Quant Trading Live Report QuantLabs.net

In this enlightening episode, join our host, Brian from quantlabs.net as he delves deep into the exciting world of latency and high frequency trading, with a primary focus on C++. This episode promises to pull you deep into the nuts and bolts of performance optimization, providing a comprehensive exploration of latency-sensitive applications and how they impact the Memory Subsystem. It's a world of code, geekiness, and high-level trading intelligence that promises to inform and captivate any tech-minded enthusiast.
 
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Follow along as Brian navigates a revealing article found on the CPP subreddit, labeled 'Latency Sensitive Applications and the Memory Subsystem: Keeping the Data in the Cache - Johnny's Software Lab'. From exploring the advantages of hardware-based HFT systems and the importance of effective cache management techniques - the conversation spans critical areas of software and hardware performance optimization in trading environments.
Not just an overview, Brian also takes a deep dive into coding techniques designed to minimize latency and maximize performance. You'll gain insight into coding examples, discussions around the use of hardware and software cache warming, the impact of different caching approaches on performance, and why a customized, well-articulated architecture is a must-have in achieving low latency.
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Beyond just coding, Brian also looks at the broader landscape, touching on the importance and role of various hardware in reducing latency and even extends the conversation to the cloud space, touching on the challenges and opportunities in leveraging Cloud vNICs.
Demystifying Latency: A C++ Deep Dive into High-Frequency Trading - QUANTLABS.NET
Whether you're interested in quant, trading, or improving your understanding of C++ techniques for optimizing latency, this podcast promises to leave you with a wealth of knowledge and insights that will help you navigate the world of high-frequency trading. Come along for this engaging journey through the intersection of streamlining software performance and trading technology.

G'day everybody! In this episode, we delve into the nitty-gritty and complex world of high-frequency trading (HFT). Through a detailed analysis of a recent technical post on quant.stackexchange.com, we explore the critical role of market-makers in HFT, their requirements, strategies, and response times in dynamic market conditions.
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Market makers operate swiftly, adjusting their quotes to reflect real-time market dynamics. The time taken for sending quotes and receiving a hit in HFT could be around 1.5 milliseconds, which exemplifies the speed with which these players operate. The actual figures might vary, depending on the sophistication and speed of the underlying infrastructure.
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When a quote is hit, the response time isn't instant because of the computational processes required. Market makers must analyse the complexity of their algorithms, prevailing market conditions, and improve their technical framework for better efficiency and reduced latency. Regulatory and operational considerations also play a part in their decision making.
 
High-Frequency Trading: Unveiling the Market Maker's Dance - QUANTLABS.NET
 
Needing no cooling-off period nor limitations, the speed at which market makers replace their quotes depends on the computational capability of their system. They rapidly adjust their quotes in high-frequency trading. If multiple quotes are hit simultaneously, they reassess their strategies, potentially widening their spreads or dynamically adjusting their pricing to manage their risk exposure.
Don't be fooled into thinking it's all about speed, though. High-frequency trading also necessitates technologically advanced data processing capabilities, refined algorithms, sophisticated risk management models, and constant vigilance of regulatory compliance. Market makers must be continually looking for strategic enhancements in each of these areas to maintain a competative edge.
All things said, this is a fascinating peek into the complex world of HFT and market making. If these concepts intrigue you, perhaps it's worth delving deeper to get a better understanding of what's happening behind the scenes in the world of finance.

Join Brian from Quantlabs.net as he demystifies the world of Forex trading, uncovers the potential origins of Bitcoin, and discusses the evolution of his website, introducing the newly launching Quantlabs.net version 2. He debunks the often overemphasized credibility of 'verified trading gurus' and underlines adaptability and transparency as key aspects of successful trading.
 
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Delving into the enigmatic origins of Bitcoin, Brian presents a provocative theory suggesting its creation might be linked to the US intelligence services. By his referencing the NSA and the Bank of International Settlements, he raises fascinating inquiries into the origin and potential influence of Bitcoin.
 
Demystifying Markets, Unveiling Origins of Bitcoin, and Charting the Future - QUANTLABS.NET
In a conversation about the uncertain future of cryptocurrency, Brian provides valuable predictions and reflects on the potential impact of emerging legislative structures in England, Russia, and China. This debate is pivotal for anyone seeking to understand the future of this volatile investment sector.
Furthermore, Brian discusses the impending shift in real estate dynamics, exploring potential changes to the landlord-tenant relationship and rent control legislation. With a spotlight on independent landlords, this discussion serves as a comprehensive guide to anyone interested in property investment or the future of the real estate market.
Moving to the technological aspect of trading, Brian shares his experiences transitioning from WordPress to Django for his website's advancement. This valuable insight perfectly serves individuals and businesses considering a similar switch to increase control and counter traffic decline.
The episode concludes with Brian showcasing a revolutionary trading system that integrates TradingView and TradersPost.io, aiming to optimize trading processes and decrease trader workload. Both trading novices and seasoned investors will find this discussion enlightening and potentially transformational for their trading practices.

In this episode of QuantLabs, our host Ryan delves into the world of algorithmic (algo) trading within the realms of real crypto exchanges and Bitcoin ETFs. Drawing from his experience with TraderPost.io, Coinbase, and Interactive Brokers, he provides an insight-rich perspective on active investment in the volatile crypto market.
 
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Listen in as Ryan debates the pros and cons of trading crypto on platforms like Coinbase or Interactive Brokers, versus opting for ETFs such as BlackRock. The episode sparks an intriguing question for traders: "Will the allure of high returns from altcoins triumph over the safety of Bitcoin ETFs or vice versa?"
 
Should You Algo Trade with a Real Crypto Exchange or a Bitcoin ETF Only? - QUANTLABS.NET
Discover the role that firms like BlackRock play in influencing Bitcoin prices, and learn about potential conflicts of interest in this domain. With a consideration on the differences in operational hours between crypto exchanges (24/7 trading) and traditional ETFs. Ryan underlines the significance of customization and flexibility in algo trading.
This episode is a treasure trove of knowledge about aspects such as risk tolerance, price control, market participation, and algo trading techniques. Whether you're a full-time trader or a casual one, this guide will help you make calculated decisions in your investment journey.
Dive into discussions about the complexity and security concerns related to real exchanges, the reduced risk and high liquidity options of Bitcoin ETFs, and the factors to consider when deciding between the two. You will also gain insight into relevant market conditions, potential benefits, and drawbacks for each option.
 
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Cap off this episode with a detailed discourse on BlackRock ETF, Coinbase, and the impact of shifting market conditions on trading decisions. Don't miss out on comprehensive price analyses and a chance to interact with a fast-growing trading community. Tune in to QuantLabs for insights and resources!
Happy trading!

Join Brian as he shares valuable insights about the transition from an MBA Finance degree to a career in Algo Trading. As technological advancements spiral, the finance industry is rapidly evolving with a focus on algorithm trading, which currently represents over 80% of all trades. In this episode, Brian points out the financial acumen, analytical competence, problem-solving skills, and trading knowledge required for the transition.
 
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In this transformative progression, Brian emphasizes the importance of Python and its libraries for beginners and C++ for advanced trading. However, one must not forget the main aim is to showcase trading skills, not language proficiency. Brian provides information about the Algo Trading concepts, specifically backtesting, different order types, and different algorithmic trading strategies, to aid listeners in their journey.
Alluding to the stiff competition in the finance industry, Brian advises listeners to acquire professional accreditations like a Chartered Financial Analyst (CFA) or a Certified Algo Trader to hone their skills and stand out. He also recommends getting involved in LinkedIn groups, webinars, conferences, and coding competitions to further expose their skills.
Finally, Brian talks about the necessity of not just having theoretical knowledge but also practical experience in trading real money. He warns his listeners of the fierce competition, especially from Chinese firms, and the importance of staying updated with the latest technology and quant analysis techniques.
For those aiming for the best-paying jobs, Brian advises to go all in - equip yourselves with degrees and recognitions from top universities, acquire a CFA, focus intensely on your coding and trading skills, and finally, be prepared to face a challenging and competitive environment.
Tune in to this informative talk and embark on your journey from an MBA Finance degree to a successful Algo Trader.

Welcome to the tutorial session for automated cryptocurrency trading. Brian from quantlabs.net will take you through the process of establishing live automated trading on your TradingView account with TradersPost.io and Coinbase. This highly informative discussion, recorded on April 23rd, 2024, explores the seamless connection between these platforms, enabling live trading and automated trading using Coinbase, currently the only supported broker for Traders Post IO when it comes to cryptocurrencies.
 
Automate Your Crypto Game: TradingView, TradersPost.io, and Coinbase - QUANTLABS.NET
 
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The talk further elaborates on the real-time support of Coinbase and anticipates the addition of Kraken broker. Brian helps you navigate through the setup of TradersPost.io and TradingView with his YouTube video playlist, offering detailed insights into payload, messaging, etc., essential for setting up automated trading. There is also a mention of the Traders Post IO’s auto-submit option that allows fully automated trade setups once the user becomes a paying customer and gains confidence in the workings of the system.
The tutorial provides a Canadian perspective, pointing out the limitations of certain countries in trading US dollar in Coinbase and Kraken. The discussion delves deeper into the creation of alerts in Bitcoin and Ethereum, the triggering of signals into TradersPost.io, and the importance of familiarizing yourself with the full features of TradersPost.io before starting live trading.
Successfully managing your position sizing is another critical topic that is covered. You will learn about the different options available, like trading a percentage of your portfolio. This can also vary based on the size of your portfolio. There is also the option to override Traders Post IO settings right from the Pine script of Trading View. The tutorial highlights the importance of understanding the options and using the Traders Post IO’s support for any assistance.
Finally, the tutorial walks you through the Coinbase section of the TradersPost.io account, ensuring it's live and enabled. On imminent trading, you either approve or reject the order manually or opt for an automated trade. This allows for a smooth trading experience without having to worry about constant maintenance or sitting by a computer placing orders manually.
Brian wraps up by inviting those interested to join the conversation on his Discord server. He also encourages viewers to sign up for his newsletter for the latest updates and gain access to quantlabs.net books. Overall, this talk gives a comprehensive overview of the seamless trading experience between Coinbase, TradersPost.io, and TradingView.