TEAM

Atlassian Price

TEAM
$65,06
-$2,94(-%4,32)

*Data last updated: 2026-04-07 21:23 (UTC+8)

As of 2026-04-07 21:23, Atlassian (TEAM) is priced at $65,06, with a total market cap of $17,29B, a P/E ratio of -207,12, and a dividend yield of %0,00. Today, the stock price fluctuated between $64,33 and $68,59. The current price is %1,13 above the day's low and %5,14 below the day's high, with a trading volume of 734,35K. Over the past 52 weeks, TEAM has traded between $64,32 to $242,00, and the current price is -%73,11 away from the 52-week high.

TEAM Key Stats

Yesterday's Close$68,09
Market Cap$17,29B
Volume734,35K
P/E Ratio-207,12
Dividend Yield (TTM)%0,00
Diluted EPS (TTM)0,72
Net Income (FY)-$256,68M
Revenue (FY)$5,21B
Earnings Date2026-04-30
EPS Estimate1,33
Revenue Estimate$1,69B
Shares Outstanding254,02M
Beta (1Y)0.994

About TEAM

Atlassian Corporation, through its subsidiaries, designs, develops, licenses, and maintains various software products worldwide. Its product portfolio includes Jira Software and Jira Work Management, a project management system that connects technical and business teams so they can better plan, organize, track and manage their work and projects; Confluence, a connected workspace that organizes knowledge across all teams to move work forward; and Trello, a collaboration and organization product that captures and adds structure to fluid and fast-forming work for teams. The company also offers Jira Service Management, an intuitive and flexible service desk product for creating and managing service experiences for various service team providers, such as IT, legal, and HR teams; and Jira Align, an Atlassian's enterprise agility solution designed to help businesses to adapt and respond dynamic business conditions with a focus on value-creation. In addition, it provides Bitbucket, an enterprise-ready Git solution that enables professional dev teams to manage, collaborate, and deploy quality code; Atlassian Access, an enterprise-wide product for enhanced security and centralized administration that works across every Atlassian cloud product; and Jira Product, a prioritization and road mapping tool. Further, the company's portfolio includes Atlas, a teamwork directory; Bamboo, a continuous delivery pipeline; Crowd, a single sign-on; Crucible, a collaborative code review; Fisheye, a search, track, and visualize code change software; and Compass, a developer experience platform. Additionally, it offers Opsgenie, an on-call and alert management software; Sourcetree, a free git client for windows and mac; Statuspage that communicates real-time status to users; Beacon, an intelligent threat detection software; and Atlassian Access that enhance data security and governance for Atlassian Cloud products. The company was founded in 2002 and is headquartered in Sydney, Australia.
SectorTechnology
IndustrySoftware - Application
CEOMichael Cannon-Brookes
HeadquartersSydney,NSW,AU
Employees (FY)13,81K
Average Revenue (1Y)$377,56K
Net Income per Employee-$18,58K

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Atlassian (TEAM) is currently trading at $65,06, with a 24h change of -%4,32. The 52-week trading range is $64,32–$242,00.

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Atlassian (TEAM) Latest News

2026-04-07 16:31

Pump.fun team/investor-related addresses deposited 2.34 billion PUMP tokens into a certain CEX

Gate News message, April 7, according to monitoring by Onchain Lens, Pump.fun team/investor-related addresses deposited 2.34 billion PUMP tokens into a certain CEX, worth about $4 million.

2026-04-07 15:02

Velora (formerly Paraswap) has published a new governance proposal to shut down the DAO treasury and terminate the staking program

Gate News message, April 7, Velora (formerly Paraswap) released a new governance proposal. The main changes include: focusing on structural decisions regarding the VLR token; terminating the staking plan and stopping reward distribution; closing the DAO treasury and using the remaining balance to pay for infrastructure services; stopping DAO-level fee routing; and updating the multisig configuration to match the governance scope. The proposal explicitly states that these changes will not modify the token supply amount, the unlock schedule, token allocations, or the transferability of VLR. Going forward, governance will focus on structural decisions that affect the VLR token, and protocol operations and infrastructure will continue to be supported by the project’s development team.

2026-04-07 14:41

SOL Strategies acquires Solana zero-knowledge technology company Darklake Labs for $1.2 million

Gate News message: On April 7, SOL Strategies announced that it has completed the acquisition of the Solana zero-knowledge technology company Darklake Labs. The total transaction price is 1.2 million US dollars, including 200,000 US dollars in cash and 1.0 million US dollars in the company’s common stock. Darklake Labs is an early Solana ecosystem startup that developed a dynamic zero-knowledge proof system called Zyga, designed specifically for the Solana blockchain, which can both enable transaction privacy and eliminate frontrunning and sandwich attacks during the execution phase. After the acquisition is completed, the founders and core team of Darklake Labs will join SOL Strategies.

2026-04-07 14:02

Fluent’s BLEND token public sale registration is now open, raising $1 million in funding with a $100 million FDV

Gate News message, April 7, Fluent posted on X that the BLEND token public offering is now open for registration. The goal is to raise $1 million with an FDV of $100 million, with a full unlock at TGE. On April 13, the token public offering will close, and the mainnet will go live 2 weeks after the offering ends. The total supply of BLEND tokens is 1 billion, with an initial unlock of 75 million. The foundation will allocate 100 million, investors will receive 225 million, the team will be allocated 200 million, and the ecosystem expansion will receive 400 million.

2026-04-07 13:51

Tether CEO: The team is developing a decentralized search engine, hypersearch.

Gate News message, on April 7, Tether CEO Paolo Ardoino said that the team is developing a decentralized search engine called hypersearch. The product is built on a distributed hash table (DHT, a decentralized data storage technology) architecture.

Hot Posts About Atlassian (TEAM)

金色财经_

金色财经_

28 minutes ago
**Over the past week, everyone in the crypto space has been repeatedly jolted by the same signal: the quantum hardware bar for cracking Bitcoin has just been smashed through, and it has just suffered a steep, cliff-like drop in value.** What had been widely assumed in academic circles to require a long wait of millions of qubits has, in an instant, been knocked down to the 500k—even 10k—range. The cryptographic high wall protecting Bitcoin appears to be wobbling. An Early Quantum Decryption Date --------- Google Quantum AI team (superconducting route) and Oratomic, a Caltech-spun startup (neutral atom route)—two technical branches with radically different underlying physical logic—nevertheless produced back-to-back answers for a breakthrough reduction in the threshold on March 30 and 31, 2026. This is not a coincidence. It’s the historical convergence brought about by violent acceleration of quantum technology under stronger external forces like AI. That also explains why, from frontier theorists to Ethereum core researcher Justin Drake, everyone has pinned the dangerous window of Q-Day (quantum decryption day) to 2029–2032. When these two fast-advancing quantum routes collide with the extremely slow consensus mechanisms of decentralized networks, “three years” becomes a life-or-death countdown. Two Routes Push the Threshold Into Reality ----------- To understand why expectations for Q-Day (quantum decryption day) were suddenly pulled forward, the first step is to change the old idea that cracking Bitcoin relies on simply stacking traditional brute-force compute power. Conventional classical cracking relies on the more compute, the more forceful it is. But quantum cracking relies on Shor’s algorithm circuit design—quantum algorithms proposed by mathematician Peter Shor in 1994. By leveraging quantum superposition and entanglement, Shor’s algorithm can solve the elliptic curve discrete logarithm problem in polynomial time, which is the core mathematical difficulty behind Bitcoin’s ECDSA encryption. Quantum computers are naturally error-prone. They need to package error correction using multiple physical qubits (real hardware units, like superconducting circuits or suspended atoms) to synthesize a stable, reliable logical qubit (a virtual unit that can actually run algorithms). In the past, the error-correction overhead was so high that hundreds, even thousands of physical qubits, were needed to get one logical qubit. That was Bitcoin’s natural moat. But now, that moat is drying up. ![](https://img-cdn.gateio.im/social/moments-8e62639a91-ed87c86deb-8b7abd-badf29) The breakthrough from Google’s team lies in extreme algorithm optimization. They redesigned the Shor algorithm circuit and cut the number of key operation steps (Toffoli gates) by more than tenfold. In the end, they only need **about 1,200 logical qubits**. Converted to real hardware, that means fewer than 500k physical qubits—20 times lower than earlier mainstream estimates. Google is like a sprinter: in the optimal case, it can crack private keys in just 9 minutes—enough to intercept funds before Bitcoin produces its block within 10 minutes, during the moment your transfer public key is exposed. Oratomic’s approach reduces error-correction cost directly from the hardware side. Led by Dolev Bluvstein, an associate professor of physics at Caltech, and with quantum information heavyweight John Preskill overseeing the effort, the company uses neutral atom qubits (atoms suspended like small balls, allowing flexible rearrangement) and pairs them with a new high-rate qLDPC error-correcting code. Oratomic is like running an energy-saving marathon. Completing the full Shor algorithm takes only 10k to 26k physical qubits—though it takes about 10 days to crack, the hardware threshold has been lowered into a range that is practical for engineering. Google is fast but needs more people. Oratomic saves people but is a bit slower. One is fast, the other is economical—yet both routes end up at the same place: Q-Day is no longer a distant theoretical concept; it has entered a quantifiable engineering phase. AI is accelerating this race ---------- The common driver that lets both routes explode in the same month is AI. AI large models aren’t just chat tools—they are redesigning quantum science. Google’s circuit optimization relies on machine learning to search for more efficient implementation approaches. Oratomic, even more directly, uses large language models (LLMs) to assist in designing qLDPC codes, driving error-correction efficiency up dramatically. At the same time, AI is also speeding up simulations of new hardware materials to find combinations with the lowest error rates. Real hardware progress in laboratories is seamlessly validating these theories. In March 2026, Quantinuum, the leader in the ion-trap route, had already run 94 protected logical qubits in experiments, and the operational fidelity even surpassed that of bare physical qubits. The era when 2 physical qubits could produce 1 high-quality logical qubit is coming into view. Meanwhile, Microsoft’s Majorana 1 chip, released as early as 2025, naturally has extremely low error rates for its topological qubits. Its target is directly aimed at a million-scale deployment, providing engineering validation for another low-overhead route. A shrinking time window --------- Different technical routes are accelerating at the same time, and validating each other. Predictions from experts such as Ethereum researcher Justin Drake and researcher Craig Gidney point to the time window for decryption capability as being around 2030 to 2032, and they estimate that the probability of successful decryption at that time will exceed 10%. For a decentralized system that carries trillions of dollars in assets and requires years of coordination, the time available for action is often not much. This is the true brutality of the three years: it’s not the time when quantum computers will politely knock on the door on schedule—it is the **final deadline** for the Bitcoin network to begin a full-scale migration. When the first private key is quietly cracked within 10k-plus neutral atoms, what the Bitcoin community will face will no longer be the mild discussions of the BIP-360 proposal, but a systemic crisis: old-address funds exposed in an instant, chaos on-chain, fork risks, and a collapse of trust. Major labs are already lining up to verify “how to make it even more cost-efficient,” and even though quantum computers themselves haven’t been built yet, the attack routes have already been optimized twice. Technology has never waited for consensus to be ready. This is the rule of quantum computing—and it’s the reality Bitcoin is facing right now.
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GateUser-bd883c58

GateUser-bd883c58

1 hours ago
Ask AI: What market cycle opportunities are captured behind the launch of a free cash flow ETF? How do you follow a path that belongs to you, guided by the investor-first philosophy, amid intense competition in the industry? ![](https://img-cdn.gateio.im/social/moments-307b39479a-1da556e676-8b7abd-badf29) Website for Investing Time, Punctuation Finance Researcher: Zhang Jingyu Today, index-based investing has already become an indispensable “infrastructure” in the field of asset allocation. With the number of domestic ETFs breaking through 1,400 and assets under management surpassing the 60 trillion yuan mark (data source: Wind), the industry is entering a brand-new stage of high-quality development. For fund managers, the key challenge is no longer simply stacking index-tracking tools, but truly understanding investors’ real needs, providing investors with long-term companionship and sufficient confidence through volatile markets. With curiosity about these questions, we visited BOC Fund and held an in-depth conversation with the Quantitative Index Team to explore how this fund company, with years of index research and investment accumulation, can use the investor-first philosophy to carve out its own path amid fierce industry competition. **1. Finding the balance between passive investing and active investing** As China’s public fund industry moves toward high-quality development, China’s ETF market has experienced a leap from none to some, and from having ETFs to having better ETFs. As one of the earlier fund companies to set up index-based investing in China, BOC Fund has been the first batch of managers of a number of ETFs across the whole market, including the SSE State-owned Enterprise ETF (SSE GuoQi ETF), the Shanghai Gold ETF, and the CSI Cash Flow ETF. Since its establishment, BOC Fund’s Quantitative Index Team has always remained true to its original intent of “putting investors first,” applying scientific investment and research logic to investment management and product planning, striving to create value for investors with professional strength. In building its investment philosophy, the Quantitative Index Team has formed a clear and complementary core direction around two product tracks: passive indices and quantitative index enhancement (quant fund index increase). **Passive Index Investing: A Practitioner of the “Market Efficency Theory”** In one sentence, BOC Fund’s passive index investing philosophy can be summarized as: **“Precise tracking, convenient allocation, and investment advisory empowerment.”** “Precise tracking” is the foundation of passive index investing. BOC Fund’s Quantitative Index Team uses refined management to strictly control tracking error, providing investors with pure index investment tools. Put simply, it is “what you see is what you get,” helping investors quickly capture investment opportunities, implement asset allocation conveniently, and effectively diversify investment risk. But simply tracking accurately is not enough. The team also hopes to address investors’ allocation needs—“what to buy and when to buy.” To that end, the team delves deeply into index and strategy research and provides professional advisory-like guidance to upgrade a product’s “tool attributes” into “service attributes,” realizing true value-empowering investment advisory capabilities. **Quantitative Index Enhancement (Quant Fund Index Increase): An Executor of Improving Market Efficacy** Compared with passive indices, index enhancement follows **“model-driven, disciplined execution.”** Its goal is, while strictly controlling risk, to continuously create steady and tangible excess returns. In terms of quantitative index enhancement, the team focuses on four core foundational areas: alpha models, risk models, portfolio optimization, and performance attribution. It also actively incorporates cutting-edge applications such as machine learning. On the basis of strictly controlling industry and style deviations and tracking error, it strives to maximize alpha, while controlling the drawdown risk of excess returns—seeking a balance between profitability and resilience—so that each increment of value for investors comes with greater confidence. **2. Build a “pyramid” talent pipeline and practice the core orientation of “long-term value”** Talent reserves are the carrier of vitality for the investment research (投研) system and the foundation for executing the investment philosophy; meanwhile, a mature and well-developed quantitative index investment research system provides a solid operating framework and efficient capability amplification for the talent pipeline. From a higher perspective, talent reserves and the investment research system together form the core competitiveness of the business. For the team’s sustainable development, the team’s long-term stability can, in turn, continuously drive the high-quality development of investment research capabilities. **Talent pipeline building: Emphasize the team’s advantages in coordinated combat to build a “stable, professional, and diverse” team** It is understood that, through a talent development model led primarily by internal cultivation and supplemented by external recruitment, BOC Fund’s Quantitative Index Team has achieved stable overall operation of the team and continued development. At present, BOC Fund’s Quantitative Index investment research team has more than 10 investment research personnel. Among them, there are 2 senior fund managers with over 10 years of investment management experience, 2 members of the mid-career generation with over 3 years of experience, and in recent years, 2 newly promoted fund managers from the junior/younger generation internally, forming a clear talent pipeline of **“senior leaders guiding + mid-career backbone + junior/younger generation reserves.”** How can such a “specialized elite” team take on a rapidly developing business? BOC Fund has its own answer. In terms of investment research capabilities, after more than ten years of accumulation, the team has independently completed the construction of everything from a database, a factor library, and an index analysis library to investment strategy models, and the models are also independently built and controllable. In terms of talent selection, by improving training and mentorship mechanisms as well as strict eligibility and selection processes, the team has achieved professionalized, market-oriented capability. In addition, the diverse composition of members’ backgrounds provides a good foundation for expanding the team’s business with multiple perspectives, multiple strategies, and multiple asset classes, and further improves its “coordinated combat” capability. All members of the Quantitative Index Team have graduated from first-class universities at home and abroad. Among them, 2 hold doctoral degrees, and 3 have overseas study or work experience. Their professional backgrounds cover multiple fields such as finance, financial engineering, mathematics, and statistics, effectively helping the team form a composite knowledge structure. There are both “quantitative experts” who have delved deeply for many years, and “fundamental analysts” with rich accumulation. In addition, team members also have backgrounds in system operations, product development, and index research. With the deep integration of diverse backgrounds, the team has been promoted toward expansion across multiple perspectives, strategies, and asset classes, forming core capabilities such as multi-asset allocation, quantitative models, fundamental research, and index and product development, enabling precise support for the company’s overall index-based business strategic layout. Team leader Mr. Feng Fuzi has nearly 20 years of experience in index-based business. He has participated in the formulation and design of multiple industry rules for index and ETF business, planned and developed multiple innovative product categories, and co-authored several professional books related to quantitative indices and ETFs. His unique insights into the industry also help the team better engage in the high-quality development of index-based investing. **Investment research system construction: Stick to the core orientation of “long-term value” and form a distinctive “investment research integration” closed loop** Upholding the core orientation of “long-term value” and enhancing investors’ sense of gain has become an important goal of the current public fund industry. In building its product line, BOC Fund’s Quantitative Index Team strives to create its own distinctive features. It always focuses on high-quality tracks and effective factors with long-term growth logic. **It hopes to form an index product line that enables investors to “hold it confidently, profit from it, and feel warmth.”** On this basis, leveraging the company’s investment research integration platform, as well as a large investment research system with shared central resources and cross-team coordinated linkage, the team continues to absorb and integrate research results across macro, strategy, and industry. Based on understanding macro policy trends and grasping industry trends, it extracts effective factors, builds quantitative models, and outputs index advisory-style services. **Index advisory exploration: Form a service system with distinctiveness and warmth** Given a market environment in which index products are becoming increasingly homogeneous, BOC Fund’s Quantitative Index Team emphasizes—**building a full-chain “advisory-style” service system, shifting from “providing index tools” to “teaching investors how to use the tools well.”** Previously, the team spent more than a year repeatedly refining and building a closed-loop investment advisory service output covering “index research,” “asset allocation,” and “strategy portfolios.” It transforms professional research into investment plans that investors can understand, use, and trust—so that index tools truly become a companion for investors to move forward long term. **3. BOC Fund’s path in index-based investing: Use research to drive products, use products to capture value, use advisory to convey value, and use value to accompany customers** Looking back on the product development journey of index products, BOC Fund has always adhered to the philosophy of **“using research to drive products, using products to capture value, using advisory to convey value, and using value to accompany customers.”** Based on index analysis models, macro policy, and industry trend research, it continuously improves the layout of index products. At present, the company’s index and index enhancement products cover broad-based indices (such as STAR Market 50 and ChiNext 50), thematic indices (such as HK stock connect internet and robotics), strategy indices (such as cash flow and dividend/bonus), commodities (Shanghai gold), and other sub-categories; it also has allocations across major asset classes including equities, commodities, and bonds. Among them, the BOC CSI All-Share Free Cash Flow ETF launched in 2025 is the first batch of CSI All-Share Free Cash Flow ETFs—an vivid example of BOC Fund’s commitment to putting investors first and deeply developing high-quality index product offerings. Behind the creation of this product are the company’s keen insights into the intersection of three “cycles.” First is the macroeconomic cycle. From late 2024 to early 2025, the investment research team observed that the macro economy is shifting from “pursuing growth speed” to “emphasizing quality,” with the transition of new and old drivers of growth underway and industries finding new paths for transformation and development. In this trend, the investment value of targets that can steadily generate free cash flow and also have anti-cycle capability, sustainable development capability, and dividend potential has been rising day by day. Second is the industry and policy cycle. At that time, “cash cow” type assets were entering a phase of value re-assessment. This not only reflects the stability of competitive industry patterns, but also aligns with policy directions that encourage dividends and return value to investors. Third is the investor demand cycle. Through ongoing companion-like interactions and education with investors, the company deeply felt that after experiencing market volatility, investors’ demand for “steady value appreciation” became unprecedentedly strong. They want to find allocation-oriented products that can go through cycles and hold steadily over the long term. When these three cycles converge at a single point, the window period for the “free cash flow” strategy arrives. The company developed the product immediately, and it became the first batch of managers of this index product across the entire market. The launch of the product is by no means accidental. It comes from continuous research accumulation, including the database and strategy models independently built by the team, as well as the team’s keen capture of factor effectiveness. At the same time, this product is also a representative example of publicizing the advisory-style service philosophy. After the product’s issuance, in terms of investor education, the company and the team continue to introduce, through multiple channels, the meaning of free cash flow, and explain how it differs from traditional dividend/bonus strategies—helping investors better understand this “new tool.” The team has always believed that if product layout is the lower bound of the business, then index advisory services in the future will determine the upper bound. **4. Proactive layout of the “15th Five-Year Plan (FYP)” for 2026–2030 and building a new ecosystem for index-based wealth management** At the start of 2026—the opening year of the “15th Five-Year Plan (FYP)”—BOC Fund’s Quantitative Index Team believes that the A-share market is likely to show a slow bull market characterized by upward oscillation and structural differentiation. From the perspective of asset allocation, facing uncertainty outside the market, investors may consider abandoning the approach of betting on a single track, and instead allocate from a multi-asset, multi-strategy, and long-term perspective. **Follow four key principles: diversify across multiple assets, combine multiple indices, enhance with multiple strategies, and hold for the long term.** As a witness to and deep participant in China’s public funds, BOC Fund has always upheld a customer-centered approach and promoted the wealth management transformation of the broader asset management industry. BOC Fund’s Quantitative Index Team will also provide index-based allocation services tailored to different investors based on their different risk preferences, investment time horizons, and wealth goals—helping clients achieve a reasonable balance between risk diversification and return. It builds a virtuous cycle of “product layout—experience optimization—cognition enhancement,” making it a trustworthy index companion for investors. Risk warning: Funds involve risks; investing requires caution.
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