Stanley Druckenmiller: From Soros' Comrade-in-Arms to the Godfather of Macro Investing—System, Disciples, and Latest Thoughts

marsbitPublié le 2026-05-20Dernière mise à jour le 2026-05-20

Résumé

Stanley Druckenmiller is a pivotal figure in global macro investing, renowned for his partnership with George Soros, his legendary fund Duquesne Capital, and a decades-long track record of near-30% annualized returns without a single annual loss. His methodology uniquely blends value, growth, macro, and trend investing. A key early experience was as a bank stock analyst, grounding him in both company fundamentals and macro forces. His most famous trade, shorting the British Pound in 1992, exemplified his approach: identifying unsustainable structural contradictions and concentrating capital on high-probability, high-payoff opportunities. The "Duquesne System" is built on four pillars: macro-directional analysis, concentrated bets on best ideas, rapid error correction, and acute awareness of liquidity. His famous phrase "Invest, then investigate" reflects a dynamic approach of entering a position based on a strong initial thesis and then adjusting based on market feedback. This differs fundamentally from Warren Buffett's focus on long-term intrinsic business value; Druckenmiller focuses on marginal changes, cycles, and capital allocation at inflection points. His influence extends through protégés like Scott Bessent (market execution) and Kevin Warsh (policy insight), representing the dual market-and-institutional understanding he embodies. He closed his flagship fund in 2010 at its peak, prioritizing flexibility and performance over asset-gathering. Recent moves highlight h...

In the field of global macro investing, if we were to choose only a few figures who have genuinely influenced market history, Stanley Druckenmiller would undoubtedly rank among the top. Compared to the more publicly familiar Warren Buffett, Druckenmiller carries more complex labels: he was one of the core traders during the Soros era, the founder of the legendary Wall Street fund Duquesne Capital; he achieved the myth of having no annual losses for decades with nearly 30% annualized returns, yet also voluntarily closed his fund at the peak of his career.

More importantly, he is not someone who succeeded through a single style. Elements that seem contradictory—value, growth, macro, trend, sector rotation, and concentrated bets—have formed a unique methodology in Druckenmiller.

Today, if one studies the global macro investing system or seeks to understand how top traders build their cognition, Druckenmiller remains an unavoidable figure.

Early Career: From Bank Analyst to Macro Trading Master

Druckenmiller's career start was not legendary. He initially worked as a stock analyst at Pittsburgh National Bank, researching specific companies and industries. This experience was crucial because it ensured he was not merely someone who only looked at macro variables. He understood both corporate fundamentals and market pricing logic.

Later, he founded Duquesne Capital and gradually developed his own investment style. Unlike many traditional fund managers, Druckenmiller did not confine himself to a single asset class. He could trade stocks, bonds, currencies, or commodities. What he truly focused on was: where the greatest risk-reward ratio existed.

In 1988, Druckenmiller joined Soros' Quantum Fund, an extremely critical stage in his career. Soros excelled at understanding markets from philosophical and macro-structural levels, while Druckenmiller excelled at translating macro judgments into specific trades. Their combination was one of the most classic pairings in the history of global macro investing.

This period reinforced a core belief in Druckenmiller: the market is not a static valuation sheet but a system of constant feedback, self-reinforcement, and continuous movement from one extreme to another.

One of the Most Classic Battles in Financial History: Shorting the British Pound

The 1992 shorting of the British pound is Druckenmiller's most famous battle, but to view it merely as "having guts" underestimates the essence of this trade.

At the time, the UK had joined the European Exchange Rate Mechanism, maintaining the pound's exchange rate within a relatively fixed range. However, the problem was that the UK's economic fundamentals did not support such an exchange rate level. The UK needed looser monetary policy to stimulate the economy, but to maintain the pound's exchange rate, it had to keep interest rates high. This created an unsustainable contradiction: the domestic economy required interest rate cuts, while the exchange rate mechanism demanded high rates.

What Druckenmiller saw was not short-term price fluctuations but the inherent fragility of the institutional arrangement itself. He judged that the UK government ultimately could not simultaneously protect both the economy and the exchange rate. When an irreconcilable contradiction arises within a macro system, the market will eventually attack this weakness.

This trade truly embodies three characteristics of Druckenmiller.

First, he did not predict prices first; he first identified structural contradictions. Second, he did not bet evenly and diversely; he concentrated his bets when high-probability, high-payoff opportunities appeared. Third, he did not succeed because his position size was large; rather, because the logic was strong enough, he dared to increase the position size.

This is precisely the difference between Druckenmiller and the average trader. Average traders like to use position size to prove courage; Druckenmiller uses position size to express probability.

The Duquesne System: The Discipline Behind High Returns

What is most astonishing about Duquesne Capital is not how much it earned in any single year, but its long-term record of almost no annual losses. For a global macro fund, this is even more difficult than high returns themselves.

Macro trading is inherently uncertain. Monetary policies change, wars erupt, market sentiment reverses, central banks may intervene suddenly, and political events can alter asset pricing. Maintaining outstanding performance over the long term in such an environment relies not on being right once, but on a complete investment system.

Druckenmiller's system can be summarized with four keywords: Macro, Concentration, Error Correction, and Liquidity.

By "Macro," it means he always first judges the broad economic direction. For instance, is the economy accelerating or slowing? Are interest rates rising or falling? Is inflation spreading or receding? Are central banks easing or tightening? Only when these major directions form a clear judgment does he seek the most suitable expression.

By "Concentration," it means he does not evenly disperse capital across numerous mediocre opportunities. He believes truly excellent investment opportunities are rare, and once they appear, one should express the view with a sufficiently large position. Many fund managers pursue "avoiding big mistakes," hence they diversify; Druckenmiller pursues "earning enough when right," hence he dares to concentrate.

By "Error Correction," it means he does not blindly believe his own judgments. He can strongly favor a certain direction, but if market feedback and changing fundamentals do not support the original judgment, he will exit swiftly. For him, admitting error is not failure but part of the investment process.

By "Liquidity," it means he places great importance on the market environment. Many assets can rise far beyond fundamentals when liquidity is ample and fall far beyond valuation models when liquidity tightens. Druckenmiller deeply understands that the monetary environment often determines the marginal direction of the market.

The True Meaning of "Invest First, Investigate Later"

Druckenmiller's famous quote, "Invest, then investigate," is often misunderstood as impulsive betting. In reality, the core of this statement is not recklessness but respect for the speed of the market.

In real markets, the best opportunities often do not wait for all information to be fully confirmed. By the time data is completely clear, news is fully digested, and research reports are written, prices have often already reflected most expectations. Therefore, Druckenmiller's method is not to act only when 100% certain, but to first establish a position when the logic is initially sound, then constantly adjust based on market feedback, fundamental changes, and data verification.

This method has an important prerequisite: positions must be dynamic. Investing first does not mean going all-in from the start, but rather getting into the market first to gain a more genuine feel for it. If the logic is validated, add to the position; if the logic is broken, exit.

This is actually a very advanced cognitive method. The problem for many investors is not insufficient research but an excessive pursuit of certainty. They hope to eliminate all risks before acting, but the market never offers such perfect answers. Druckenmiller accepts uncertainty and deals with it through position management and rapid error correction.

The Fundamental Difference Between Druckenmiller and Buffett

Comparing Druckenmiller and Buffett side by side allows for a clearer understanding of his uniqueness.

Buffett's core question is: Is this a good company, is the price reasonable, and can it continue to generate cash flow over the next decade? Druckenmiller's core question is: What changes are currently happening in the world, is the market mispricing these changes, and which asset class best expresses this judgment?

Buffett focuses more on intrinsic corporate value; Druckenmiller focuses more on marginal changes. Buffett emphasizes long-term holding; Druckenmiller emphasizes flexible adjustment. Buffett likes stable compounding; Druckenmiller likes to attack heavily at key junctures.

This is not to say one is superior to the other, but rather that the two approach the market differently. Buffett views the market as a quoting system for corporate ownership; Druckenmiller views it as a dynamic system driven by macro variables, capital flows, and human expectations.

If an investor studies Buffett, they learn patience, moats, and compounding; if they study Druckenmiller, they learn cycles, payoffs, and position sizing.

Two Disciples: Two Types of Legacy Represented by Bessent and Warsh

Druckenmiller's influence is manifested not only in performance but also in the figures he nurtured and influenced. Scott Bessent and Kevin Warsh can be seen as two extensions of his intellectual system.

Scott Bessent is closer to a successor on the trading front. He spent a long time in the macro trading environment of Soros and Druckenmiller, familiar with the relationship between currencies, interest rates, fiscal policy, and market prices. What he inherited is the most trading-oriented aspect of Druckenmiller: identifying macro misalignments, judging payoffs, and expressing views with position sizing.

Kevin Warsh, on the other hand, is closer to a successor on the policy front. He worked within the Federal Reserve system, possessing deep understanding of monetary policy, central bank decisions, and financial regulation. Warsh's value is not primarily in trade execution but in policy judgment and institutional understanding.

Looking at these two together reveals that the Druckenmiller system is not merely about "knowing how to trade." It requires two capabilities: market capability and institutional capability. Understanding only price movements without understanding policy and institutions leads easily to technical trading; understanding only macro narratives without understanding market feedback leads easily to remaining at theoretical analysis. Druckenmiller's strength lies precisely in combining these two.

Why He Closed His Fund at Its Peak

In 2010, Druckenmiller closed the external fund business of Duquesne Capital, a decision very worthy of analysis.

Typically, fund managers with glorious track records tend to continue scaling up, as management fees and performance fees imply substantial interests. But Druckenmiller chose to exit, indicating he was acutely aware of how scale erodes investment returns.

Global macro investing relies on flexibility. The larger the capital scale, the more difficult it is to enter and exit markets, the fewer opportunities are available, and the greater the impact trades have on market prices. Opportunities that a medium-sized fund could flexibly capture in the past may become impossible to execute effectively after capital expansion.

More importantly, Druckenmiller held himself to extremely high standards. He was unwilling to continue managing external funds if he could not maintain the original quality. This reflects his risk philosophy: the real risk is not earning a little less, but continuing to attack when it's unsuitable to do so.

Closing the fund does not mean he lost interest in the market but rather shifted from "managing other people's money" to "managing his own capital." This freed him from the redemption pressures of external investors and allowed his decisions greater freedom.

From AI to Copper: The Logic Behind Recent Portfolio Changes

In recent years, one of the market's greatest focuses on Druckenmiller has been his views on the AI wave, dollar trends, and the resource cycle.

He participated earlier in AI-related investments, showing he is not a conservative macro investor in the traditional sense. As long as he believes an industry trend is strong enough and market pricing still has room, he will actively engage in growth and tech stocks. However, his recent reduction in AI exposure and statement that his portfolio is no longer driven by AI does not necessarily mean he is bearish on AI itself; it more likely indicates he believes market expectations have become overly concentrated.

This is typical Druckenmiller thinking: he cares not whether a theme is good, but whether the price already reflects it. If a theme is universally recognized and valuations are fully priced-in, then even if it is correct in the long term, it may not be a good trade in the short term.

In contrast, his focus on copper better exemplifies second-order thinking. On the surface, AI is about chips, models, and computing power, but behind it lie electricity, data centers, transmission networks, and infrastructure. Copper sits at the bottom of this chain. If AI continues to develop, energy systems and grid upgrades cannot be avoided, and copper could become one of the most directly benefited resources.

This shows Druckenmiller does not simply chase popular assets but seeks assets not yet fully priced in behind popular narratives. He may not buy the most obvious thing but rather what best expresses supply-demand contradictions.

Bearish on the Dollar: Fiscal Deficits and Monetary Credibility Issues

Druckenmiller's concerns about the long-term purchasing power of the US dollar also extend his macro framework. He is not simply predicting the dollar will fall tomorrow but observing the long-term pressures on the US fiscal and monetary systems.

If a country's fiscal deficits expand chronically, debt accumulates continuously, and the political system lacks the ability to cut spending or increase revenue, monetary credibility will eventually be challenged. The US dollar, as the global reserve currency, still holds a strong position in the short term, but this does not mean its purchasing power cannot be diluted.

Druckenmiller cares about long-term institutional constraints. When fiscal discipline deteriorates and the boundaries between the central bank and fiscal authorities blur, the market will eventually reassess the currency's value. This judgment may not immediately reflect in exchange rates but will gradually affect allocation logic for gold, resources, overseas assets, and real assets.

This is also why he simultaneously pays attention to the dollar, copper, fiscal deficits, and industrial investment. These seemingly disparate themes actually point to the same issue: the future world may enter a phase of declining monetary credibility, repricing of real assets, and rising capital expenditures.

The Core of Druckenmiller's Methodology: Payoff over Probability

Many who study Druckenmiller mistakenly assume his greatest ability is accurate prediction. More accurately, his strongest suit is payoff judgment.

Investing is not an exam where answering more questions correctly is better. An investor can be right seven out of ten times, but if each correct bet earns only a little while one wrong bet loses a lot, they still fail long-term. Conversely, an investor may make fewer judgments, but if they bet heavily on high-payoff opportunities and cut losses quickly when wrong, they can still achieve extremely high returns.

Druckenmiller places great importance on this difference. He does not seek to have a view every day or allocate to every asset. He waits for opportunities that offer "limited loss if wrong, substantial gain if right."

This is also his biggest distinction from the average investor. Average investors often ask, "Will this go up?" A Druckenmiller-style question is: "If I'm right, how much can I earn? If I'm wrong, how much will I lose? Has the market already fully reflected this judgment? Is there a better way to express it?"

From this perspective, his system is not a prediction system but a decision-making system.

What Ordinary Investors Can and Cannot Learn

Druckenmiller's methods are highly instructive, but that does not mean ordinary investors can copy them directly.

What ordinary investors should absolutely not emulate is high leverage and frequent macro trading. Global macro trading requires vast information, experience, understanding of liquidity, and risk control capabilities. If one only sees Druckenmiller's successful concentrated bets but ignores the depth of research and speed of error correction behind them, it easily becomes reckless gambling.

What is truly worth learning for ordinary investors are three types of thinking from him.

First, learn to focus on marginal changes. Market prices reflect expectations, not static facts. A good company can still be a poor investment if expectations are too high; a poor industry can present阶段性 opportunities if expectations are extremely low.

Second, learn to distinguish between views and position sizing. A view can be strong, but position size must be determined based on the risk-reward ratio. The greatest danger in investing is not being wrong, but having too large a position and correcting too slowly when wrong.

Third, learn to seek opportunities using second-order logic. For example, in the AI frenzy, the market first buys chips and software, but deeper opportunities may lie in electricity, copper, equipment, infrastructure, and energy systems. This ability to move from surface narratives to underlying constraints is the most valuable part of the Druckenmiller system to learn.

Conclusion:

Druckenmiller is not merely a trader nor a traditional value investor in the conventional sense. He is more like a strategist within the market. He understands macroeconomics but also respects price; he dares to bet heavily but also values risk extremely highly; he holds strong views but never dogmatically adheres to them; he pursues big opportunities but is not addicted to constant trading.

His success does not stem from some mysterious indicator but from a complete investment personality: keen, restrained, flexible, decisive, and simultaneously deeply respectful of the market.

If one were to summarize Druckenmiller's investment philosophy in one sentence, it would be: Recognize when the world presents a major misalignment; enter when the market has not yet fully priced it in; increase exposure when the logic is validated; and leave immediately when the judgment is disproven.

The reason this system is worth continuing to study today is that regardless of whether market themes shift from the internet to AI, from low inflation to high debt, from globalization to reindustrialization, what ultimately determines long-term investment success is still not the speed of chasing trends but the ability to understand cycles, judge payoffs, manage positions, and control risks.

Disclaimer: This article is compiled based on publicly available information and is for reference only. It does not constitute any investment advice.

Questions liées

QWhat are the four key elements of Stanley Druckenmiller's investment system?

AStanley Druckenmiller's investment system can be summarized by four key elements: Macro, Concentration, Correction, and Liquidity. Macro refers to always judging the broad economic direction first. Concentration means not spreading capital thinly across mediocre opportunities but placing substantial bets on high-conviction ideas. Correction involves not being dogmatic about one's views and exiting quickly if market feedback contradicts the original thesis. Liquidity emphasizes the critical importance of the market's monetary environment, which often determines the marginal direction of asset prices.

QHow does Druckenmiller's core investment approach fundamentally differ from that of Warren Buffett?

AWarren Buffett focuses on whether a company is fundamentally good, if the price is reasonable, and if it can generate cash flows for the next decade. Stanley Druckenmiller focuses on what major changes are occurring in the world, whether the market is mispricing those changes, and which asset best expresses that view. Buffett emphasizes intrinsic value and long-term holding; Druckenmiller emphasizes marginal changes and flexible adjustments. Buffett seeks stable compounding; Druckenmiller seeks to attack with concentrated positions at key inflection points.

QWhat is the true meaning behind Druckenmiller's famous phrase 'Invest, then investigate'?

AThe phrase 'Invest, then investigate' is often misunderstood as impulsive betting. Its core meaning is respect for market speed. The best opportunities often don't wait for all information to be confirmed. Druckenmiller's method involves establishing a position when the initial logic holds, then continuously adjusting based on market feedback, fundamental changes, and data verification. A crucial prerequisite is that the position must be dynamic—starting with a smaller stake to gain real market feel, then adding if the thesis is confirmed or exiting if it is invalidated. It's an advanced way to handle uncertainty through position management and rapid error correction.

QWhy did Stanley Druckenmiller close his fund Duquesne Capital at its peak?

ADruckenmiller closed Duquesne Capital's external fund business in 2010 primarily due to the corrosive effect of asset size on investment returns. Global macro investing relies on flexibility. Larger capital makes market entry and exit more difficult, reduces the pool of available opportunities, and increases the market impact of trades. More importantly, it reflected his risk philosophy: the real risk isn't making less money, but continuing to attack when conditions are no longer suitable. Closing the fund allowed him to shift from managing others' money to managing his own capital, freeing him from investor redemption pressures and granting greater decision-making freedom.

QAccording to the article, what is the core of Druckenmiller's methodology: predicting odds or predicting correctness?

AThe core of Stanley Druckenmiller's methodology is judging odds (risk/reward or payout ratio), not merely predicting correctness (win rate). He doesn't seek to be right most often, but to identify asymmetric opportunities where the potential gain if right is substantial, while the potential loss if wrong is limited. He waits for 'high-probability, high-payout' opportunities and is willing to place concentrated bets on them. His system is a decision-making framework that prioritizes 'How much can I make if I'm right? How much can I lose if I'm wrong? Is the market price already reflecting this view?' over simply asking 'Will this go up?'

Lectures associées

De Web3 à l'Agent IA, le vieux VC crypto Variant mise 2 milliards sur une transformation

Variant, un vétéran du capital-risque crypto, annonce un nouveau fonds de 222 millions de dollars, le "Variant 4". Ce fonds marque une évolution de sa thèse d'investissement centrale : du concept de "propriété numérique" vers celui plus large de "souveraineté individuelle" (autonomie). Cette autonomie concerne le contrôle accru que les utilisateurs ont sur leur vie numérique, leurs actifs, leur identité et leur capacité d'action, au-delà de la simple automatisation. La distinction clé est que l'automatisation intelligente doit servir l'utilisateur final, et non la plateforme, pour véritablement accroître l'autonomie. Variant investira donc dans les technologies qui étendent cette souveraineté, en augmentant l'accès, les connaissances et la propriété des utilisateurs. Ce cadre englobe ses investissements passés dans les blockchains (Ethereum, Solana), l'infrastructure pour développeurs, les marchés financiers décentralisés et les produits grand public. Le fonds voit dans la convergence des agents d'IA intelligents et des rails financiers globaux ouverts un potentiel de transformation structurelle d'Internet, passant d'un modèle où "l'utilisateur est le produit" à un modèle où l'utilisateur dispose d'une autonomie inédite. Variant mettra son expertise, acquise dans l'écosystème crypto, au service des fondateurs qui construisent aux frontières de ces systèmes autonomes.

marsbitIl y a 6 mins

De Web3 à l'Agent IA, le vieux VC crypto Variant mise 2 milliards sur une transformation

marsbitIl y a 6 mins

Bloomberg révèle : Comment les riches Chinois contournent la limite annuelle de 50 000 dollars pour transférer leurs actifs ?

Bloomberg révèle que malgré le plafond annuel de 50 000 dollars par personne fixé par l'administration chinoise des changes, environ 150 milliards de dollars s'échappent chaque année via des canaux informels ou souterrains. L'article retrace l'évolution du contrôle des capitaux depuis 1994, avec un durcissement notable après la dévaluation de 2015 et une sophistication numérique accrue entre 2024 et 2026, incluant le CRS et un suivi renforcé des transactions. Cinq principales méthodes de transfert sont identifiées : le système de compensation "Duiqiao" (aucune sortie effective de RMB), le "déménagement de fourmis" utilisant les quotas légaux de multiples personnes, la falsification des factures commerciales, la migration vers des canaux de gestion de fortune des grandes banques (ex: QDII), et les arrangements structurels comme les fiducies ou l'immigration. La réponse réglementaire se concentre désormais sur les individus plutôt que sur les seules entreprises, avec le CRS comme outil de rétrospection clé pour identifier les actifs offshore. Même les cryptomonnaies, parfois perçues comme une échappatoire, font l'objet de poursuites pour infraction. La pression pour diversifier les actifs à l'étranger reste forte parmi les millions de ménages aisés chinois, malgré un "mur" réglementaire de plus en plus haut et intelligent.

marsbitIl y a 18 mins

Bloomberg révèle : Comment les riches Chinois contournent la limite annuelle de 50 000 dollars pour transférer leurs actifs ?

marsbitIl y a 18 mins

Claude Code lance des workflows dynamiques : faire en sorte que l'IA apprenne à travailler en équipe

Claude Code introduit des flux de travail dynamiques, permettant à l'IA de créer des cadres d'exécution sur mesure pour des tâches complexes. Ces workflows coordonnent plusieurs agents Claude indépendants, chacun avec son propre contexte, pour décomposer les missions, traiter en parallèle, valider de manière antagoniste et synthétiser les résultats. Cette approche vise à résoudre des problèmes courants des modèles linguistiques sur de longues tâches : la paresse agentique (arrêt prématuré), le biais d'auto-préférence (favoriser ses propres conclusions) et la dérive d'objectifs. Les flux de travail dynamiques s'appliquent au-delà du code, pour la recherche approfondie, la vérification des faits, le tri de CV, l'enquête sur les causes profondes, le brainstorming de noms ou l'examen de plans d'affaires. L'article présente des modèles pratiques comme la classification et l'exécution, l'éventail et la synthèse, la validation antagoniste, les tournois et les boucles jusqu'à l'achèvement. Il souligne que les workflows, bien que consommant généralement plus de jetons, ne sont pas une solution universelle mais représentent une direction importante : la future concurrence des outils d'IA pourrait reposer sur leur capacité à orchestrer des processus d'exécution fiables et réutilisables pour des objectifs complexes.

marsbitIl y a 59 mins

Claude Code lance des workflows dynamiques : faire en sorte que l'IA apprenne à travailler en équipe

marsbitIl y a 59 mins

Hyperliquid, le dépanneur de Wall Street ouvert 24h/24

Le samedi de février où son téléphone a annoncé les frappes aériennes de Trump contre l'Iran, Vala Zeinali, trader dans un fonds spéculatif, s'est immédiatement rendu sur Hyperliquid. Cette plateforme de trading décentralisée, ouverte 24h/24 et 7j/7, est devenue un repaire pour les traders de Wall Street cherchant à anticiper les marchés hors des heures d'ouverture. Zeinali y a clôturé des positions sur le pétrole pour un gain de 243%. Fondée il y a trois ans par Jeff Yan, ancien trader quantitatif, Hyperliquid répond au besoin de garder le contrôle de ses actifs, renforcé après la chute de FTX. Avec seulement 11 employés, la plateforme et sa blockchain ont généré environ 8 milliards de dollars de revenus l'an dernier. Son jeton natif, HYPE, a vu sa valeur exploser. Hyperliquid symbolise la fusion entre la finance traditionnelle et les cryptos, proposant des contrats perpétuels sur des actifs variés : Bitcoin, S&P 500, pétrole, ou même des entreprises non cotées comme SpaceX. Bien que les utilisateurs américains soient officiellement interdits, beaucoup contournent la restriction via des VPN, attirés par l'interface simple, la diversité des produits et l'absence de vérification d'identité rigoureuse. La plateforme cultive une forte communauté. Les utilisateurs interagissent directement avec l'équipe sur Discord et animent l'espace en ligne avec le mème "Hypurr". Cependant, les contrats perpétuels, avec leur effet de levier, sont très risqués. Lors d'un krach en octobre dernier, les liquidations sur Hyperliquid ont atteint 10 milliards de dollars, révélant à la fois les risques et la robustesse technique de la plateforme qui est restée opérationnelle. L'objectif ultime d'Hyperliquid est d'héberger toute activité financière. La plateforme prévoit maintenant de s'étendre aux marchés de prédiction et aux options.

marsbitIl y a 1 h

Hyperliquid, le dépanneur de Wall Street ouvert 24h/24

marsbitIl y a 1 h

Trading

Spot
Futures
活动图片