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NinjaTrader provides a trading platform for active traders dealing with futures, forex, and options. It offers tools for market analysis, advanced charting, trade simulation, and the ability to develop and run automated trading strategies. The core platform is free for advanced charting and simulated trading, while revenue comes from trade commissions, premium features, and third-party integrations. Its goal is to help traders analyze, test, and execute trades more efficiently and consistently through an extensible ecosystem of tools.
Industries
Data & Analytics
Enterprise Software
Fintech
Financial Services
Company Size
501-1,000
Company Stage
Debt Financing
Total Funding
$100M
Headquarters
Chicago, Illinois
Founded
2004
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Total Funding
$100M
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London Stock Exchange teams with Kraken's parent to launch tokenized UK equities. The London Stock Exchange is partnering with NinjaTrader Group, Kraken's parent company, to offer 24/5 trading access to tokenized UK stocks, the Financial Times reports. The London Stock Exchange is moving deeper into the digital asset era, partnering with NinjaTrader Group - the parent company of cryptocurrency exchange Kraken - to offer tokenized exposure to United Kingdom-listed equities, according to a report published by the Financial Times. The arrangement, which targets around-the-clock trading at 24 hours a day, five days a week, marks one of the most high-profile intersections of traditional exchange infrastructure and blockchain-based securities to emerge from a major Western bourse. The significance of the deal lies not just in the names attached to it, but in what it signals about the structural direction of equity markets. For decades, exchange-listed stocks have been governed by fixed trading windows, settlement cycles that stretch across days, and custody arrangements rooted in mid-twentieth-century financial plumbing. Tokenization promises to dismantle much of that legacy architecture, replacing it with programmable assets that can move on distributed ledgers at any hour, with near-instant finality. The LSE's willingness to attach its considerable institutional credibility to such an initiative suggests that promise is nearing practical reality. Why the LSE and why now. The London Stock Exchange occupies a singular position in global capital markets - it is both a national symbol of British financial power and an institution that has spent the past decade rebuilding itself as a data and technology company following its acquisition of Refinitiv. That strategic repositioning makes the embrace of tokenized equities less surprising than it might appear. The exchange has been signaling openness to digital asset innovation for several years, and the partnership with NinjaTrader Group - which controls Kraken, one of the longest-operating and most regulated cryptocurrency exchanges in the world - gives the LSE a technically credible and compliance-experienced counterpart with genuine retail and institutional crypto distribution reach. For NinjaTrader Group and Kraken, the strategic logic is equally compelling. Crypto exchanges have spent years building liquidity pools, custody infrastructure, and regulatory relationships, but the total addressable market for purely digital assets remains constrained relative to the tens of trillions of dollars sitting in traditional equities. Tokenized stocks represent the most natural bridge: they allow crypto-native platforms to offer products that are familiar to mainstream investors while keeping those assets on digital rails. Gaining access to UK-listed equities through a partnership directly with the LSE removes a critical barrier and lends institutional legitimacy that no amount of marketing spend could replicate. The 24/5 promise and its implications. The specific target of 24/5 trading - continuous access Sunday evening through Friday - is a detail worth examining carefully. It stops short of true around-the-clock, seven-day operation, which would require deeper restructuring of settlement, corporate actions processing, and regulatory oversight frameworks that are still calibrated to business-day cycles. But 24/5 coverage represents a substantial practical improvement over the current London market hours, which run roughly seven and a half hours per day. For international investors in Asia-Pacific time zones in particular, the ability to react to UK corporate news or macroeconomic data outside London's window has long been a source of frustration. Tokenized UK equities available through the evening hours of Asian trading sessions could meaningfully expand the investor base for LSE-listed companies. There is also a retail dimension that deserves attention. Platforms catering to younger retail investors have spent years conditioning their users to expect instant, always-available access to financial products. Robinhood's extended-hours trading in the United States demonstrated the appetite; tokenized equities through a crypto-native interface could accelerate the same dynamic in the United Kingdom and across the European market. If LSE-listed stocks become available through Kraken's existing user base - which spans millions of verified accounts across multiple jurisdictions - the distribution implications for UK equities liquidity are non-trivial. A broader tradfi inflection point. The LSE-NinjaTrader arrangement does not exist in isolation. Across traditional finance, the exploration of tokenized equities has accelerated meaningfully. Major custodians, asset managers, and exchanges in the United States, Switzerland, and the Asia-Pacific region have all piloted or announced tokenized securities infrastructure over the past two years. What distinguishes this particular partnership is the directness of the relationship: a top-tier exchange operator is not merely experimenting through a sandbox subsidiary but engaging with an established crypto exchange group to build a live product. That structural commitment is a meaningful step beyond the proof-of-concept phase that has characterized much of the industry's earlier activity. Regulatory clarity will remain the pivotal variable. The United Kingdom's Financial Conduct Authority has been developing its approach to digital securities under the Digital Securities Sandbox established by HM Treasury, and the success of any tokenized equity offering at scale will depend heavily on how settlement finality, investor protections, and market abuse rules are applied in a distributed ledger context. The LSE's institutional weight in those regulatory conversations should not be underestimated. What this means for markets. If the partnership delivers on its stated ambition, it could redefine the competitive landscape for equity trading in the United Kingdom. Investors who have grown accustomed to the flexibility of digital asset markets will encounter familiar underlying assets - British blue chips, growth companies, investment trusts - wrapped in infrastructure that matches their expectations for speed and availability. Traditional brokerages and wealth managers who have been slow to engage with tokenization will face renewed pressure to respond. And for the LSE itself, positioning at the center of this transition - rather than being disrupted by it - represents a strategic bet that history will likely judge as either prescient or premature. The early signals, at least, favor the former. Klaus hartmann. Banking infrastructure correspondent. Tracks the Bundesbank, the ECB and German Mittelstand financial systems. § Comments Open discussion no account needed
Algorithmic trading for beginners: from zero to your first strategy. NocNoe Team August 31, 2026 Trading Strategies algorithmic trading Algorithmic trading for beginners often feels like a wall of complex code and high-frequency math. In reality, it is the most logical evolution for any serious futures trader looking to remove emotion from their execution. Automated trading allows you to execute precise rules without the hesitation that plagues manual traders. By the end of this guide, you will understand how to start automated futures trading and deploy your first strategy on NocNoe. What is algorithmic trading? Algorithmic trading is the process of using a computer program to follow a defined set of instructions for placing a trade. These instructions are based on timing, price, quantity, or any mathematical model. For futures traders, this means your platform monitors the ES, NQ, or CL markets 23 hours a day. When your criteria are met, the trade executes instantly, often faster than a human eye can even register the price change. At NocNoe, NocNoe focus on making this transition seamless. You don't need to be a C# developer to benefit from automation; you just need a proven edge and the right infrastructure. Why beginners should start with futures. If you are looking at algorithmic trading for beginners, the futures market is the gold standard. Unlike equities, futures offer high leverage, deep liquidity, and nearly 24-hour market access. Futures contracts are standardized, making them perfect for algorithmic modeling. Whether you are trading the E-mini S&P 500 or Micro-Gold, the mechanics remain consistent across the board. Furthermore, the tax advantages (60/40 rule in the US) make futures more attractive for high-frequency automated strategies compared to standard stock trading. Step 1: understanding the infrastructure. To learn how to start automated futures trading, you must first understand the "stack." You need a data feed, a brokerage, and an execution platform. NocNoe integrates directly with NinjaTrader, the industry leader for retail futures automation. Its automated NinjaTrader strategies are designed to plug directly into your existing setup. Your infrastructure must be robust. A millisecond of latency or a dropped internet connection can be the difference between a winning trade and a catastrophic error. The Role of the VPS. Never run an automated strategy from your home laptop. Power outages and Windows updates are strategy killers. Serious algorithmic traders use a Virtual Private Server (VPS). This ensures your strategy runs 24/7 in a data center with redundant power and high-speed connections to the exchange. Step 2: defining your trading logic. An algorithm is only as good as the logic behind it. You cannot simply tell a computer to "buy when it looks cheap." You must define specific, quantifiable parameters. For example: "Buy 1 contract of MNQ when the 5-minute RSI crosses below 30 and the price is above the 200-period EMA." This level of specificity is what separates disciplined algorithmic traders from gamblers. If you can't write it down as a flowchart, you can't automate it. Common strategy types for beginners. * Trend Following: Entering trades in the direction of the prevailing momentum. * Mean Reversion: Betting that price will return to a historical average after an extreme move. * Breakout Trading: Entering when price moves outside of a defined range or volatility band. Step 3: backtesting and optimization. The biggest advantage of algorithmic trading for beginners is the ability to see the past. Backtesting allows you to run your strategy against years of historical data in seconds. However, beginners often fall into the trap of "over-optimization." This is when you tweak parameters so perfectly that they fit the past data but fail miserably in live markets. To avoid this, use "Out-of-Sample" testing. Optimize your strategy on 70% of your data, then test it on the remaining 30% to see if the performance holds up. Step 4: how to start automated futures trading with NocNoe. If building a strategy from scratch sounds daunting, NocNoe provides a shortcut. NocNoe offer institutional-grade strategies that are already coded, tested, and ready for deployment. Its Pro Tier ($99/mo) gives you access to automated NinjaTrader strategies that have been vetted by its team. You don't need to write a single line of code. By using NocNoe, you bypass the months of development and debugging. You can focus on portfolio management and risk scaling rather than syntax errors. Step 5: risk management in automation. In automated trading, your risk management must be hard-coded. You should never deploy a strategy without a mandatory stop-loss and a daily loss limit. Algorithms can fail. APIs can disconnect. A "fat finger" error in your code can liquidate an account in minutes if you haven't set hard boundaries. NocNoe recommend starting with "Micro" contracts. Trading Micro E-mini futures allows you to test your automation in live market conditions with 1/10th the financial risk of standard contracts. The importance of a trade journal. Even though the computer is doing the work, you must still monitor the performance. An automated strategy is a tool, not a "set and forget" money machine. Use the NocNoe trade journal and social features to track how your automated strategies perform against the broader market. Comparing your results on its leaderboard helps you identify if your strategy is losing its edge. If you notice a deviation between your backtest results and live results (slippage), you need to investigate immediately. This is where its AI Trading Coach becomes invaluable. Using the NocNoe AI Trading Coach. The NocNoe AI Coach analyzes your execution data to find patterns you might miss. It can identify if your strategy performs poorly during specific news events or certain times of the day. For beginners, this feedback loop is critical. It bridges the gap between "running a script" and "understanding the market." The AI Coach acts as a senior quant looking over your shoulder. Common pitfalls to avoid. When learning how to start automated futures trading, avoid these three mistakes: * Chasing High Win Rates: A strategy with a 90% win rate often has a massive "tail risk" that can wipe out your account in one trade. Focus on expectancy, not win percentage. * Ignoring Market Context: Algorithms that work in trending markets often fail in sideways markets. You must know when to turn your bot off. * Under-Capitalization: Automation requires a buffer. If your account is too small, a normal "drawdown" (a temporary dip in equity) will force a margin call before the strategy can recover. The path forward: from zero to live. The journey of algorithmic trading for beginners starts with education. Start by taking its free courses available on the NocNoe platform. Understand the basics of futures market structure before you risk a single dollar. Once you have the theory down, move to a simulated environment. Run your automated strategy in "Paper Trading" mode for at least two weeks. This ensures your execution logic is sound and your connection to the exchange is stable. When you are ready to go live, start small. Use NocNoe's Pro strategies on Micro contracts. Monitor the logs daily. Scale only when the data proves the edge is real. Join the NocNoe community. Trading is a lonely game, but algorithmic trading doesn't have to be. Its leaderboard allows you to see what other automated traders are doing and which strategies are currently leading the pack. Transparency is its core value. NocNoe don't believe in "black box" systems. NocNoe believe in providing the tools, the data, and the community to help you become a professional systematic trader. Ready to automate your edge? Stop fighting the machines and start using them. Get access to professional NinjaTrader strategies, its AI Coach, and the NocNoe leaderboard today. Conclusion. Algorithmic trading for beginners is a marathon, not a sprint. It requires technical discipline, rigorous testing, and the right partners. By leveraging the NocNoe ecosystem, you significantly reduce the barrier to entry and the time to market. The futures markets are waiting. Whether you are looking to hedge your portfolio or build a high-frequency scalping bot, the tools are now within your reach. Start your automation journey today. Risk Disclaimer: Futures trading contains substantial risk and is not for every investor. An investor could potentially lose all or more than the initial investment. Risk capital is money that can be lost without jeopardizing ones' financial security or life style. Only risk capital should be used for trading and only those with sufficient risk capital should consider trading. Past performance is not necessarily indicative of future results. Algorithmic trading involves unique risks including technical failure and model obsolescence. Risk Disclosure: Futures and forex trading contains substantial risk and is not for every investor. An investor could potentially lose all or more than the initial investment. Risk capital is money that can be lost without jeopardizing ones' financial security or life style. Only risk capital should be used for trading and only those with sufficient risk capital should consider trading. Past performance is not necessarily indicative of future results. NinjaTrader(R) is a registered trademark of NinjaTrader Group, LLC. No NinjaTrader company has any affiliation with the owner, developer, or provider of the products or services described herein, or any interest, ownership or otherwise, in any such product or service, or endorses, recommends or approves any such product or service.
Paul Stevens named NinjaTrader row regional director. * Posted fxdailyinfo * Date 10 August 2026 * View 35 NinjaTrader names Paul Stevens regional director for RoW. NinjaTrader has appointed Paul Stevens as regional director for the rest of the world (RoW), according to an update on his LinkedIn profile. Stevens started the position in June 2026 after spending more than 16 years at online trading provider IG. During his time there, he held commercial, operational, and client-facing roles. He joined NinjaTrader after nearly six years as IG's head of emerging markets. Stevens managed profit and loss for IG's emerging markets and South African operations, with responsibility for commercial strategy, customer acquisition, pricing, and expansion. Under his leadership, the business achieved double-digit annual revenue growth. New customer acquisition also rose by more than 20% year over year. In addition, Stevens created a partner channel that eventually generated 10% of new customer applications. Between 2017 and 2020, he worked as IG's global head of client performance. His responsibilities included improving client retention, refining customer segmentation, and increasing operational efficiency across the group. Earlier in his career, Stevens held positions including head of trading services for Europe, the Middle East and Africa, manager of trading services in the UK, and sales trader. Stevens is the second senior IG executive to join NinjaTrader within the past year. The futures broker hired Christopher Tripp as general manager of its international division in February. Tripp previously worked as commercial director for IG's UK entity. | Headquarters: | Suite 305, Griffith Corporate Centre, Beachmont, P.O Box 1510, Kingstown, St Vincent and the Grenadines. | | Foundation Year: | 2019 | | Country: | St Vincent and the Grenadines | | Email: | [email protected] | | Trade Platform: | MetaTrader 5, MT5 WebTerminal, MT5 for Android, MT5 for iOS, MT5 for MacOS, MetaTrader 4, MT4 WebTerminal, MT4 for Android, MT4 for iOS, MT4 for MacOS | | Acc Funding Methods: | Credit Card, Debit Card, Western Union, Perfect Money, Neteller, Skrill, FasaPay, Internal transfer, Local Deposits, Bitcoin, TrustPay, Boleto, Multiple local methods, Sticpay, PayTrust, PayRetailers, Payment Asia, Crypto, Absa, Help2pay, Pix | | Max: Leverage: | 1:2000* | | Min. Deposit: | $1 | | Base Currencies: | EUR, USD, GBP, SEK, DKK, ZAR, NOK, PLN, AUD, AED, CZK and More | | Min. Spreads: | 0.0 Spreads From |
CAIOs on the move: July 2026. This month's appointments reflect the growing recognition that artificial intelligence is no longer confined to individual business units. Chief AI Officers are working alongside CEOs, CIOs, CFOs, and business leaders to establish governance frameworks, identify high-value use cases, and ensure AI investments deliver measurable business outcomes. Below are 10 AI leadership appointments announced during July 2026. Meta announces Alexandr Wang as CAIO. Alexandr Wang joins Meta as the company's first-ever Chief AI Officer, where he leads Meta Superintelligence Labs (MSL). As Chief AI Officer, Alexandr plays an integral role in shaping Meta's AI vision and driving its strategic initiatives from concept to execution. Prior to Meta, Alexandr founded Scale AI in 2016 as a 19-year-old MIT student with the vision of providing the critical data and infrastructure needed for complex AI projects. Josh Fecteau named Chief Data and AI Officer and CIO at Teradata. Teradata announced the appointment of Josh Fecteau as Chief Data and AI Officer and Chief Information Officer, expanding his leadership responsibilities to include both enterprise technology and the company's internal data and AI strategy. Fecteau joined Teradata in 2019 and has led the company's Data and AI organization since late 2025. Arnold & Porter announces Roger Maeda as first CAIO. Arnold & Porter is pleased to announce the appointment of Roger Maeda as the firm's first Chief Artificial Intelligence Officer, reinforcing its commitment to responsible and innovative artificial intelligence and the future of technology-enabled legal services. Oz Benamram joins pillsburt Winthrop Shaw Pittman as CAIO. Oz Benamram has officially joined Pillsbury Winthrop Shaw Pittman as chief AI officer. Benamram is one of the legaltech industry's best-known names, having advised law firm leaders, legaltech companies, and investors on legal AI transformation. He has spent decades building and leading knowledge and innovation functions at several of the world's leading law firms, including Simpson Thacher, White & Case, and Morrison & Foerster. USEReady promotes Amit Phatak as CAIO. USEReady, a global AI, data, and analytics company, has announced the appointment of Amit Phatak as Chief AI Officer. In this role, Amit will lead USEReady's AI practice strategy, define the company's agentic AI positioning across industries and partner ecosystems, and drive thought leadership and market engagement as enterprises accelerate their move from AI pilots to production-grade deployments. Guy DeCorte Joins KlariVis as CAIO. KlariVis expanded its C-suite by promoting Guy DeCorte to the newly created role of Chief AI Officer to focus entirely on driving the company's artificial intelligence product roadmaps and proactive automation tools. NinjaTrader Group promotes brian Weis as first CAIO. NinjaTrader Group has created its first Chief Innovation & AI Officer role. Brian Weis, previously Chief Product Officer, has been appointed Chief Innovation & AI Officer, responsible for leading the company's artificial intelligence strategy, agent-native platform development, Model Context Protocol infrastructure and prediction market initiatives. Shobhit Varshney joins Optum as CAIO. Shobhit Varshney has been named chief AI officer at Optum. He joins from Citi, where he was global head of AI. Before that, he spent more than 13 years at IBM, most recently as head of data and AI and as a vice president and senior partner at IBM Consulting, where he led the firm's data, AI and automation business across the US, Canada and Latin America. Raptive announces John Roa as CAIO and GM of Raptive Intelligence. Raptive, a technology and media company serving creators and publishers across the open internet, has named John Roa Chief AI Officer and General Manager of Raptive Intelligence, its newly launched business unit, which is focused on supporting creator monetization and audience growth in the AI era while helping make creator expertise and consumer intent more accessible to brands, retailers, AI platforms, and other enterprise partners. Foundry appoints Kyle Roche as CAIO. Foundry has appointed Kyle Roche as chief AI officer to guide the company's technology development. Roche was the co-founder and former CEO of AI "orchestration platform" Griptape, and joined Foundry in February this year, following the company's acquisition of Griptape.
NinjaTrader Group appoints first Chief Innovation & AI Officer and new Chief Product Officer to accelerate platform growth. July 07, 2026 Brian Weis Moves into Newly Created AI Leadership Role; Former Codal Executive, Stephen Yi Joins as Chief Product Officer Chicago - July 7, 2026 - NinjaTrader Group, a global leader in retail futures trading, today announced two executive leadership appointments designed to advance the company's product and technology strategy. As AI reshapes financial markets and retail trader expectations evolve faster than ever, NinjaTrader is expanding its leadership structure to lead this innovation moment for futures trading. NinjaTrader Group has appointed Brian Weis as Chief Innovation & AI Officer, a newly created role that formalizes the company's commitment to frontier technology development. Weis, who previously served as Chief Product Officer, will lead the company's efforts in agent-native AI direction, MCP platform development, and prediction markets, taking emerging initiatives from concept to launch. "The most important work happening in trading right now is at the intersection of AI and trading infrastructure, and NinjaTrader is uniquely positioned to lead that charge," said Weis. "Traders are demanding smarter tools, faster insights, and platforms that work as hard as they do. We are making sure NinjaTrader continues to deliver on that. Accelerating AI into the next-generation trading experience is where we are today, but at a bigger and bolder scale." The company has also appointed Stephen Yi as Chief Product Officer. Yi joins from Codal, where he served as Managing Director of Product & Engineering, and brings more than a decade of trading industry experience including over 10 years at Jump Trading. "NinjaTrader has spent years successfully earning the trust of serious traders and building a leading platform," said Yi. "I am excited to join the industry's top futures trading platform as we lead the way in expanding retail trader access to capital markets innovation. I am honored to take on this role to help shape the next chapter of NinjaTrader's growth and evolution." "AI is going to fundamentally reshape how people invest and trade, and NinjaTrader's mission is to make sure our traders are on the right side of that shift," said Martin Franchi, CEO of NinjaTrader Group. "These appointments reflect our commitment to that future. Brian will push our AI and innovation agenda forward at the frontier level, and Stephen will ensure our product roadmap is built around what traders need to succeed in that world and deliver on that mission." About NinjaTrader Group NinjaTrader Group is a global leader in retail futures and trading technology. Since 2003, NinjaTrader has been empowering a community of more than 3.5 million traders with cutting-edge technology, ultra-low commissions, and world-class support. Its modern, cloud-based platform, available on desktop, web, and mobile, gives traders the freedom to seize market opportunities anytime, anywhere. NinjaTrader Clearing, LLC provides direct access to the futures markets, while NT Technologies delivers new tools, seamless NinjaTrader platform integration, and institutional-grade technology to support both individual prop traders and prop trading firms. For institutions, NinjaTrader Connect delivers a comprehensive suite of B2B solutions, providing advanced technology and financial infrastructure for technology providers. For more information, visit www.ninjatrader.com. Disclaimer: Futures trading involves substantial risk and is not suitable for everyone. Losses may exceed the initial investment. Past performance is not necessarily indicative of future results. View Risk Disclosure Statement. NinjaTrader Clearing, LLC d/b/a NinjaTrader is a CFTC-registered futures commission merchant and an NFA Member (NFA ID: 0309379). View Disclosures: ninjatrader.com/disclosures/.
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Industries
Data & Analytics
Enterprise Software
Fintech
Financial Services
Company Size
501-1,000
Company Stage
Debt Financing
Total Funding
$100M
Headquarters
Chicago, Illinois
Founded
2004
Find jobs on Simplify and start your career today