Quant Trading Live Report

A Deep Dive About Coming Chinese Quant Firm International Expansion

In this episode, Brian from quantlabs.net takes a deep look at the international expansion of Chinese quantitative hedge funds. Drawing insights from an article on hedgeweek.com entitled "Chinese Quants Look to International Expansion," he analyzes the implications and potential opportunities arising from this trend. Chinese quant firms are rapidly gaining attention in the investment world and their potential for expansion beyond China is massive.

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Brian underscores how increased domestic scrutiny from Chinese regulators has led some Chinese quant funds to escalate international activity. For instance, companies like MS Capital and DH Fund Management are ramping up their overseas operations. Despite the prevailing pessimistic views about the Chinese market, Brian observes that the Chinese stock market seems to be stabilizing and showing signs of improvement.

Citing examples of Chinese quant funds broadening their horizons, Brian recognizes the strides made by MS Capital and DH Fund Management. Both companies are evolving their strategies by attracting offshore investors and prepping to venture into global markets. Even the Beijing-based Ubiquant is planning to establish a U.S. office. The rate of international expansion for Chinese quant hedge funds is accelerating due to domestic market regulations.

Finally, Brian also mentions possible investment opportunities in these emerging Chinese quant funds for Western investors. The episode ends with Brian encouraging listeners to join his newsletter and the QuantLabs Discord server for more insights into these promising markets and potential investment opportunities.

 

https://quantlabs.net/blog/2024/04/a-deep-dive-about-coming-chinese-quant-firm-international-expansion/

Essential Resources, Books and Tip for Quant Research Career

Welcome to another episode with Brian from quantlabs.net, recorded on the 22nd of April. In this episode, Brian explores two significant forum posts that have recently caught his attention on quant.stackexchange.com. The central theme revolves around resources to learn algo trading quant development. Our host provides some impressive insights that could be beneficial for those interested in quantitative trading.

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A user's question on the forum sparks the discussion - the user is a full-time stack developer for three years and is now interested in learning algo trading quant dev development. They are seeking advice on resources, books, and suitable programming languages to learn. Brian shares one effective resource he stumbled upon - Wilmot.com. It isn't just a job-posting site, but it also includes details on who the job postings are for. The likes of JP Morgan, Goldman Sachs, HSBC are just few names from the list. This resource might be useful for anyone looking to delve deeper into the quant industry.

Moving on, Brian discusses a vast list of books available on quant.stackexchange.com that can be beneficial for anyone venturing into quantitative finance. He warns about the potential for analysis paralysis given the extensive list. He also shares his top picks from the list, including books from Mark Joshi and Dr. Ernie Chan, and more. He also alludes to some upcoming interviews with industry experts like Robert Pardo and the later Dr. Ernie Chan on his YouTube channel and podcast.

Apart from those, Brian recommends three more books to dive into quantitative finance. They include 'The Concept of Practiced Mathematical Finance' by Mark Joshi, 'Paul Wilmont on Quantitative Finance' by Paul Wilmont, and 'Options, Futures, and Other Derivatives' by John Hall. He advises new entrants to start with Paul Wilmott's book series which covers all major components of quant.

Finally, Brian introduces TradersPost.io, a service that can help interested individuals to get up and running quickly in the world of algorithmic trading with minimal programming. Once again, he invites listeners to join his Discord community to discuss these topics more and sign up for his email list for some big announcements. He concludes the episode looking hopeful to get Dr. Ernie Chan again on the show for another interview on his latest company launch on machine learning.

Market Efficiency Impacton the future of Quant

In this informative and thought-provoking episode, Brian from quantlabs.net discusses a significant topic pertaining to the future of Quant. He addresses a subreddit post regarding the inherent demand for quant in the next five to ten years. While highlighting the undeniable potential impact of AI on the growing industry, he also offers listeners invaluable advice, critical insights and answers to various comments from the online community.

Brian contemplates on the matter of AI developing to replace many sectors, regardless of seniority, and further changing the landscape of Quant. Utilizing both ChatGPT and Google Gemini's latest version, Brian encourages users to employ AI to generate lucrative ideas and implementations. He responds to a comment suggesting domination by those with PhDs in statistics and physics, and shares his insights on the drastic influence AI will have on making markets more efficient.

Moreover, Brian delves into further comments about the future of math PhDs in the industry. He dissects how AI influences the software engineering field and the potential implications for quant and modelling research. Brian ponders over a statement suggesting no need for quants in the future due to market efficiency and draws parallels with the SEO industry. The discussion further extends to the introduction of AI in markets and the resulting consequences for various sectors.

Drawing the podcast to a close, Brian addresses several humorous and thought-provoking comments, leading back to the role of AI. He provides a fitting conclusion to the conversation about the future of quant, emphasizing both the potential opportunities and threats AI imposes. For individuals keen on learning more about the quant world, Brian points you to informative resources on quantlabs.net and invites you to engage in the discussion on their Discord server. Tune in for unique perspectives and valuable insights.

Mastering Automated Trading With TraderPost.io and Interactive Brokers

In this insightful episode, Brian from quantlabs.net reveals how to maximize your trading experiences using TraderPost.io and Interactive Brokers. This step-by-step guide covers setting up and connection processes, benefits of the platform, and how to deal with potential difficulties. From Interactive Brokers' unique single connection feature to TraderPost.io's automatic daily reset option, this episode provides all the need-to-know details. Learn how to set up confirmation via email for every trade, ensuring utmost security and peace of mind.

In the latter part of the discussion, Brian simplifies TradingView's alert box setup with practical tips and addresses the common confusion between strategy definitions in TradingView and TraderPost.io. This segment is invaluable for anyone seeking to harness the full potential of these incredible platforms.

The episode further delves into TraderPost.io's strategic code usage with Pinescript and its seamless integration with popular platforms like TradingView and Interactive Brokers. For safeguarding your transactions and mitigating risks, solutions are shared that are proven to be effective and reliable.

Additionally, Brian unveils the future plans of TraderPost.io involving support integrations with renowned brokers such as Coinbase and Kraken. This episode not only offers tangible tips but also provides an adaptable outlook on trading techniques in relation to market changes. It is an essential listen for savvy investors and beginners alike who want to explore and excel in automated trading.

Your Solution for Executing Trades with TradingPost.io

In this instructive video, Brian from SmallLabs.net provides a detailed walkthrough of TraderPost.io's back-end functionalities. This trading solution hosts a range of user-friendly features - from custom code support to Discord bot creation, and comprehensive live trading options.

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One of TraderPost.io's most impressive features is its extensive webhook connectivity, enabling users with no programming knowledge to execute trades in supported platforms such as TradingView. Moreover, the platform supports a plethora of reputable live brokers, including Interactive Brokers, TradeStation, TD Ameritrade, and Coinbase, with more to come in the future.

Prior podcast here 

Your Solution for Executing Trades with TradingPost.io - QUANTLABS.NET

In this detailed discussion, Brian focuses on the importance of understanding the asset classes available, the associated costs, and selecting the correct account tier based on desired asset class. Explore the potential of trading three asset classes at a cost of $200 per month, and the restrictions linked with opting for a single asset class.

Cryptocurrency trading is highlighted as a case study, with emphasis placed on the volatility of the asset class, and the options available for trading ETFs through Interactive Brokers. In addition, Brian speculates on the future inclusion of Bitcoin and Solana on the same platform.

The video also delves into the benefits of employing TradingView's open-source strategy, providing viewers with a guide on selecting their preferred strategy, and utilizing the platform's extensive Pine script library. We also explore the challenges and potential solutions related to linking with the Trader Workstation (TWS), and connecting with Interactive Brokers via TradingPost.io's web portal.

In regards to security, Brian discusses the risks associated with connecting to a broker via a public URL or webhook, while simultaneously highlighting how TraderPost.io mitigates such concerns by ensuring a secure connection with the chosen broker.

Finally, dealing with the setbacks of high-frequency trading on TradingView and TradingPost.io is discussed, alongside advice on testing paper trading for Interactive Brokers and live trading on Coinbase. To conclude, viewers are invited to join the SmallLabs.net Discord group and email list, and are given a sneak peek into upcoming plans for a new website.

A New Frontier for Algo Traders Who Don't Program

Join Brian of QuantLabs.net as he delves deep into the world of automated trading. In this podcast, he shares his insights into the limitations of TradingView's automated trading feature and discusses some alternative solutions. Discover how to work around these limitations and take your automated trading strategies to the next level. Brian also introduces tradingpost.io, a service that promises to simplify the process and make trading faster and easier.

Throughout this podcast, Brian stresses the importance of fully understanding the vulnerabilities of any trading system. Whether it's the potential for hacking or unexpected trading hiccups, being aware of these issues is crucial for success. As he explores the services offered by tradingpost.io, he explains what makes this platform stand out in the world of automated trading. If you've wanted to streamline your trading process but didn't know where to start, this podcast could provide the insights you've been searching for.

Brian also discusses the potential benefits and drawbacks of working with multiple brokers. With a platform like tradingpost.io, managing and monitoring trades across different accounts could become an easier task. Listeners also get a firsthand account of the types of programming required for such a system. Discover why Brian believes that traders could reap considerable advantages from integrating tradingpost.io into their trading strategies.

Beyond automated trading and tradingpost.io, listeners can also expect to receive insights into the latest developments in AI, brokerage support, and more. With Brian's years of experience and technical expertise, this podcast promises to deliver valuable knowledge for any trader interested in automated trading.

AI, Expert Developers, and Open Source Dependencies

In this podcast episode, Brian from Quantlabs.net shares his opinions on managing open source dependencies and software upgrades, with a focus on the amalgamation of AI and expert developers. He highlights the significant difficulties these tasks can pose, but also indicates potential solutions - notably artificial intelligence (AI) co-generation techniques.

Further, Brian explores the concept of code generation, and its effectiveness in completing these arduous undertakings. He puts to the test various options regarding AI, including Google Gemini and Microsoft Copilot. He underscores the key aspect of how effective the AI model depends on how prompts are formulated, commonly referred to as "prompt engineering". He showcases the power and convenience of such AI models through concrete examples, notably an arbitrage script for gold assets.

The conversation also covers the accessibility of different tools, their advantages, and potential drawbacks. Particularly, the constraints and complexities of open source software such as Lama 2 and Startcoder 2 are examined. Lastly, Brian opens the door to further discussions on tools for managing software upgrades and dependencies on his Discord channel and his Sub Stack.

 

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Is It Necessary Or A Friction To Market Freedom?

Welcome to the latest episode of Brian from quantlabs.net's podcast. This discussion dives into the current debate concerning the regulation of artificial intelligence (AI) in the trading industry. Brian examines an article from risk.net which covers the concerns raised by market participants about the Monetary Futures Trading Commission's approach towards managing AI in trading. Jennifer Hahn, Chief Counsel and Head of Regulatory Affairs at Managed Funds Association, argues for leveraging the existing regulatory framework instead of developing redundant regulations.

In the backdrop of the rise of web3 projects and state control over software development, Brian asks pertinent questions about the balance between upholding a free society and ensuring scams are mitigated against. Reflecting on the revolution AI has brought to trading and the risks associated with it, Brian's in-depth analysis explores how automation of trades and remote hosting of code could pose threats to not only markets but entire economies.

Brian believes regulators have a role in countering systematic risks, particularly when it might threaten financial stability. Although the extent and process of regulation remain contentious. Drawing parallels from the military and banking sectors, he raises concerns about the seeming lack of regulation on AI in the trading operations of large companies. He calls for scrutiny of the practices of large trading entities like Citadel, Black Rock, and Vanguard.

Wrapping up the episode, Brian invites his listeners to join discussions via the podcast as well as on platforms like Substack and TradingView. With his hard-hitting reflections on a topical issue, this podcast sparks profound thoughts on the intersection of AI, trading, and regulation.

What are Your Questions Algo Trading Legend - Robert Pardo

In this riveting episode, we dive into the world of algorithmic trading with one of its pioneers - Robert Pardo. With decades of market analysis and strategy creation under his belt, Pardo is an expert high-performance trader, application professional, and the founder of Pardo & Company. A man of stellar reputation, his trading program XT99 Diversified has been recognized for its top-tier performance over and again.

Robert Pardo, widely recognized as a trading industry titan, has been a consultant to prestigious trading firms such as Goldman Sachs and Daiwa Securities America. His groundbreaking efforts in the industry are unsurpassed, particularly his creation of Walk Forward Analysis - the gold standard in strategy validation.

 

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What are Your Questions Algo Trading Legend - Robert Pardo - QUANTLABS.NET

 In this enlightening podcast episode, we offer the opportunity for our listeners to forward their pressing questions to this industry pundit by emailing us.

Don't miss this chance to gain invaluable insights from an industry legend. Send us your questions, subscribe to our podcast to keep abreast of this impending interview, and join our discord server for engaging trading discourse.

Also, get free trading book PDFs at quantlabs.net/books. Stay tuned as we have a new, advanced, and highly flexible website in the works that will provide a customized strategy integrating seamlessly with our current strategies and analysis. We are excited to bring you something truly special so watch this space!

 

Exploring the Power of KDB+ for High-Frequency Trading and Data Analytics

This podcast by Brian from QuantLabs.net dives into the world of High-Frequency Trading (HFT) and the role of KDB+ in this domain.

• KDB+: Developed by KX, KDB+ is a high-performance software used for data handling in HFT. It excels at working with large time-series datasets and is known for its:

  • Efficiency
  • Uncomplicated code structure
  • Python integration
  • Cloud interoperability

• KDB+ and Ticker Plant: Ticker Plant can be used to feed data into KDB+, making it a popular combination for HFT applications.

• Cost: A major barrier to entry for KDB+ is its high cost, estimated to be around $100,000 per year. This limits its use primarily to the well-funded fintech industry.

• Future Potential: Despite the cost, KDB+ remains a dominant player due to its performance and features. Brian discusses the potential of KDB+ to evolve even further with advancements in technology and AI.

• Call to Action: Brian invites listeners to join his Discord community to discuss KDB+ and related topics.

Exploring the Power of KDB+ for High-Frequency Trading and Data Analytics - QUANTLABS.NET

Welcome everyone, Brian from QuantLabs.net is here with another intriguing episode. In this episode, Brian dives deep into the world of High-Frequency Trading and advanced data analytics, emphasizing the role of KBD+ in it. Touching upon a previous episode of the podcast on the same topic, he delves into the intricacies of software like the Ticker Plant.

Brian explains that KDB+, produced by KX, is a high-standard enterprise-level software known for its efficient data handling capabilities. As he deconstructs the workings of this software, he highlights how Ticker Plant could write all incoming records to a log file, pushing all data to the RDP. This software, although widely unknown, is an industry standard.

The focus then shifts to the price aspect of KDB+, and the barriers it poses for widespread market adoption. Discussing a comment on Hacker News, Brian brings to light the exorbitant cost of KDB+, estimated at around a hundred thousand dollars per year. As per the comment, software is extremely lucrative and can only be afforded by the fintech industry.

Despite the cost, KDB+ comes highly praised. A comment Brian brings up highlights KDB+ as an elegant solution for running analytics on large data sets, especially those with time series. Known for its performance, uncomplicated code structure, Python integration, and cloud interoperability, KDB+ has been a dominant player in electronic trading analytics on Wall Street for over 20 years.

In conclusion, Brian discusses the potential of KDB+, which opens avenues for potential business opportunities. He emphasizes how innovations in technology and AI could lead to exploring beyond the limitations imposed by network cards. Following his exploration of KDB+ and its potential, he invites listeners to join his Discord community and actively engage in stimulating discussions.

 

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