Latest news with #algorithmicTrading
Bloomberg
31-05-2025
- Business
- Bloomberg
At 10 AM, Stock Options Soar as Retail Traders Unleash New Bots
When people talk about algorithmic traders, it evokes images of rooms full of math PhDs creating complex models that place huge trades in milliseconds after economic or earnings data is released. But now, it's retail traders who are turning in droves to automated trading, building the kind of programs in their basements more associated with Wall Street banks than the Reddit thread r/wallstreetbets. Using these systems, though, has a downside: they can result in predictable, herd-like behavior, with data from Cboe Global Markets showing trades clustered at certain times of day. There's a risk that more sophisticated market participants could exploit the predictability of small-volume traders at specific moments when retail demand for options spikes.
Yahoo
29-05-2025
- Business
- Yahoo
Hilbert Group CEO to Present Q1 2025 Report
STOCKHOLM, SE / / May 29, 2025 / Hilbert Group (STO:HILB-B)(FRA:999) Hilbert Group AB's (Nasdaq:HILB B) today announced that its Chief Executive Officer, Barnali Biswal, will present the company's Q1 financial results on Friday the 30th of May @ 09:00am CET. The presentation will cover key performance highlights, strategic initiatives, and an outlook for the coming quarters. A live webcast of the presentation will be available on the link below, with a replay accessible shortly after the event: Presentation link For further information, please contact:Barnali Biswal, CEO Hilbert Group AB orNiclas Sandström, Co-founder Hilbert Group AB+46 (0)8 502 353 00ir@ About Us Hilbert group is a quantitative investment company specializing in algorithmic trading strategies in digital asset markets. Hilbert Group is a Swedish public company and is committed to providing operational infrastructure, risk management and corporate governance that meets the ever-increasing demands of institutional investors. Hilbert Group is listed on Nasdaq First North Growth Market (ticker HILB B) with Redeye AB as Certified Adviser. For more information, visit: Attachments Hilbert Group CEO to present Q1 2025 report SOURCE: Hilbert Group View the original press release on ACCESS Newswire Sign in to access your portfolio
Mail & Guardian
26-05-2025
- Business
- Mail & Guardian
How digital trading platforms are reshaping investment paradigms in South Africa
The acceleration of financial technology across South Africa has dismantled structural impediments that historically constrained market participation. Today, the These systems replace high-cost, relationship-based brokerage models with algorithmic precision, real-time transparency and scalability. Overarchingly, this mutation signifies a broader recalibration within South African financial systems, where technological sophistication is redefining access to capital markets. Cost Compression and Structural Efficiency Traditional financial intermediaries often presented prohibitively high transaction costs and administrative burdens. Contemporary platforms, however, leverage automation to compress fees and remove procedural latency; features such as fractional share allocation and commission-free models lower the threshold for participation. Through a process of simplifying onboarding and reducing operational friction, these platforms like Intelligent Systems and Market Responsiveness The integration of predictive analytics, machine learning algorithms and real-time macroeconomic indicators has elevated the analytical capacity of digital platforms. Here, users interact with dynamic dashboards populated by live data feeds, volatility indices and currency correlations—this infrastructure accommodates probabilistic modeling of asset performance rather than reactive speculation. However, decision-making processes are increasingly guided by algorithmic pattern recognition and sentiment analysis. With the Johannesburg Stock Exchange aligning its infrastructure with global digital standards, the sophistication of available tools mirrors the functionality of leading international trading conditions. Diversification Through Non-Traditional Assets Beyond conventional securities, digital trading backdrops in South Africa have incorporated digital currencies, tokenized commodities and blockchain-referenced instruments. Here, the inclusion of decentralized financial assets introduces alternative risk profiles and correlation models to portfolio construction. Nonetheless, regulatory bodies such as the Financial Sector Conduct Authority continue to refine supervisory frameworks for these instruments, seeking a balance between market integrity and innovation. As a result, allocation strategies are shifting from linear asset classes to multidimensional configurations. Autodidactic Investment and Cognitive Capital Embedded within many platforms are educational structures that support iterative learning and strategic refinement: interactive modules, scenario simulators and market theory primers serve as foundational instruments for knowledge acquisition. Overall, these components cultivate cognitive capital critical for long-term financial agency. Meanwhile, gamified learning features are increasingly used to maintain engagement and reinforce key financial concepts through behavioral reinforcement. In the South African context, such frameworks are particularly significant, addressing systemic gaps in financial literacy and encouraging more participants to interpret and act on market signals with autonomy. Infrastructure Expansion and Mobile Integration South Africa's rapidly These advancements extend participation to areas previously disconnected from financial systems, where offline functionality and data-light modes are increasingly prioritized to accommodate bandwidth variability. As mobile bandwidth and latency improve, access to financial instruments becomes more synchronous and inclusive, boosting overall market liquidity. Social Mechanics and Peer-Based Validation Modern trading platforms now embed social verification mechanisms, allowing participants to observe, benchmark and replicate the strategies of consistently high-performing traders. These functionalities stimulate horizontal knowledge exchange rather than top-down advisory models. Equally, public trade histories, ranked performance boards and real-time strategy disclosures encourage collective learning and behavioral accountability. Within South Africa, where intergenerational wealth transfer has been historically uneven, this peer-led model introduces a digitally mediated avenue for knowledge dissemination. Regulatory Innovation and Institutional Credibility Regulatory frameworks have adapted to accommodate the technical realities of digital trading systems. The Financial Sector Conduct Authority and South African Reserve Bank have introduced layered governance models addressing identity verification, liquidity thresholds and cross-border data compliance. These interventions contribute to institutional legitimacy and facilitate capital inflows from foreign investors seeking regulated exposure to emerging African markets. The regulatory pivot also aligns local fintech practices with Legacy Institutions and Technological Convergence The presence of agile digital platforms has catalyzed strategic reconfigurations within traditional banks and asset managers, with many legacy institutions now integrating API-based trading functionalities or acquiring proprietary platforms to preserve market relevance. This convergence results in hybrid models that combine trust-based brand capital with next-generation interface design and automation. In this context, strategic partnerships with fintech startups are increasingly employed to accelerate internal innovation cycles. As market expectations shift toward immediacy, minimal fees and intuitive control, conventional firms are restructured to reflect new transactional paradigms. Future Trajectory and Market Architecture Digital platforms in South Africa are projected to incorporate increasingly sophisticated features, including adaptive portfolio balancing, behavioral signal processing and automated derivative exposure management. Looking ahead, advances in backend processing, such as modular chain architecture and zero-knowledge proof protocols, promise further latency reduction and data integrity enhancements. As algorithmic trading strategies become more accessible, the structural contours of the investment landscape will be redrawn to reflect decentralized, data-driven, and hyper-responsive methodologies. This metamorphosis encourages the development of adaptive frameworks capable of real-time portfolio optimization and risk mitigation. A Structural Realignment in Motion The proliferation of digital trading platforms across South Africa marks a critical inflection point in the nation's financial history; what once functioned as an exclusionary ecosystem is now governed by distributed systems, regulatory foresight and digital precision. Participation has expanded, costs have compressed and informational asymmetries have narrowed. These developments signal a fundamental realignment of investment paradigms—one where technology operates equally as a facilitator and gatekeeper in a newly architected financial order.
Associated Press
21-05-2025
- Business
- Associated Press
Blackalgo Unveils Its New AI-Powered Crypto Trading Platform
Dubai, UAE, May 21, 2025 (GLOBE NEWSWIRE) -- Blackalgo, an algorithmic trading company founded in 2005 in the United States, announces the launch of its crypto trading platform driven by artificial intelligence. This firm, which first tackled conventional markets before pivoting to crypto in 2017, now operates in Dubai under a proprietary trading license granted by the Virtual Assets Regulatory Authority (VARA). Blackalgo invests its own capital in these markets. It also offers non-custodial tools for users who wish to keep complete control over their assets. In doing so, the company prioritizes security and transparency, which it views as the cornerstones of success. History and Shift Toward Crypto It initially focused on automated forex and other traditional strategies, then progressively ventured into Bitcoin and altcoins in 2017. Its relocation to Dubai aimed at placing its operations under VARA's regulatory umbrella. This authority supervises companies that engage their own funds in the digital asset ecosystem. The goal: ensuring compliance, thus reassuring investors. Since obtaining its proprietary license, Blackalgo has followed strict internal guidelines. AI-Powered Trading Platform Blackalgo's new solution relies on automated trading powered by artificial intelligence. The algorithm continuously scans market data, detects trends, and executes orders without constant human input. Users can securely connect their accounts—on Binance, Bybit, IC Markets, Pepperstone, or MT4—to the platform via API. Since it is non-custodial, the platform never holds user funds. Assets remain on the investor's personal account, with Blackalgo authorized only to place trades, not withdraw capital. 'Our mission has always been about innovation, security, and user autonomy. Holding a proprietary trading license demonstrates our reliability, while letting clients maintain control of their assets fosters greater trust,' says Olivier Becquet, founder of Blackalgo. Verified Performance and Risk Management Blackalgo reveals an audited track record dating back to September 2018. Over time, it has averaged a 6% monthly return. Such past performance remains purely historical, offering no guarantee of future results. Markets shift. Strategies evolve and the algorithm does too. Robust risk management is pivotal. Stop-loss measures, prudent allocations, and volatility safeguards operate within the platform. The aim is to tackle crypto market swings without draining users' capital. Security and VARA Compliance AES-256 encryption secures the API and confidential data. Users can enable multi-factor authentication to protect account access. The company also conducts regular penetration tests and audits. A proprietary license from VARA compels rigorous governance. Blackalgo must prove the legality of its operations and the resilience of its systems, addressing regulatory expectations. 'We want our clients to feel confident. Our proprietary trading license under VARA underscores our transparent practices. We invest our own capital. We simply share our strategies with investors who wish to follow suit, yet their funds remain under their own control,' Becquet clarifies. Blackalgo plans to open its platform to new users gradually. Those interested in getting priority access can sign up for the waitlist on the official website. For investors seeking the benefits of AI insights while maintaining full authority over their funds, this approach strikes a balance of innovation, security, and user autonomy. About Blackalgo Founded in 2005, Blackalgo is a proprietary trading firm specializing in automation and AI. Headquartered in Dubai and regulated by VARA, the company's philosophy emphasizes adaptability and risk control in the ever-evolving crypto market. Its non-custodial structure reinforces user trust and autonomy. Waitlist: Disclaimer: Blackalgo Team contact(at)
Entrepreneur
20-05-2025
- Business
- Entrepreneur
How Algorithmic Trading Is Empowering Small Investors
Opinions expressed by Entrepreneur contributors are their own. Algorithmic trading used to be something only Wall Street powerhouses could afford — complex systems, massive data and lightning-fast decisions were out of reach for most. Now, that's changing. Smaller investors and startups can tap into the same fast-paced world, using tools that automate trades and react to markets in real time. It's like watching a high-speed chess match where the pieces move themselves, and you're suddenly invited to play. But with all the excitement, is it really the right move for you or your business? Let's dive in. Related: Steps to Setting up Your Own Algorithmic Trading Desk What is algorithmic trading? Algorithmic trading is when you use computer programs to automatically or semi-automatically make trades. If you're just using algorithms to do some math but still placing trades manually, that doesn't really count as full-on algorithmic trading. Initially, algorithmic trading was used to break up large orders and execute them in parts, since it is obvious that it is much easier to find a counteroffer for many small orders than for one large one. Later, it got additional meaning, and statistical data began to be included in the concept and used to simplify operations in various markets. At the very beginning, this kind of trading was available only to large stock market players, but over time, the area of application expanded. Now, any trader can afford to trade automatic systems. The perks The upsides of algorithmic trading are speed, consistency and scalability. A good algorithm can scan thousands of markets and execute trades faster than any human ever could. Software algorithms can automatically open and close trades. These robots follow pre-set rules to analyze market data and make decisions without needing the trader to step in. They don't panic-sell. They don't get greedy. They just do their job. The downsides You need serious infrastructure: low-latency servers, reliable data feeds and airtight execution. And when things go wrong (because they will), a tiny bug can mean a massive loss. Plus, it's not just about writing code — you need to understand markets deeply to create strategies that don't crumble in the real world. Algorithm traders in search of perfection constantly refine existing systems and offer new ones. Such diversity creates difficulties for the average trader, as it becomes more difficult to choose the ideal program. But that's not the whole story. Algorithmic trading uses AI to make trading decisions based on predefined rules and real-time data. These systems can execute transactions within milliseconds, which is a significant advantage in the fast-moving financial markets. Related: The Stock Market Doesn't Care About You — You Need These 5 Things to Be a Successful Day Trader Want to start an algorithmic trading business? Here's the reality check. Starting an algorithmic trading venture fine-tunes your risk management. The algorithms remove everything that sets stops and limits for you. But the truth I wish someone had told me earlier is: It's tough. Not just intellectually, but financially, technically and emotionally as well. First, the costs. You can't just run an algo trading bot on your laptop and hope to compete with Wall Street. You'll need fast servers, real-time market data (which isn't cheap) and execution systems that can fire off trades in milliseconds without crashing. One missed trade because your system lagged? That could cost you a fortune. Then there's the competition. Big hedge funds and proprietary trading firms have million-dollar budgets, elite developers and access to infrastructure you can only dream of. They're not just ahead — they're playing a different game. And while you're debugging your first strategy, they're deploying AI-enhanced systems that evolve in real time. Don't forget the bugs. One small coding error or an overlooked exchange rule can drain your account before you even know what happened. The stakes are high, and the margin for error is razor-thin. Oh, and the red tape? Expect strict regulations, compliance headaches and audits. Plus, finding and affording skilled quantitative analysts and developers is like trying to recruit for NASA on a startup budget. Advice for entrepreneurs: Taking your first step If you're an investor, it's worth considering strategies or funds that use algorithmic tools to optimize performance. If you're a startup founder or entrepreneur, it might just be the next big opportunity — if you're ready for the grind. My advice? Start learning. Use cloud-based platforms like QuantConnect to build and test your algorithms before you spend a dime on your own servers. These tools let you simulate strategies across years of market data without the upfront cost. Instead of battling giants in traditional markets, look for under-served niches — crypto, emerging markets or areas powered by alternative data (think weather patterns, shipping logs, social sentiment). These are less saturated and more forgiving to newcomers with smart ideas. Don't reinvent the wheel. Use open-source tools like Python and partner with broker APIs to handle trade execution. This saves you from building everything from scratch and lets you focus on refining your strategies. Most importantly, manage risk like your business depends on it. Because it does. Set hard loss limits. Don't overleverage. Build safety nets into every algorithm. One rogue trade can sink your startup before it sees its first round of funding. And please, talk to a lawyer early. Financial regulations are no joke. Staying compliant isn't optional — it's your license to play the game. Related: I Wasted So Much Money Making These 3 Mistakes As a Day Trader Algorithmic trading is not just a trend — it's the future of investing. For entrepreneurs and startups, it offers an opportunity to free up a lot of time to devote to other important matters of business growth. In addition, the traders will not have to worry about each transaction. While there are challenges, like costs, technical risks and fierce competition, the rewards can be significant. By starting small, staying strategic and focusing on smart risk management, algorithmic trading can be the gateway to new business opportunities and financial success.
