Afleveringen
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Good day, everybody. Today is May 30th. This is now Bryan from quantlabsnet.com. Our platform is transitioning to a new web domain, and the previous one will be phased out within the next 30 days. Let's dive into an insightful article from Bettersystemtrader.com titled, A New Approach to Trading Volatility with Rob Hanna.
The article highlights the inverse relationship between the VIX and the S&P 500, and how traders can use VIX signals to time their trades on the S&P 500. Interestingly, a similar inverse relationship exists between Bitcoin and the US dollar, providing another avenue for trading strategies.
Another key point is that using the S&P 500 to time its own trades can be more effective than relying on the VIX. The article suggests that short-term indicators for the S&P 500 are better predictors of VIX movements. Additionally, traders might find value in using the S&P 500 to time the VIX, potentially reducing the length of drawdowns.
For a deeper understanding, the article includes video clips explaining these concepts. If you're into algo trading, these insights could be particularly beneficial. To stay updated, visit quantlabs.net/book and join the email list.
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In this episode, Brian from quantlabs.net delves into a fascinating article from eFinancialCareers.com about Better Hand Financial Technologies (BHFT), a high-frequency trading firm based in Dubai. BHFT has been making waves with its remote work model and strategic hires from top competitors.
New website at Home | Quantlabs (quantlabsnet.com)
Key hires include Ilya Malinovsky, former head of HFT at Tower Research Capital and Credit Suisse, and Ruslan Reskipov, previously head of derivatives and algo trading at Renaissance Capital. The firm has also attracted talent like Rook Teeter, former managing director at KCG Holding and Tower Research.
BHFT stands out by using Rust instead of the traditional C++ for its trading systems, attracting a diverse team that includes chess champions, martial arts winners, and world-class math and science talents. Despite the remote work setup, the company boasts a friendly, multicultural team with a modern tech stack.
The episode also covers BHFT’s current job listings, including roles for senior quant traders and researchers, with a notable focus on the Chinese and Indian trading markets. Brian wraps up by sharing updates about his new website, quantlabsnet.com, and invites listeners to join the new community group.
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Zijn er afleveringen die ontbreken?
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Good day, everybody! Brian here from quantlabs.net. In today's episode, we're diving into an often overlooked tool for financial analysis: Microsoft Excel. While many focus on programming and high-frequency trading, Excel provides a powerful platform for non-programmers to conduct financial research and analysis.
Get your trading tech books here books2 - QUANTLABS.NETWe'll explore various uses of Excel, such as data gathering and cleaning, trend analysis, and fundamental analysis. Learn about essential Excel functions like XNPV, IRR, VLOOKUP, and HLOOKUP, and discover how to leverage Excel's powerful features like Power Query, macros, and add-ins for advanced financial modeling.
Powering Your Research: Using Excel for Financial Analysis - QUANTLABS.NET
If you're interested in enhancing your financial analysis skills with Excel, this episode is for you. Plus, don't forget to check out our free trading books and stay updated on our upcoming website changes by joining our email list at quantlabs.net/books.
Thanks for tuning in, and have a great day!
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Good day, good day, everybody. Brian here from wantlabs.net. Today is May 28th. I'm going to have some big news coming down the pipe soon. So keep your eyes and ears and all that peeled out for it. Anyways, I came across another interesting article. I do like this BetterSystemTrader.com podcast. It's pretty good. They did a posting called 10 Insights from the Man Who Solved the Market. This is referring back to the book Jim Simons Medallion Fund. It's the book put out by Gregory Zuckerman a few years ago. So this guy, Andrew Swan Scott, read it and thought he'd provide his insights. So let's go through these.
Get your free trading tech books here books2 - QUANTLABS.NETThe first one is originality matters. Ignore conventional wisdom about the markets. Innovate and explore unique trading strategies and ideas. Look at the market differently from the herd. I totally agree with that because when you look at the markets, there's usually a star performer out there if you go out and dig for that among all the different data sources. And it could be a long-term trending strategy that you could use based on that. A good one in the past was USD Japanese Yen. Another one that was lesser known was USD Turkish Lira or Euro Turkish Lira. They did really good over the years, but now central bankers have stepped in and taken away those opportunities. Now, I don't know about the yen. That could continue, but that could lead to something that could be the next big catalyst to take us all down. But at the end of the day, looking for those sort of things, finding them, that's what gives you what they call trading edge for sure.
Number two, collaborative success. Partner with talented individuals. Foster a collaborative environment to enhance problem-solving and innovations. Again, I cannot stress this. We're hoping to have an interview with Ernie Chan and other people that have kind of trailblazed the whole quant trading space, specifically for those that are coming from the retail trading space. Because as we know, to do true HFT, high-frequency trading, and true low-level quant research and that, people can kind of do it, but you have to have a fairly big account to take advantage of it to really do the pay-to-play thing directly right on the exchanges. As a retail trader going through a retail trading broker, that's pretty hard to do. So you have to find people that are kind of in the same area as you in terms of your account size, maybe your technical chops, as well as your mathematical experience. For myself, I guess I can share this now is that I will be moving my site over to a better technology, to Wix. I'm hoping to build out a better group community through that. That's part of the WIC's features, I guess. I did have an amazing group a few years ago. They're still around. I just want to bring more people together so that they can engage with each other behind the scenes. All at a paywall, but membership privileges have its costs. So that's where you get the collaborative success. So that's what I'm hoping to bring to the table.
Okay, number three, embrace scientific rigor. Apply a rigorous scientific approach in model Model testing and validation ensuring robustness and statistical significance. This isn't really HFT, but to make life easier for a retail trader, I find using tools, very popular, very in-depth tools like TradingView helps you here. You can see instantly without going through any of the wonky backtesting packages out there, frameworks. works. Out of the box, you're ready to go. When you're working with an open source trading strategy, if you build your own, buy one, lease one, whatever on TradingView, you get the ability to see it. What's its profit potential? What is its profit factor? Which is another way of saying, if I'm going to put a dollar in, how much can I expect to get return from that via the profit factor? These are right there out of the box. So when you have these sort of instantly viewable to you from a high level, it makes your life a lot easier and a lot less stressful. A lot of people want to build and roll their own solutions. I'm not against that. But when you get up to my age, you will start to see how valuable time will be. That's all I could tell you. Efficient capital allocation. Okay. Develop systems to optimize capital allocation across various strategies to maximize returns and manage risk. One thing I can mention here, a lot of the boutique hedge funds, boutique AGFT shops, a lot of them will trade in the space of options. I don't think you can operate under a really successful trading strategy with a $1,000, $5,000 account. You need to have something fairly significant to play those kind of, I don't want to say gains, but kind of strategy capabilities. You need probably $20,000, $25,000 because you have to add all your premium and all that fun stuff. And that's why one of the reasons why ETFs are popular because they're not really risky. You can dream like a stock and there's no margin requirement any of that so these sort of things matter but if you do do the options training you can do very well if you get something that actually actually works okay let's talk number six leverage with caution use leverage strategically to amplify your returns now most people i talk to who keep their account in check from early blowing up. One of the things they do is they use no more than six times. I've seen in crypto years ago, finance would have 100 times and so on. And that's high risk when things are not going your way, especially when the assets are in a consolidation phase or downward spiraling or falling knife environment. You don't want to use leverage there. If it's a long-term trend and it's doing well, then yeah, add your leverage. Some people may go up to 12, let's say, but no more will not go more than six.
Data quality is key. Prioritize the acquisition and cleaning all extensive data sets for accurate model development and testing. Again, this is where I like TradingView. you. You can get all kinds of data sources. You'll get, let's say if you're using free data sources like Yahoo Finance, expect to get the gaps. The gaps are going to be deadweight to you and they're going to be hard to work with. So you got to use good quality data. Obviously, there's lots of sources and most of them, I think all of them are going to be paid. And if you're not willing to do that, you're going to, I don't know, if you're just playing around and experimenting, fine. But if you ever want to get serious, you got to pay for the data. And as I say what you get what you pay for is what you get so if you're going to get free stuff I expect to have a low quality. Experiences and results that's all I can tell you they have the ability to enable you to have. Enable you to have decent success there. But obviously, you got to find your proper strategy. Short-term focus, number eight, concentrate on short-term trading opportunities where predictive power is stronger and more actionable. I know one successful trader, he most likely will hear this, he's trading on one minute. Now, he's probably successful there based upon his experience, based upon his history, and he's probably blown up a lot of accounts. So the short focus can help, but this is, again, for a guy who's built and defined high-frequency trading. And obviously, sub-second, sub-minute matters if you're successful. If you're coming from the free trade world, you want to work with basically. Basically long-term, daily, four-hour. When I was writing for Seeking Alpha, they wouldn't accept articles that timeframes less than four hours. So that's just to give you a scenario depending upon who you are and where you're coming from in terms of knowledge in the world of trading.
Execution matters. Invest in technology and processes for efficient trade execution to minimize market impact and slippage the one i've come up with between trading view and the auto trading that's how trading view defines it with something like traders post is exceptional i could be sleeping at night and it trades and it's 100 fully synced that's all i can tell you there unless you try it you're not going to know except luck's rule there is a lot of luck i'm not going to deny that to you and yeah so we'll leave it at that you know basically it's like betting in a casino where if you're betting. If you're betting in Vegas, well, that means you may be riding on luck. You may have to do 10 little trades, take 10 little losses, but maybe that 11th trade may be the big one that you're seeking. But how often does that happen? No one knows. If you have a strategy that may be able to predict that, fine. And then you can work off of that for luck. So basically what this guy was saying, the author of this article here, Peter, this Andrew guy said, what Simmons, Simons and his team achieved is remarkable. We'll probably never see anything like this in our lifetime. Who knows? Computers may come up and do stuff and they may be doing it already through the AI, but we just don't know about it because these are not publicly known. They're not going to go on the internet and say, hey, look at me. I bought a Ferrari because I made an amazing AI trading solution. And if they are, they're just probably BSing. And if they're not showing they're creating journal to achieve that, well, there's a problem there. We may never know the details, but there are enough hints to guide all traders. Very true.
Yeah. And then there's interview posted here with the guy, Gregory Zuckerman. Also, I think I can say about this is that Simons was very reluctant to do the interview and to do the book. And apparently, there are some parts in the book that Simons didn't want to get revealed. But this Zuckerman still went ahead and published it. And I don't think Simons was too happy about it. I wanted to leave that as well. And I'll talk to you soon. Have a good day. Remember, get on our training books, quantlabs.net slash books. That may change soon. So do it while you can. Over and out. Thank you.
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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.
Here is a bunch of free tracing tech books books2 - QUANTLABS.NET
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!
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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.
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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.
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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.
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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.
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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.
Ger your free trading tech books here books2 - QUANTLABS.NET
More details here
Why KX kdb+ and Q Should Be Your Next Financial Power Tools - QUANTLABS.NET
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.
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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.
Get on our Discord to talk about this
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.
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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.
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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.
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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.
Get your free trading tech books books2 - QUANTLABS.NET
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!
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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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books2 - QUANTLABS.NET
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.
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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.
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Hello listeners, Brian from quantlabs.net here. In this episode, I discuss an intriguing article I read on hedgeweek.com. The title of the article was 'Quant Aspect Up 21% on Currency Market Bets'. It caught my eye, and I wanted to break it down for you all.
Aspect is a London-based quant hedge fund with a substantial 7.5 billion. It managed to score a 21% return in its flagship fund in 2021, thanks mainly to its currency market and commodities bets. As a result, Aspect scored above the 14% average for trend following funds and 3% average for discretionary macro managers over the same timeframe.
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The majority of the firm's returns came from dispersion in currencies and commodities. These were the most profitable areas given that US market performance has been lackluster recently. Commodities, especially gold and silver, were also performing well, although they dropped off a bit due to an expected US market rally.
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Aspect’s market-following trading strategies capitalized on a strengthening dollar, shorting the Japanese Yen and the Swiss franc - some of the year's worst-performing major currencies. Furthermore, the firm has been subtly adjusting its commodities position, lowering its stakes in cocoa after a record high while increasing exposure to gold and oil amidst escalating tensions in the Middle East.
What I've noticed is how the US markets have a significant influence on global trading trends. For those interested in delving deeper into this topic, check out the link to my Discord server and join my newsletter at quantlabs.net/books for more insights and free trading tech books in PDF format. Tune in to demystify the complicated world of trading currencies and commodities with me, Brian - your guide to understanding the global market pulse.
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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/
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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.
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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.
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