes the importance of understanding whether Alibaba is genuinely transitioning into an AI technology giant or merely using substantial cash reserves to cover short-term operational flaws.

Changes in Alibaba's Valuation Model: From E-commerce to AI Infrastructure Company

The analysis points out that Alibaba's valuation model has evolved, shifting its story from being just an e-commerce platform to being recognized as an AI infrastructural company. This transformation highlights not only a change in branding but a critical realignment in how market participants and consumers perceive Alibaba's role in the technology landscape, moving beyond traditional revenue models related solely to e-commerce.

Why AI is Not Traditional Software, But Virtual Labor

AI is characterized as a virtual labor force, fundamentally different from traditional software, which primarily serves as tools. AI provides organizations with autonomous operational capabilities, focusing on essential business expenditures such as labor costs and production process automation. This distinction is vital as it indicates AI's potential to reshape business operations by taking over complex tasks that previously required human input.

The Business Logic Behind the $50 Trillion Market Imagination

The discussion delves into the massive $50 trillion market potential for AI, which, if realized, could encompass a significant portion of human productivity across various sectors. However, skepticism arises from historical perspectives on tech industry valuations. The reality of turning this ambition into operational success is tied to an effective business model that can capitalize on AI's capabilities in aggregate productivity rather than solely relying on software licensing revenues.

Full-stack Strategy: Chips, Cloud, Large Models, and Application Scenarios

Alibaba's full-stack strategy aims to intertwine chips, cloud computing, large AI models, and various application scenarios. This approach underscores the necessity of having an integrated framework to benefit comprehensively from AI developments. By orchestrating investment across the entire tech stack, Alibaba seeks to mitigate risks associated with shifting market dynamics and to establish a robust competitive position in the rapidly evolving AI landscape.

Why Qwen's Open Source is Not Charity

The emphasis on Qwen's open-source model illustrates that its intention extends beyond mere charity. The strategy is to create an ecosystem where the foundation is available for free, fostering widespread usage and eventual dependence on proprietary services. This model reflects a nuanced understanding that providing free tools can catalyze further monetizable solutions down the line, establishing a recurring revenue stream rooted in enterprise-level solutions.

How MaaS Platforms and Agent AI Drive Cloud Consumption

MaaS (Machine as a Service) platforms and agent-based AI are explored as vehicles to propel cloud consumption. These innovations facilitate enhanced user experiences and enterprise functionalities, promoting the adoption of cloud services. As enterprises seek efficiency through these advanced platforms, the demand for scalable cloud solutions is expected to increase significantly, allowing companies like Alibaba to capitalize on this trend.

Behind Free Models: The Real Revenue Comes from Computing Power and Toolchains

The concept of “free models” in AI is discussed, revealing that the actual monetization stems from computing power, toolchains, and enterprise-level integrations rather than the software itself. Users may access the initial model at no charge, but the ongoing costs associated with system operation, maintenance, and optimization are substantial and represent a more lucrative business opportunity.

How Alibaba Uses AI and Cloud to Enter the European Market

Alibaba's strategy to penetrate the European market involves leveraging AI and cloud services tailored to local compliance needs and data sovereignties. By emphasizing data privacy and regulatory adherence, Alibaba positions itself as a credible alternative for European enterprises worried about dependence on U.S. tech giants. This localized approach aims to build trust and establish a foothold in a region with growing tech concerns.

Paris' New Cloud District, Data Sovereignty, and European Compliance

The establishment of a new cloud district in Paris signifies Alibaba's commitment to data sovereignty and compliance within Europe. This development showcases the necessity for tech firms to adapt to regional regulations and reassure customers that their data will remain controlled within local jurisdictions, addressing prevailing fears associated with data privacy.

Is Alibaba Cloud a Plan B for European Enterprises?

The discussion questions whether Alibaba Cloud can serve as an alternative to current solutions available to European enterprises. With concerns about reliance on dominant U.S. cloud providers, Alibaba's offerings may cater to businesses searching for local options that align with regulatory structures, thus broadening the competitive landscape within the cloud market.

Grand Vision Meets Reality: Free Cash Flow Pressures

The video highlights a considerable drop in Alibaba's free cash flow compared to the previous year. The stark contrasts between ambitious AI developmental goals and real financial outcomes provide a sobering view of the challenges facing the company. This financial strain raises critical questions about sustainability and the company's long-term strategies amidst fierce market competition.

Four-Level Rocket Monetization Model: Open Source, Ecosystem, Cloud, Scenarios

Alibaba's monetization strategy is described through a four-level rocket model, comprising open-source components, ecosystem developments, cloud services, and application scenarios. This model outlines how the company plans to leverage each level to optimize revenue generation while addressing different market needs through strategic investments that gradually push offerings from free to premium.

C-end Retention, AI Revenue Growth, and Business Model Validation

Evident trends in C-end retention and AI revenue growth present Alibaba with opportunities to validate its business models. Maintaining customer loyalty and continuously innovating services ensure that adopted AI solutions translate into tangible revenue. The overall effectiveness of these models will determine longevity and success in such a competitive environment.

Summary of Key Conflicts in Alibaba's AI Transformation

Key contradictions in Alibaba's transformation to an AI-centric company are discussed, revolving around the balance between revolutionary ambitions and ongoing financial realities. Emphasizing the need to address cash flow issues while pursuing cutting-edge tech illustrates the tensions that could affect Alibaba's success trajectory in the AI market.

The Second Half of AI: Scoring is Unimportant; Cash Flow is Key

Looking ahead, the discussion suggests that merely scoring on AI capabilities will not be sufficient; the focus must be on sustaining cash flow to remain viable. The evolving landscape necessitates a shift towards ensuring resources support productive growth rather than getting sidetracked by merely achieving superficial advancements in technology.

Final Question: Will AI Infrastructure Ultimately Lead to Super Oligopolies?

The video poses critical questions regarding the future of the AI infrastructure market. Concerns arise over the potential domination by a handful of players, leading to super oligopolies. This scenario warrants ongoing examination as the dynamics of an increasingly competitive AI landscape unfold.

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Full transcript of “【阿里AI殺入歐洲?】蔡崇信巴黎發聲:美國雲巨頭之外的 Plan B|阿里巴巴9988 BABA|技術分析”. Click a timestamp to open the video at that moment. Need another video? Use the YouTube transcript generator.

0:00 阿裡喺巴黎BFAtech科技大會上向世 界講A會係一個高達50萬億美元嘅經市場 ,另一邊當你打開佢冰冷嘅財務報表,就會 見到另一個現實自由現今金流出咗問題,為 咗追呢個所謂嘅未來,阿裡短一年入面自由 現金流接出咗466億人民幣,所以今日要 解嘅唔係阿裡,又出咗咩新口號,唔佢又講 咗幾多AI嘅警要睇嘅係,阿裡到底係咪真 係由一間中國電商 變成一間AI家嘅全科技頭定係佢只系用幾 百億現金去填一個暫時睇唔到底嘅臥底動視

0:46 頻最後仲有我自己對阿裡巴巴99八技術分 析,講真當我哋再睇阿裡呢間公司,舊有嗰 套估值,可能已經唔夠用。以前你睇好似唔 會惗 告收入,但而家裡市場接受嘅新故事係:我 唔止係電商,我系AI機件公司,呢個轉變 唔係PR層面,玩具slogan咁簡單, 我哋要穿過啲好性感嘅科技概念,直接佢背 後嘅model更加重要嘅係嗰四6億人民 幣消失咗嘅現金流,其實影射緊所有in AI4科技都面對緊同一場生死局。先由最

1:31 誇張嗰個數字講起,50萬億美元。即係可 市場空間,你要知道全球一連GDP大概都 係100萬億美元出頭,阿裡宜家講AI市 場有50萬億美元,差唔多於將人類社會一 半生產力,都懷入AI嘅潛在地盤,你第一 眼聽到可能會覺得係咪畫餅劃到上太空,係 咪純粹為咗推高值製造一個如果你利用傳統 software行業嘅角度,睇呢個懷疑 好合理,因為過去幾十年科技公司主要賺嘅 係企業部門嗰筆錢,每間公司每年有固定 IT不絕,大家就喺嗰蛋糕入面搶,傳統邏 輯簡單你賣幾多套件,有幾多月用戶每個月

2:21 收幾多錢,但阿裡今次想講嘅係一套邏輯佢 想唔好再將A當software喺雙業賬 本超可 虛而勞動力,以前嘅software就好 似買一把風利嘅產工人,工人可以畫到土畫 得快啲,但質上仍然係工具,但係AI唔同 。AI係直接派一個可以自己判斷,自己執 行任務嘅虛擬員工比你,佢滲透嘅就唔再係 少少ITbudget,佢瞄準嘅係企業最 大支出之一人力成本仲有企業最核心嘅生產 程,例例如自動化複雜數據分析,全天後克 服大規模社當一部分以前需要人手做嘅努力

3:06 勞可以被AI產品化成個市場想空間就唔同 曬,所以阿裡嘅盤係我唔再滿足於每個月收 你少少software我想賺嘅係企業重 工作程部分人力,使用底層無型推理同算力 嗰筆錢呢個就係美 聽背後嘅邏輯,就算市場真係有50萬億美 元咁大,阿裡 覺得自己食得到,答案就係佢哋反覆強調嘅 full全策略。阿裡唔係淨係做箍 抵有平晶片,中間有阿理魂、上仲有徒 保خت保 聽落好似我全部都要,但喺而家AI呢個階

3:53 段,我全部都要,其實唔止係進攻略亦系被 迫出嚟嘅防守,點解?因為而家冇人知AI 產業年入面最大嘅長期利潤最後會沉澱喺邊 一層系底推精片,係 礎大模型,定係最上層嘅應用,每人睇得準 如果你只做其中一層,風險其實好大,例如 你只係一間大型公司,萬一聽日開型,將價 格打到極低,甚至近免費,你嘅เปล業化 可能即刻崩盤,所以下你嘅邏輯其實係想建 立一個內循環,無論值最後轉去邊一層,啲 肉都儘量爛難喺自己個煲入面,但係呢度又 有一個好反直覺嘅位,如果基礎無形係成個

4:41 生態嘅大腦,係核心資產,點解阿裡要將自 己嘅団模型寬、大幅開,甚至免費俾人用, 表面睇,好似將皇冠上面凹補石拎出嚟送人 ,競爭對手白咗點算,但商業界入面免費2 個字,通常都都最貴嘅密碼開完唔係做 狠,最高效率嘅獲口,你自己個無形落僕玩 下做個test當然可以免費但係一間真正 嘅企業,你想將AI無型接入深流程事情就 完全唔同,你需要凱亮力去run佢將公司 多年嘅私有數據入去令佢真正式你賠生意你

5:28 需要安全嘅端Database去存商業機 ,你需要企業微調工具,你要合虧審搜審查 ,要日致追蹤,要權限管理,呢個時候免費 型只系第一步後面真正收錢嘅地方係魂,係 算力,係工具,係企業務,資料入面有個詞 出現得好物,k平臺同Argetic AI,即係 你可以將你嘅model像成另一個高度定 化嘅虛以工廠,唔係嚟買一套 software,而係租用呢個兵廠用自 己嘅數據訓練同組裝一批最用嘅AI員工。 至於AI,講白啲就係有行動力嘅AI,佢

6:15 唔係淨係搭今日天氣點,而係你同佢講幫我 安排一場巴黎 會議,佢可以自己查力睇機票發甚至流酒店 呢個就唔在嘅checkboot,呢個係 真係可以落手落腳做嘢嘅AIagent, 但喺業入面部署呢種級別嘅AI,靠部本地 電腦根本唔實,你一定要上運,而當你用緊 免費嘅箍,又需要龐大力將佢變成真正嘅, 最順你成將嘅服務商就係阿裡,呢個好似阿 裡免費送你一架頂級跑車,車係免費,但車 要加佢特製嘅航空,要保養、要調教要賽道 全部都喺阿裡工廠入面做,你架車跑得越快

7:03 ,交油費就越多,資料入面嘅數據幾美 studio客戶基爭咗8倍,開降低咗企 業使用門檻,但只要企業用出效果就好容易 轉化成裡真金嘅力消費。所以開唔係喺送禮 ,佢係一個漏鬥用免費模型,叫動極之昂嘅 機噉下一個問題係阿裡打算將呢套係賣俾邊 個,答案就要睇佢海報局點解 唐州講呢套景,點解唔去谷開發佈會,點解 偏要喺巴黎BFTA對住歐洲市場推嘅全

7:50 AI戰略,因為歐洲而家好慮,科技焦慮, 歐洲人好清楚,AI係下一次人工業革命心 ,但一望出去雲機底抵層晶片先進AI大型 ,基本上都掌握喺幾間美國科技頭手上,歐 洲唔係完全冇AI公司,例如就係一個代表 。但喺龐大基礎設施層面,歐洲仍然有好大 真空,歐洲政策製定者同大型企業,對科技 主嘅渴望已經去到一個前所未有嘅高度,佢 哋好驚自己 時代徹底變成用資料入面提到,蔡遜講前一 日,亞ဝ雲喺巴黎正式推出咗一個新雲區,

8:36 入面包括兩個區呢個詞聽落好似公關克話, 但喺世界見一個新可絕對唔係幾排ser咁 簡單,你要買地你要數據中心你要份型你要 鋪壓電網同,你要建立物理上完全隔離嘅數 據保,阿裡喺巴黎樂重只有一個,向歐洲證 明,你嘅數據可以留喺歐洲本 跨過大西藥呢張牌。好準,因為歐洲最重視 嘅就係dataprivacy同 compliance,你可以惗而家歐洲 棟大廈都接住一個巨大美國電影,暫時用得 好好但始終覺得命脈喺人哋手上,驚有一日

9:24 被人拉 黎,喺佢哋後院見一座獨立法電站,蔡遜同 歐洲人講,你哋用中國技術取代技術啦,呢 個唔真正嘅係一個planB一個第二選擇 一個緊急被險嘅被胎,當然你可能會問面對 咁複雜嘅全球政治,歐洲大型企業真係會放 心將心業務物交,呢度就涉及一個好現實嘅 商業,業[音樂]殘判黑森,從來唔係八份 百信任,而係桿。對歐洲嚟講,佢哋未必需 要完全擁抱雲,佢哋只需要喺市場入面引入 一個有足夠實力嘅競爭者,增加自己而家能

10:10 力當你有第二個選擇,你面對美國嘅時候, 戰略旋間就大好多,呢個就係阿裡捕捉到嘅 生態我唔一定要做你唯一供可以做建立技術 人性防止被單一傷卡死嘅籌碼再加上箍溫泉 開本地理機 龜牌打得非常精準講到呢度好宏大歐洲報局 亦聰明但而家要由巴黎浪漫嘅科技南拉翻去 最現實體呢套全AI邏輯底可唔可以轉化成 真金白人呢個先係最 開頭講過阿理自由現金流出466億人民幣 ,但你知唔知上一年同期係幾多?上一年同

10:58 期自由現金流 入738億一中間差咗超過1000億建物 理數據保 免費開 貼錢買server買片交費更加全部都係 錢呢個其實就係資本市場而家最 甚至有AI具頭嘅地方要明白呢466億嘅 血就要刷你階段嘅四級火箭邏輯第一級火箭 係無型礦扇,即係透過開 夥箭係超,將免費用無 客戶,呢兩[音樂]就係前面港嘅漏鬥邏輯

11:45 但阻力喺邊阻力在於跑通呢套漏鬥之前,你 要先落重嘅資產投入 現金流出你可以當係起一座超級賭場嘅成本 ,賭場都未正式開,已經先駛曬出去,你要 先喺最靚嘅酒店,買入幾萬臺ser清晶片 費、電費、機成本所有成本都發生喺第一個 真正島賭客想排之前去到第二跨第三級磨擦 力就更大,第三級火箭係辨現,阿裡A深度 接入徒保, 促成交易同工作流程從扣但資料入面提到一 個隱

12:36 貪新鮮,用嚟寫手話將能身鮮感過咗就未必 日日都用如果連流都做唔到咁,第四級火箭 亦即係最關鍵嘅財務回報就好難講,你可能 會話但係阿裡產品收入唔係已經連續11個 季道三位數增長佔比亦去到38成左右,冇 錯,促係靚問題係呢部分高質收入嘅絕對規 模,唔夠背後極之龐大嘅機件,接同算力開 始,如果cover唔到呢個 businessmodel就未成立,如 果自由現金流唔能夠盡快回正資本市場就會 好冷,將嗰億為一個巨大成本黑動,而係一

13:22 條 增長曲線呢個就係四級火箭隨時解體嘅高位 ,所以總結呢份資料最核深嘅信息係。阿裡 巴巴而家正用一種近破嘅方式,重自己嘅身 份,佢用50萬億美元है,重新定義市場 邊界,用fullst部局同平台搭見AI 工廠,用QAN開造前 ົ亮入口,再入歐洲科技焦慮嘅隙,嘗試國 投之外嗰個一可 大戰略最後都要翻到一個好冷嘅財務指標上 面接受驗自由現金流呢場型戰唔只係對未來 認知嘅比拼,更加係一場殘酷嘅現金消耗戰

14:11 ,唔止阿裡,其實成個全球AI產業而家都 喺經歷呢種集體震痛,所以下次再睇到新聞 鋪天地話,某戴無形喺奇怪跑又贏咗對手或 者某間大廠又發佈咗幾天嘅AI影片生成功 能,唔好淨係比面而熱鬧呃到你要冷靜啲有 個公關術,睇佢冇收入有冇真增長,睇住佢 裁報入面嘅自由現金流,因為AI下半場, 真正可以留喺排桌上嘅,唔一定係無型跑最 高果個,而係喺邊個最先頂得著龐大資本開 ,將技術真正變成正向金流,撥開啲光先嘅 技術標添最抵

14:56 寵力定律,其實從來冇變過,最後留一個問 題俾大家諗,我哋頭先講到:歐洲因為深科 技慮,所以好想到美國科技頭之外嘅第二選 擇,阿裏就試圖將自己嘅運服務同AI機入 呢個生態位,但係如果你睇返而家近瘋狂嘅 消錢速度,一年幾十億甚至美元級別嘅現金 流出,最後呢個地球上可以活落嚟嘅底AI 機件供應商會剩低極少少數最有錢嘅超級寡 頭,咁到未來,當AI基礎設施徹底變成兩 三間頭 革,今日我哋講嘅,所謂多元化鼻胎、 planB會唔會最後都只係人類面對呢個

15:41 龐大疑未知嘅智能系統,一個無可內何嘅退 露,呢個問題就留你自己慢慢諗,最後進入 我自己嘅技術分析,打開阿裡巴巴九八,今 6月22號,噉同大家睇嘅系98,咁今日 98呢就差唔多做咗個低位出嚟㗎喇,就係 蚊之前嗰個位呢係都差唔多幾多嘅啫咁睇返 目前current現價喺52high同 low而家嘅位置就係差唔多破㗎喇,但係 未破嘅。咁最近90日成個設已經去咗46 㗎喇咁差唔多仲有4個啱好就要 恆子一年呢,就係差咗負嘅咁最近成個月呢

16:31 就同行紙比呢係差咗12個啦咁,今日呢, 仲同大家做咗一個叫做週 期嘅分析呢係去到四五嘅,即係仲有四日先 到嘅咁呢個今日嘅收價錢就係102蚊9毫 ,咁最近呢比較誇張就係成個918差唔多 最近一個月啦係跌咗19%㗎喇,咁呢邊呢 啲比較複雜嘅咁大家就唔使睇啦,咁呢啲菠 率嘅呢啲,因為其實必都係一個比較短嘅時 間,咁其實就第一個其實係記一個月已經跌 咗19個咁呢邊都唔使特別睇嘅,因為時間

17:17 係比較短嘅咁第一就係話最近跌咗啦單日月 11號最跌咗㗎喇咁今日嘅Dayolow 呢就係100蚊咁之前舊年7月份嘅DO呢 係100蚊嘅咁其實都好無分別㗎咁呢邊就 一路同大家過去啦咁呢邊會一個叫其 單兒嘅咁大家嘅APP同APP都有㗎啦咁 下嘅地方就係話佢淨係可以睇到呢幾日嘅大 咁,其實呢啲大單都唔係特別大嘅啫就只能 夠做一個區間性嘅參考,咁一個比較重點嘅 就係呢會有一個成交量同埋買嘅分佈啦咁第 一個就係Core嘅應

18:04 大家去睇返就係蚊。而 半嘅呢個位置咁佢嘅成交量咧就係最大嘅呢 個位置,同埋成交額就係會最大嘅咁所以其 實有幾個關鍵就係話一個位置就係係 102.5啦咁睇一個位置啦,咁第二個就 係一個put嘅期 乘量係5602 嘅咁呢個係四啦咁跟住幾嘅話呢,應該加上 去或者會變㗎啦咁成個成交喺呢度咁基本上 就係話有三個點位啦咁,第一個就係呢個 100蚊仲有嘅呢個.5仲有C嘅呢個

18:50 105,基3個位出嚟㗎呢邊亦都會有一個 巴同分布圖啦,就係呢三個點嘅咁大家亦都 會睇到呀嚇。呢個呢個位置嘅成交係最多嘅 咁102啦就夾咗喺中間,咁105呢。就 喺嗰度就基本上喺大概率啦,今個星期嘅價 格嘅運行呢,就會夾咗喺呢三個價位區間嗰 度㗎啦。咁其實呢邊會睇到啦咁誒做咗一個 為蚊嘅成交量係最多嘅咁,但係觀眾想知道 嘅就係話咁呢一個入邊係買嘅定係賣嘅。因 為呢度有5600幾張嘅,咁佢體係買幾多

19:36 呢,同埋買賣幾多,因為我都睇唔到嘅呢個 數據目前冇咁嘅level好睇到,咁有人 可以睇到啦,咁我話真係睇唔到嘅整體嚟一 個誒點樣判斷方向呢就睇返最近嘅一啲叫做 期有面移動嘅資金流啦咁呢邊亦都會睇到話 今日組盤嗰陣時呢係會做咗一啲sell嘅 動作啦咁呢邊亦都係做一啲sell嘅動作 啦咁呢邊亦都會有一啲做咗買嘅動作嘅咁大 家可以單咁參考一下就知道有一個咁嘅點位 喺度同埋關注返最近落嚟四日嘅一啲期權 嘅單嘅情況啦咁提之後呢就set呢個同牛 偶同大家睇返成個998嘅一個

20:22 嘅一個位啦咁將成個升浪嘅點位呢就去返舊 年1月份啦,即係75蚊左右啦,75蚊拉 到105咁最近都係一路跌㗎啦,3八啲 50啲㗎啦六一啲啦,差唔多到78㗎啦, 咁七八幾多咧98蚊98蚊啊參考嘅咋咁睇 返之前喇,就今日係做咗一個。百零八啦。 咁之前嗰個位呢?即係舊年7月份呢?係 107嘅咁本質上呢即係冇乜冇乜冇乜 cre別嘅唧,咁多Donald 75,咁用呢個range嘅去睇返成個嘅

21:11 價格變喇,即係參考嘅唧,咁如果係要跌破 嘅咁基game基上都係穿曬㗎喇咁睇完咗 呢個啦咁用返平時誒開嘅三條線啦咁正常嘅 都係短系日啦咁呢排都係一直都喺日線下面 㗎啦咁高位都係一個頂,邊畀一個頂要低咁 一個 抵㗎咁如果係話大家要企嘅話咁先睇啦 咁亦都係未到嘅咁啱好啦亦都係 嘅。咁一個左位咁第二個左位就係一24啦

21:56 睇返支各位喇就係 呢度喇,係啦107呢邊就係92呢邊就係 74咁如果係迷啲講法啦咁打個半即係大概 到93即係由呢度9亞呢個位置差唔多係打 半節嘅嗰個位喇咁唔知有冇咁嚟土啦嚇成? 唔一定喇咁到嘅話都有個心理準備啦,如果 有貨嘅朋友。咁睇返今日嘅成個成兩啦咁今 日係綠色啦,綠色啦。但都未上到去嘅咁下 邊睇 md喇有喺下邊㗎啦 噶。咁你話有冇一啲特別嘅方式去睇呢個呢

22:46 咁一個嘅真係好簡單睇每一日嘅價位,呢一 1人一日一日一日一日過一日㗎啦咁呢個就 係非直接㗎,最緊股價真係一日低一日。1 日一日一日,日game基本上都係每一日 都可以低過一日嘅咁好犀利喇咁巴 咁睇完呢度之後咧翻個咁頭先同大家講嘅一 個叫做期分析啦咁呢個期分析呢咁簡單嚟睇 翻上面就會一個 睇呢度度先即係6月號嘅,即係頭先嗰個同 大家summary嘅嗰個表呢咁game 基game基本上嘅data呢都係嚟自呢 度㗎啦咁簡單睇啦咁先睇,第一個簡單啲啦

23:34 咁,先睇成啦咁,證明一百蚊呢個位啦,成 量就係最多㗎喇。咁第二個位置呢就係蚊二 半咁呢個位啦咁第三個位呢就係105嘅咁 大家就會見到啦呢邊係call啦咁呢邊係 啦,咁你實質上呢我同大家亦都唔知知道, 究竟係邊啲係BYore啦邊啲係啦。咁所 以呢個係比較重要嘅咁。咁第二個就係話有 一個誒 分析啦咁呢邊亦都係簡單啲啦咁一睇就知道 今個星期重要嘅價格就係喺100蚊啦。誒 咁嘅,咁呢三個位置啦。呢三個位置呢三個 位置去睇嘅咁仲有第2個就係話點樣睇成一

24:19 個誒權啦咁呢邊會一個期權嘅咁到期亦都係 去到四5嘅咁呢邊目前嘅成個期權以動嘅情 緒呢都atleast啦嚇atleast 係睇到喇咁睇返啲頭先所講嘅關鍵位啦即係 100蚊呢個位咁呢度係有嘅咁但係佢呢度 呢個put呢係做put呢就係變多嘅咁但 係頭先睇到嗰度嘅成交量其實係有五千幾嘅 咁究竟呢五千幾呢係呢個sell嘅多啦呢 個buy嘅啦咁,我亦都係睇唔到啦咁成冇 咁嘅權限啦咁,所以其實大家係可以關注返 呢幾日成個期權嘅情況啦咁even啦甚至 可以去到

25:05 BBA嗰度兩邊作為一個參考嘅咁呢邊係一 個誒嘅數據嚟嘅唧。咁再睇返一個週線喇咁 雖然今日線都未到啦簡單一眼啦咁今星就誒 呢個位置波嘅嚇睇下午之後呢,可唔可以夾 返上去咁其實105係邊個位呢?105就 係呢個位啦,係呀。105就係呢個位啦。 咁如果睇返一個預線啦。即係真係好難睇。 1二三四五。即係連跌咗七八個月㗎啦線真 係好難睇啦。咁成個月線呢度呢咁呢度出咗 條所謂嘅黃色啦咁,簡單下啦七呢啲都唔係

25:51 啲咩資線嚟嘅咁簡單睇下成個貴線嘅成個啦 咁,基本上呢都 睇成個形態啫底一個底,畀一個底 㗎喇,咁呢個底又系咁但係成個季度未結束 啦咁簡單feel成個形啦咁呢邊就係巴嘅 連線啦,咁今年亦都係未結束嘅,咁舊年就 升得好勁啦。舊年呢升得好勁喇咁今年可唔 可以仲有半年啦,睇唔可以回返上去啦咁, 基上其實後尾呢啲睇都冇咩意義嘅冇咩意嘅 ,除非大家係選՞一啲呢就可以參考一下或 者開頭揀股票嘅時候呢,就可以參考一下, 咁巴百嚟講最大就係啦,咁上邊嘅呢啲人啦 仲未解嘅呢個就係選股票最大嘅二啦。然之

26:41 後呢邊就係 日線啦,係喇,日線咁成個基上巴都係最近 就一路上落去㗎喇咁最後summy,咁關 注嘅位就係話知道之前低就係一7啦咁之後 就係90啦,咁相到嚟講92呢其實就係 1886嘅腰斬嘅位置喇,即係1860除 左右啦咁嘅位置嘅咁同埋再返個星期五嘅誒 週渡期權最後收判嗰一下究竟係落邊個位置 呢?係落啦。一百蚊啦 定係話?105嘅,咁跟住嗰四日啦咁大家

27:28 冇咩做嘅話咧,就可以去focus返動呢 個位啦,無論係一百啦同埋啦咁,簡單呢個 市場 兇呀咁,其實呢邊呢都攻嘅啫,因為錢唔係 特別多嘅成 ತ್一百蚊 哩度亦都係啦,output咁嘅邏輯就係 話只要跌100蚊啦咁呢啲人呢都會去願意 去接貨啦咁就係最近嘅支撐啦咁如果大家覺 得今日share嘅可以幫到你嘅話呢記得 Scomment同埋subscribe

28:14 啦咁我哋下期節目再見拜拜。

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