Dalio's Latest Warning: Don't Get Carried Away by AI, Real Returns on US Stocks in the Next 5-10 Years Could Be -5% to -10%

marsbit發佈於 2026-06-17更新於 2026-06-17

文章摘要

Ray Dalio, founder of Bridgewater Associates, warns investors against excessive concentration in AI stocks. He argues the current market, dominated by a few AI giants, mirrors historical patterns where revolutionary new technologies lead to high risk, volatility, and uncertainty. While acknowledging AI's transformative potential, Dalio emphasizes that most investors fail at this stage of the cycle by over-concentrating in a handful of leading companies. He cites inherent risks: companies cannot accurately forecast investment needs or external shocks (e.g., monetary policy, geopolitics, taxes), face potential disruption from future technologies and international competition (notably from China), and experience significant price swings. Dalio's core advice is diversification, calling it his "Holy Grail of Investing." He presents a mathematical case that a well-diversified portfolio of 15-20 uncorrelated, good bets offers a superior risk-adjusted return compared to a concentrated position. Dalio also offers a cautious outlook, suggesting U.S. stocks may deliver real returns of -5% to -10% over the next 5-10 years based on valuation and bubble indicators. He concludes that in the face of high uncertainty, the prudent strategy is not to avoid betting entirely, but to avoid large, concentrated bets where one lacks sufficient informational edge. Instead, investors should build a strategically balanced, diversified portfolio.

Author: Ray Dalio

Compiled by: Deep Tide TechFlow

Guide: Bridgewater founder Ray Dalio posted an investment note on X, doing the math on the current market dominated by a few AI giants. His judgment is tough: high risk is a fact, low returns are an opinion—the real returns on US stocks over the next 5 to 10 years could be in the range of -5% to -10%. He's not telling you not to buy AI; he's advising you not to put all your chips on AI. This is the 'Holy Grail of Investing' he has summarized over more than 50 years, and now he's sharing it publicly with everyone.

Investment Principles: How to Play the Hand You're Dealt

This note is about how to play the game of investing in the current situation.

You can think of it like bridge, poker, backgammon, or chess. It's your turn to move, and there's a computer next to you helping you assess the situation and make suggestions. For me, investing feels like that. Whether you have that computer or not, I think you should ask yourself one question: given how the cards are laid out now, what move should I make (i.e., what are the current market's characteristics and what forces are influencing it).

I've played this game for a long time. At this stage, my goal is to pass on my way of playing and, going a step further, to create a platform where all sorts of people can use it to explore the subject of investing, however they like—to learn, to look back at what they would have done, and to do it well. I believe there are right and wrong ways to play the hand you're dealt. So when you encounter a specific situation, you should ask yourself: 'How should I bet in this situation?' and be able to give a reliable answer.

Below, I want to talk about what the market looks like to me now, and what I think should be done (which is also what I am doing).

How to Play This Round Now

What are the most critical conditions today, and how should you bet on them?

In my view—and probably in everyone's view—we are currently in a market where a very small number of companies, concentrated in a sector with astonishing new technology (mostly AI), are dominating the direction of the entire market. These companies account for a high proportion of market capitalization and have a huge impact on the market and the economy. It's the same every time this happens: the new technology sector is filled with great excitement, uncertainty, and volatility, and these emotions spread to global stock markets. Therefore, the ups and downs and uncertainty of this sector are of great significance.

Beyond that, there are several other equally important major variables, what I call the 'Five Great Forces': 1) what's happening with debt and money, 2) what's happening with political and social issues (which significantly affect taxes and other politically-driven market factors), 3) the impact of geopolitics on markets (like those wars), 4) what's happening in the natural world, and 5) what's happening with new technologies. I feed these conditions into my investment system, and it calculates how to bet on them, while I'm also thinking about what to bet on.

When considering how to bet, the most important question to ask and answer clearly is: Do you want to a) bet more heavily on the new technology than the market index (like the S&P 500) already implies, overweighting this sector or the few companies you think are best; b) maintain a weight roughly similar to the index; or c) diversify away from this concentration?

Almost everyone wants to own the best assets and is desperately trying to do so, and this new technology in front of us seems to be changing almost everything. But history tells us that at this stage of the cycle, putting a high proportion of chips on the few leading companies producing this technology has failed for the vast majority of people. There's logic behind this, and it's played out this way every time in the past. AI is indeed a unique new technology, but there have been many unique new technologies in history that can serve as references. You should look at them. If you choose to ignore them, you need a good reason explaining why this time is different.

The Risk Is Indeed High

The stories of all great new technologies in the past have played out the same way, for the same reasons. High risk combined with great uncertainty is inherent to these new technology companies. Looking back at their performance in similar situations, you'll find that even revolutionary companies that ultimately succeeded in the long run (like Microsoft and Apple) got beaten to a pulp at similar junctures. And in the present moment of a new technology company's emergence (not in hindsight), it's simply not easy to tell who will succeed and who will fail; IBM is an example. Looking at all these cases laid out, you'll understand that high uncertainty about the future is the nature of new technology companies.

For example, they either invest too much or too little. The reason is: not investing enough guarantees failure, but they can't predict the future precisely, so they can't know if they're overinvesting. Both over- and under-investing come at a cost.

They also can't accurately foresee all the changes that will affect them, including exogenous ones—monetary tightening, war, dramatic tax changes. So they all go through huge ups and downs, first exciting investors, then terrifying the faint of heart and washing them out, thereby amplifying market volatility. Digging a layer deeper: these new technologies and companies, which disrupted their predecessors, will ultimately be disrupted by newer technologies and companies themselves, in ways that are unthinkable now. We have to consider whether the same thing could happen to today's companies. The impact of quantum computing is one of the 'known knowns'. What about those not yet imagined?

What about the risk from competitors? For example, China is producing and distributing AI technology, and Chinese policymakers have a completely different view of the economy and AI. We are in a new technology war, and leaders of each country believe they must win. From China's perspective, because AI has huge productivity dividends and can raise the overall standard of living, it should be provided free or at low cost to the public. In their view, profit is less important; the overall benefits from many people using these new technologies are what matter. I expect them to compete in the international market just as they have with products like cars, solar panels, and batteries.

The current situation resembles many historical moments that can give us lessons. I can't help but think of the late Dutch Empire and the early British Empire, the period when Britain surpassed the Netherlands in shipbuilding and other important industries. Also, geopolitical conflict surrounding Taiwan, which should at least make us consider the possibility: could China use 'preventing chips from leaving Taiwan' as a tool in geopolitical competition? AI stocks face other risks, such as the risk of wealth taxes and other taxes rising—which could force people who have a lot of wealth tied up in these stocks to sell; or rising anti-AI sentiment, which could impose restrictions on companies' expansion.

I could list a bunch of other things to worry about, and I could also list an equally long list of great AI opportunities I'd like to bet on. I'm not saying how these risks will turn out, nor am I saying you shouldn't buy AI companies. I'm just saying that there is a large amount of concentrated risk in the market—that's indisputable—and you should know how to play in such a situation. Based on my research of all similar cases, and out of logic, I am confident that the risk is high, and the best way to play this situation is:

Diversification Is Good

You probably know my mantra is diversification. My 'Holy Grail of Investing' is to try to hold 15 good, uncorrelated, risk-balanced positions. To put it another way:

"A well-diversified portfolio of good bets will outperform a concentrated bet (it has a higher return-to-risk ratio and can be engineered to produce better returns at the same level of risk). The more risk is concentrated in one part of the market, the more you should diversify, especially when the market is driven by a revolutionary new technology that inherently brings great uncertainty."

This is not an opinion; it's a mathematical certainty. For example, assume a bet has a return-to-risk ratio of 0.3 (e.g., 6% return with 18% standard deviation, which is typically considered the level for stocks), and compare holding 5, 10, 15 uncorrelated bets: I can achieve the same 6% return, but the risk measured by standard deviation drops to 8%, 6%, and 5%, respectively. That is, 15 good uncorrelated investments can improve my return-to-risk ratio by 4.3 times (from 0.3 to 1.29). You can also add leverage if you wish, achieving much higher returns at the same level of risk. This is a fact.

My confidence comes from backtesting, from the real returns I've delivered over more than 50 years of investing, and from the largely solid logic: a well-diversified set of bets, adjusted to one's desired level of volatility, will produce much better returns over time than the concentrated bets most investors prefer. To be more specific, good diversification can give you a better risk-return ratio than any concentrated bet; adjusting it to your desired risk level allows you to achieve higher returns at that risk level than with any other approach.

Because I've made this method public, it has now become my 'no longer so secret' recipe for success. But I rarely encounter people who think about investment strategy this way—that is, few people think about portfolio construction, about how a well-structured, well-diversified portfolio of bets would perform compared to a concentrated position in a few stocks in a great transformative industry. Most people only think about whether these stocks, this industry, will go up, and how to bet. The performance gap between those who think about portfolio construction and those who don't is huge. I'll have a chance to explain this more fully later.

Based on all of the above, in my view, pondering how to play the current hand should lead one to ask oneself: How large should my concentrated positions be? And then, diversify.

Returns Appear Low

High risk is an indisputable fact. Next, I'll give you an opinion that could be wrong: expected returns are low. This judgment comes from my analysis of valuations and the readings of my bubble indicators—over the next 5 to 10 years, the real returns on stocks look to be about -5% to -10%, though there is considerable uncertainty around these numbers. In my view, these stocks are very long-duration assets with significant risk because it's difficult to reliably see the distant future, and they appear both expensive and in shaky hands.

A Question from My Research Team

At a recent meeting, someone on the team asked me: Why do you think the market's current configuration is wrong? How do you know that the lack of diversification in the market today isn't for good reasons—for example, some investors believe the expected returns on AI stocks are very high; for example, when an industry accounts for such a high proportion of market capitalization, such concentration in an index is natural; or, when there is extreme enthusiasm for an industry, many investors buy these stocks without doing the smart, reliable math to figure out what future earnings will be and how those earnings should be priced?

My Answer

Prices rise for all sorts of reasons, not all of them good. Some investors watch prices and push them up because they think prices are attractive relative to fundamentals; some hold these stocks because they are convinced it's a great new technology and take rising prices as confirmation that 'these are good stocks'; and other investors hold index exposure, passively placing heavy weight on these stocks. In my opinion, you can agonize over these issues, trying to figure out what to do; or you can admit that you don't need to agonize at all because you simply don't have enough information to bet confidently. You can perfectly well say, 'I don't know enough, I won't take this bet.' And then actually not bet.

What gets people into trouble is the thought that 'I must have an opinion, and my opinion is worth something,' when the reality is more likely that you simply can't form a view reliable enough to bet on. (Note: To be clear, I'm not recommending not betting—you can't avoid betting anyway because you always have to put your money into some investment, or into cash, and most people think cash has the lowest risk, when it's actually the worst long-term investment. I recommend understanding how to diversify bets well, even if you have no tactical view on which markets are good or bad. The approach is: when you have no confident tactical judgments, hold a balanced, strategic asset allocation portfolio. But that's a topic for later.)

So I believe that knowing what you don't know, and thus deciding when not to bet, is as important as knowing what you do know and betting accordingly.

To put it more simply, I believe in this principle: since it's usually difficult to have enough information to justify concentrated bets, the best approach is to form a diversified portfolio consisting only of your most confident, uncorrelated bets, and then engineer that portfolio to your desired risk level. That's my 'Holy Grail of Investing.'

Right now, facing the current hand, I don't think anyone can know clearly enough what will happen next in this technology-driven market to make a large, concentrated bet. In my view, avoiding concentration and staying diversified is the best way to deal with this 'not knowing.' I know this contradicts the theories you read in textbooks—textbooks basically say markets are efficient, so you should 'just believe in the market.'

To summarize: We currently have an unusually concentrated market centered around a revolutionary new technology, which should precisely remind us not to confuse excitement about the new technology with the attractiveness of new technology stocks, and then throw caution to the wind to hold a bunch of high-risk, highly correlated concentrated bets—especially when we could achieve similarly attractive returns at much lower risk through smart diversification.

P.S. I won't share my holdings or tactical judgments with you, because I don't want to be your investment advisor. But I will soon share some key perspectives behind these judgments, including the readings and logic behind my bubble indicators.

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相關問答

QWhat is Ray Dalio's key warning about investing in the current AI-dominated US stock market?

AHe warns investors not to be carried away by the hype. He argues that future 5-10 year real returns for US stocks could potentially be negative, in the range of -5% to -10%, and advocates for diversification over concentrated bets on AI stocks.

QAccording to Dalio, what is the 'Investment Holy Grail' he has developed over 50+ years?

AHis 'Investment Holy Grail' is to seek a well-diversified portfolio of about 15 or more good, uncorrelated bets, which can be engineered to achieve a significantly better return-to-risk ratio compared to any concentrated bet, especially in a high-risk environment.

QWhat are the main risks Dalio identifies for AI and technology stocks in the current market?

AThe main risks include: inherent high uncertainty and volatility of revolutionary new tech companies; geopolitical risks (e.g., competition from China, potential Taiwan conflict affecting chip supply); risks from changing policies (e.g., wealth taxes, anti-AI sentiment); and the historical pattern where most new tech leaders get disrupted or experience severe downturns.

QHow does Dalio respond to the argument that the market's current concentrated allocation to AI might be justified?

AHe disagrees, stating that price increases can happen for various reasons, not all good. He argues that many investors lack sufficient information to form a confident, justifiable view for a concentrated bet. Therefore, the best approach is to admit what you don't know and diversify, rather than feeling pressured to have an opinion.

QWhat is Dalio's core advice for investors facing the current 'hand' of the market?

AHis core advice is to prioritize diversification. He believes it is mathematically superior to hold a portfolio of uncorrelated good bets. Given the high concentration and uncertainty driven by revolutionary AI technology, avoiding concentrated positions and maintaining a well-diversified portfolio is the best strategy to manage the 'not knowing'.

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什麼是 $S$

理解 SPERO:全面概述 SPERO 簡介 隨著創新領域的不斷演變,web3 技術和加密貨幣項目的出現在塑造數字未來中扮演著關鍵角色。在這個動態領域中,SPERO(標記為 SPERO,$$s$)是一個引起關注的項目。本文旨在收集並呈現有關 SPERO 的詳細信息,以幫助愛好者和投資者理解其基礎、目標和在 web3 和加密領域內的創新。 SPERO,$$s$ 是什麼? SPERO,$$s$ 是加密空間中的一個獨特項目,旨在利用去中心化和區塊鏈技術的原則,創建一個促進參與、實用性和金融包容性的生態系統。該項目旨在以新的方式促進點對點互動,為用戶提供創新的金融解決方案和服務。 SPERO,$$s$ 的核心目標是通過提供增強用戶體驗的工具和平台來賦能個人。這包括使交易方式更加靈活、促進社區驅動的倡議,以及通過去中心化應用程序(dApps)創造金融機會的途徑。SPERO,$$s$ 的基本願景圍繞包容性展開,旨在彌合傳統金融中的差距,同時利用區塊鏈技術的優勢。 誰是 SPERO,$$s$ 的創建者? SPERO,$$s$ 的創建者身份仍然有些模糊,因為公開可用的資源對其創始人提供的詳細背景信息有限。這種缺乏透明度可能源於該項目對去中心化的承諾——這是一種許多 web3 項目所共享的精神,優先考慮集體貢獻而非個人認可。 通過將討論重心放在社區及其共同目標上,SPERO,$$s$ 體現了賦能的本質,而不特別突出某些個體。因此,理解 SPERO 的精神和使命比識別單一創建者更為重要。 誰是 SPERO,$$s$ 的投資者? SPERO,$$s$ 得到了來自風險投資家到天使投資者的多樣化投資者的支持,他們致力於促進加密領域的創新。這些投資者的關注點通常與 SPERO 的使命一致——優先考慮那些承諾社會技術進步、金融包容性和去中心化治理的項目。 這些投資者通常對不僅提供創新產品,還對區塊鏈社區及其生態系統做出積極貢獻的項目感興趣。這些投資者的支持強化了 SPERO,$$s$ 作為快速發展的加密項目領域中的一個重要競爭者。 SPERO,$$s$ 如何運作? SPERO,$$s$ 採用多面向的框架,使其與傳統的加密貨幣項目區別開來。以下是一些突顯其獨特性和創新的關鍵特徵: 去中心化治理:SPERO,$$s$ 整合了去中心化治理模型,賦予用戶積極參與決策過程的權力,關於項目的未來。這種方法促進了社區成員之間的擁有感和責任感。 代幣實用性:SPERO,$$s$ 使用其自己的加密貨幣代幣,旨在在生態系統內部提供多種功能。這些代幣使交易、獎勵和平台上提供的服務得以促進,增強了整體參與度和實用性。 分層架構:SPERO,$$s$ 的技術架構支持模塊化和可擴展性,允許在項目發展過程中無縫整合額外的功能和應用。這種適應性對於在不斷變化的加密環境中保持相關性至關重要。 社區參與:該項目強調社區驅動的倡議,採用激勵合作和反饋的機制。通過培養強大的社區,SPERO,$$s$ 能夠更好地滿足用戶需求並適應市場趨勢。 專注於包容性:通過提供低交易費用和用戶友好的界面,SPERO,$$s$ 旨在吸引多樣化的用戶群體,包括那些以前可能未曾參與加密領域的個體。這種對包容性的承諾與其通過可及性賦能的總體使命相一致。 SPERO,$$s$ 的時間線 理解一個項目的歷史提供了對其發展軌跡和里程碑的關鍵見解。以下是建議的時間線,映射 SPERO,$$s$ 演變中的重要事件: 概念化和構思階段:形成 SPERO,$$s$ 基礎的初步想法被提出,與區塊鏈行業內的去中心化和社區聚焦原則密切相關。 項目白皮書的發布:在概念階段之後,發布了一份全面的白皮書,詳細說明了 SPERO,$$s$ 的願景、目標和技術基礎設施,以吸引社區的興趣和反饋。 社區建設和早期參與:積極進行外展工作,建立早期採用者和潛在投資者的社區,促進圍繞項目目標的討論並獲得支持。 代幣生成事件:SPERO,$$s$ 進行了一次代幣生成事件(TGE),向早期支持者分發其原生代幣,並在生態系統內建立初步流動性。 首次 dApp 上線:與 SPERO,$$s$ 相關的第一個去中心化應用程序(dApp)上線,允許用戶參與平台的核心功能。 持續發展和夥伴關係:對項目產品的持續更新和增強,包括與區塊鏈領域其他參與者的戰略夥伴關係,使 SPERO,$$s$ 成為加密市場中一個具有競爭力和不斷演變的參與者。 結論 SPERO,$$s$ 是 web3 和加密貨幣潛力的見證,能夠徹底改變金融系統並賦能個人。憑藉對去中心化治理、社區參與和創新設計功能的承諾,它為更具包容性的金融環境鋪平了道路。 與任何在快速發展的加密領域中的投資一樣,潛在的投資者和用戶都被鼓勵進行徹底研究,並對 SPERO,$$s$ 的持續發展進行深思熟慮的參與。該項目展示了加密行業的創新精神,邀請人們進一步探索其無數可能性。儘管 SPERO,$$s$ 的旅程仍在展開,但其基礎原則確實可能影響我們在互聯網數字生態系統中如何與技術、金融和彼此互動的未來。

91 人學過發佈於 2024.12.17更新於 2024.12.17

什麼是 $S$

什麼是 AGENT S

Agent S:Web3中自主互動的未來 介紹 在不斷演變的Web3和加密貨幣領域,創新不斷重新定義個人如何與數字平台互動。Agent S是一個開創性的項目,承諾通過其開放的代理框架徹底改變人機互動。Agent S旨在簡化複雜任務,為人工智能(AI)提供變革性的應用,鋪平自主互動的道路。本詳細探索將深入研究該項目的複雜性、其獨特特徵以及對加密貨幣領域的影響。 什麼是Agent S? Agent S是一個突破性的開放代理框架,專門設計用來解決計算機任務自動化中的三個基本挑戰: 獲取特定領域知識:該框架智能地從各種外部知識來源和內部經驗中學習。這種雙重方法使其能夠建立豐富的特定領域知識庫,提升其在任務執行中的表現。 長期任務規劃:Agent S採用經驗增強的分層規劃,這是一種戰略方法,可以有效地分解和執行複雜任務。此特徵顯著提升了其高效和有效地管理多個子任務的能力。 處理動態、不均勻的界面:該項目引入了代理-計算機界面(ACI),這是一種創新的解決方案,增強了代理和用戶之間的互動。利用多模態大型語言模型(MLLMs),Agent S能夠無縫導航和操作各種圖形用戶界面。 通過這些開創性特徵,Agent S提供了一個強大的框架,解決了自動化人機互動中涉及的複雜性,為AI及其他領域的無數應用奠定了基礎。 誰是Agent S的創建者? 儘管Agent S的概念根本上是創新的,但有關其創建者的具體信息仍然難以捉摸。創建者目前尚不清楚,這突顯了該項目的初期階段或戰略選擇將創始成員保密。無論是否匿名,重點仍然在於框架的能力和潛力。 誰是Agent S的投資者? 由於Agent S在加密生態系統中相對較新,關於其投資者和財務支持者的詳細信息並未明確記錄。缺乏對支持該項目的投資基礎或組織的公開見解,引發了對其資金結構和發展路線圖的質疑。了解其支持背景對於評估該項目的可持續性和潛在市場影響至關重要。 Agent S如何運作? Agent S的核心是尖端技術,使其能夠在多種環境中有效運作。其運營模型圍繞幾個關鍵特徵構建: 類人計算機互動:該框架提供先進的AI規劃,力求使與計算機的互動更加直觀。通過模仿人類在任務執行中的行為,承諾提升用戶體驗。 敘事記憶:用於利用高級經驗,Agent S利用敘事記憶來跟蹤任務歷史,從而增強其決策過程。 情節記憶:此特徵為用戶提供逐步指導,使框架能夠在任務展開時提供上下文支持。 支持OpenACI:Agent S能夠在本地運行,使用戶能夠控制其互動和工作流程,與Web3的去中心化理念相一致。 與外部API的輕鬆集成:其多功能性和與各種AI平台的兼容性確保了Agent S能夠無縫融入現有技術生態系統,成為開發者和組織的理想選擇。 這些功能共同促成了Agent S在加密領域的獨特地位,因為它以最小的人類干預自動化複雜的多步任務。隨著項目的發展,其在Web3中的潛在應用可能重新定義數字互動的展開方式。 Agent S的時間線 Agent S的發展和里程碑可以用一個時間線來概括,突顯其重要事件: 2024年9月27日:Agent S的概念在一篇名為《一個像人類一樣使用計算機的開放代理框架》的綜合研究論文中推出,展示了該項目的基礎工作。 2024年10月10日:該研究論文在arXiv上公開,提供了對框架及其基於OSWorld基準的性能評估的深入探索。 2024年10月12日:發布了一個視頻演示,提供了對Agent S能力和特徵的視覺洞察,進一步吸引潛在用戶和投資者。 這些時間線上的標記不僅展示了Agent S的進展,還表明了其對透明度和社區參與的承諾。 有關Agent S的要點 隨著Agent S框架的持續演變,幾個關鍵特徵脫穎而出,強調其創新性和潛力: 創新框架:旨在提供類似人類互動的直觀計算機使用,Agent S為任務自動化帶來了新穎的方法。 自主互動:通過GUI自主與計算機互動的能力標誌著向更智能和高效的計算解決方案邁進了一步。 複雜任務自動化:憑藉其強大的方法論,能夠自動化複雜的多步任務,使過程更快且更少出錯。 持續改進:學習機制使Agent S能夠從過去的經驗中改進,不斷提升其性能和效率。 多功能性:其在OSWorld和WindowsAgentArena等不同操作環境中的適應性確保了它能夠服務於廣泛的應用。 隨著Agent S在Web3和加密領域中的定位,其增強互動能力和自動化過程的潛力標誌著AI技術的一次重大進步。通過其創新框架,Agent S展現了數字互動的未來,為各行各業的用戶承諾提供更無縫和高效的體驗。 結論 Agent S代表了AI與Web3結合的一次大膽飛躍,具有重新定義我們與技術互動方式的能力。儘管仍處於早期階段,但其應用的可能性廣泛且引人入勝。通過其全面的框架解決關鍵挑戰,Agent S旨在將自主互動帶到數字體驗的最前沿。隨著我們深入加密貨幣和去中心化的領域,像Agent S這樣的項目無疑將在塑造技術和人機協作的未來中發揮關鍵作用。

864 人學過發佈於 2025.01.14更新於 2025.01.14

什麼是 AGENT S

如何購買S

歡迎來到HTX.com!在這裡,購買Sonic (S)變得簡單而便捷。跟隨我們的逐步指南,放心開始您的加密貨幣之旅。第一步:創建您的HTX帳戶使用您的 Email、手機號碼在HTX註冊一個免費帳戶。體驗無憂的註冊過程並解鎖所有平台功能。立即註冊第二步:前往買幣頁面,選擇您的支付方式信用卡/金融卡購買:使用您的Visa或Mastercard即時購買Sonic (S)。餘額購買:使用您HTX帳戶餘額中的資金進行無縫交易。第三方購買:探索諸如Google Pay或Apple Pay等流行支付方式以增加便利性。C2C購買:在HTX平台上直接與其他用戶交易。HTX 場外交易 (OTC) 購買:為大量交易者提供個性化服務和競爭性匯率。第三步:存儲您的Sonic (S)購買Sonic (S)後,將其存儲在您的HTX帳戶中。您也可以透過區塊鏈轉帳將其發送到其他地址或者用於交易其他加密貨幣。第四步:交易Sonic (S)在HTX的現貨市場輕鬆交易Sonic (S)。前往您的帳戶,選擇交易對,執行交易,並即時監控。HTX為初學者和經驗豐富的交易者提供了友好的用戶體驗。

1.8k 人學過發佈於 2025.01.15更新於 2026.06.02

如何購買S

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