Quant Trading Live Report QuantLabs.net

Hello everybody, Brian here from quantlabs.net. Today is May 23rd. I just wanted to go over two podcasts I'm putting out today. I haven't done anything in a while. If you want to know why, just hold out to the end and I'll fill you in.
 
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Weird Algo Strategies, Controversial Claims, and Exciting Website Updates! - QUANTLABS.NET
One of the sources that I use is bettersystemtrader.com. And the title I thought was interesting. It's called Weird NASDAQ Algo Strategy. It's a bit weird, but it's also quite profitable. There's an associated video with it on YouTube. The creator, Thomas Nesnidal, shares the source code in easy language for TradeStation. He explains why you shouldn't be afraid of strategies like this and how they can work on multiple markets.
Another topic I cover is about a controversial video quoting Jesus, where the creator claims to be better than 99% of all hedge fund managers. He talks about learning programming in three months and making money through ETFs and high-performing ETFs based around big tech, using Robinhood.
I also provide an update on the new website coming, which will be 100% custom coded by myself using Python Django with Wagtail. I've been looking for a new web hosting provider and decided to move to DigitalOcean. The new website will be more news-driven, focusing on various investment sectors and providing free samples to generate responses.
Additionally, I discuss my new deep scanning analysis for ETFs, which involves analyzing ETFs globally and categorizing them into different sectors. This method helps identify high-performing ETFs based on profitability percentage and profit factor.
Lastly, I mention the importance of transparency in trading. I plan to sync my trading account with TraderSync to share my performance and learnings with the community. The new website will also feature a big news section, moving content from my Discord channels to the public site.
Thank you for listening. If you want to know more, I've got my newsletter and trading PDFs at quantlabs.net/books. Stay tuned for more updates!

Join Brian from quantlabs.net as he delves into the complexities of high-frequency trading (HFT) and provides valuable insights for software engineers aiming to transition into this competitive field. This episode covers the essential technical and trading concepts you need to grasp, from order books to matching engines, and explores the specialized knowledge required to excel in HFT firms.
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Breaking into High-Frequency Trading: Essential Career Insights - QUANTLABS.NET
Brian discusses the journey of transitioning into HFT, misconceptions about the field, and the key areas of expertise needed. Topics include order book dynamics, pricing engines, option pricing, and the intricacies of protocols like FIX. Additionally, he shares practical tips for impressing in interviews and thriving in the fast-paced environment of HFT shops.
Don't miss this comprehensive guide to navigating the world of high-frequency trading and setting yourself up for success in one of the most lucrative sectors in finance.

In this podcast, we discuss a recently published Hedgeweek article focusing on Renaissance Technologies, also known as Rentech, and their acquisition of GameStop and AMC shares. These shares surged in value, prompting questions around the validity of Rentech's actions and whether this was a calculated investment decision or potential insider trading.
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We delve into the intricate mechanisms of the stock market, highlighting how Rentech's sophisticated quantitative modeling and data-driven investment strategies could have possibly predicted and benefited from this phenomenon. However, with a focus on potential insider trading, we question whether the Securities and Exchange Commission (SEC) should be investigating this situation.
 
Renaissance's Meme Stock Bet Insider Trading or Savvy Investing? - QUANTLABS.NET
The podcast also considers the broader implications of Rentech potentially being involved in this 'Meme Stock' rally, discussing the potential damage to their reputation, potential regulatory changes, and the effect on the general stock market. The participation of other traders and potential collusion via social media are other facets explored in relation to this complicated issue.
The potential consequences of the SEC finding evidence of wrongdoing within Rentech are also considered, with the discussion speculating on the possible outcome of hefty fines, criminal charges, and reputational damage. We emphasize the broader message such verdicts would send to other hedge funds and the critical importance of ethical investing.
Despite the potential risks, the discussion acknowledges the possibility that if no wrongdoing is found, this venture could be considered a successful well-timed strategy, which could inadvertently solidify the reputation of Rentech.
The podcast concludes with the potential impact this 'Meme Stock' saga might have on future regulations aimed at preventing market manipulation and protecting investors, acknowledging that increased participation of retail traders, prompted by social media, could influence stock market volatility and unconventional investment strategies.
Sign up for our newsletter for more insights into market trends and get free trading books at quantlabs.net books.

Join Brian from Quantlabs.net in this episode as he unveils the impressive revamp of their website, enhancing user experience to new levels and offering a glimpse into the possibilities offered by their services. Understand the evolving landscape of algo trading, the challenges of credibility it faces, and how Brian and his team are finding success through empirical evidence of their trading prowess.
 
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Learn about the exciting world of algo trading and auto trading, and how platforms like TradingView are revolutionizing the way we trade and invest. This episode gives a detailed comparison between algo trading and automated trading, underlining the feasibility of the latter for everyday people. Discover how TradingView is experiencing a boom in the social trading community, surpassing giants like Bloomberg and CNBC in terms of audience size.
Algo Trading, Transparency, and Building Your Trading Journey with Quantlabs.net V2 - QUANTLABS.NET
This episode also dives into portfolio management, emphasizing the importance of being proactive in managing your own investments rather than heavily depending on financial advisors. Explore the potential risks and benefits of integrating cryptocurrencies in your portfolio and gain insights into both passive and active portfolio strategies.
Last but not least, the episode stresses the need to showcase real trading results, sift through the lessons learnt from them, and maintain an active awareness of the financial markets. Join the experience to challenge your perceptions about trading, break free from traditional approaches, and dive into the vibrant world of algo/auto trading.

On this episode, I expound on the extraordinary life and legacy of Jim Simons, a mathematician, successful hedge fund manager, and a philanthropist who made an unwavering impact on Wall Street. Simons, the founder of Renaissance Technologies is widely considered one of the world's greatest investors.
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In the late '70s, Simons switched career paths and entered finance, founding the company we know today as Renaissance Technologies. This marked the beginning of his journey into quantitative finance, an industry to which he would become one of the most innovative pioneers.
As I explain, Simons always sought out PhDs in Physics, math, and computer science rather than MBAs, opting for the deep technical knowledge these fields offered - a trend that marks Wall Street's hiring culture today. Simons was driven by the power of data analysis and was always on the lookout for hidden patterns in data that the human eye could not perceive, leading to Renaissance Technology's extraordinary success.
We also delve into how Simons' legacy continues through his philanthropic efforts especially in the sphere of mathematical and scientific education. His foundation, the Simons Foundation, has donated billions of dollars to these causes, making a significant impact and demonstrating his deep belief in education.
Simons' life stands as a testament to the power of applying a scientific lens to complex problems and his pioneering spirit in the world of finance. He will be long remembered as a visionary in his field.
Join me in looking through the life of this extraordinary man and dive into the intricacies that led to his phenomenal success.

In this enlightening conversation, a veteran developer advocate from KX unfolds critical insights about the compelling database, KDB Plus. Journeying through her personal evolution from an apprentice to an advocate, she delves into the launch and progression of KDB Plus and the cost columnar structure that enhances its query efficiency.
This is an interview and webinar presentation with Michaela Woods who is Developer Advocate at KX.
Beyond the basics, she highlights the extensive resources available for learning KDB Plus — from books to online training academies – and emphasizes the significant role of community spaces such as forums and online platforms for knowledge share and query solution.
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More details here
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The discussion takes a turn, exploring KX Academy's course structure designed to equip learners with fundamental to advanced understanding of handling massive time-series data and creating custom functions. Demonstrating the sandbox feature, Michaela highlights the beauty of learning in a hosted environment without the need for installations. Michaela concludes with a glance at their advanced courses, tailor-made for individuals wanting to master KDB Plus.
Moving on, the conversation introduces a more modern development – PyKx. Shedding light on PyKx's rising popularity, it describes how Python integration is expanding KDB Plus's accessibility to software applications with its enticing interfaces for new users, without replacing the underlying Q language.
Discussion further covers the inclusive certification programs by KDB and its successful implementation in the manufacturing sector. Lastly, it dives into the recently launched developments: KDB AI and KDB Insights, exploring how they are innovatively reshaping data storage, retrieval, and cloud-based workloads.
This comprehensive discussion is designed to equip developers and beginners alike to leverage KDB Plus and PyKx for efficient time-series data handling and enhanced data analysis.