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Algorithm tradingBest Quant websites | An unconventional guide

Best Quant websites | An unconventional guide

By Chainika Thakar

Generally, a quant is a professional in the financial technology industry who designs complex algorithms with the help of quantitative analysis.

Quants are skilled in mathematics, finance, and computer skills. In the trading domain, quants design and implement algorithms to predict the price and implement trading strategies.

Finding the information that has quality is most important here because it is the information that helps to add value to our knowledge. And this knowledge can be found through quant blogs, articles, etc.

That is why we have done a thorough research and have compiled a list of websites or, let us say, quant sites in which a quant would like to invest their time and efforts in. The websites or the quant sites are divided into four categories for maintaining ease with regard to navigation. The categories are as follows:


First and foremost, we have the list of websites or quant sites that consist of the most informative blog articles for quants. Hence, the websites we are going to see below exist with a good fan following for their blogs.

How do I know about their fan base? Well, being in the industry I spoke to some quants who helped me with their favourite “quant sites” for reading blog articles. And they are:


Quantocracy is a curated mashup of algorithmic and quantitative trading blogs that aggregates some of the best articles available on the internet. They feature lots of thought-provoking and insightful articles in the quant trading domain. Quantocracy is followed by a huge community of traders and is considered one of the best in business.

Under the ‘Quant Mashup’ section, you can see some of the top-ranked blogs by the readers which will help you narrow down your search to some freely available quantitative trading strategies.

Dr. E.P. Chan’s blog

A famous practitioner and author, Dr. E. P. Chan is the Managing Member of QTS Capital Management, LLC. He is also a faculty member at QuantInsti for the EPAT programme and a popular financial blogger.

The trading community looks up to him and he is a role model for most of the aspiring algo traders out there. What better way to learn from him than his own website that covers information on the algorithmic trading platform, book reviews, posts on factor models and trading strategies?


We are a research and training institute with an aim to foster financial market professionals in the field of quantitative and algorithmic Trading.

Our blog page is best known for its high-quality content, detailed summary of selected trading strategies drafted by market experts, and a huge follower base.

The articles on our blog page are based around a broad level of categories including career advice, downloadable trading strategies, algorithmic trading, news, programming & trading tools, Python trading platforms, project work, webinars, and much more.

Moreover, for quants, there are more than 141 blog articles related to trading strategies to help with strategy creation for different markets (forex, stock, etc.). You can also check our Project Work EPAT category to access the collection of project work published by the students and alumni from their EPAT programme.

We also have several success stories about entrepreneurs, traders, developers and analysts from around the globe who gained the needed skills and began their successful trading journey. These success stories are specially mentioned to help you get inspired by their journey.


Founded in 2012 by Michael Halls-Moore, QuantStart provides educational resources for potential and practising quantitative analysts.

Some of the popular categories of articles include algorithmic trading, quant reading list, machine learning, time series, and Python implementation.


Wholly owned by IAC (NASDAQ: IAC), Investopedia is the largest financial education website in the world. Just as the name suggests, it is the encyclopaedia of the finance industry. Investopedia has a vast number of articles on anything and everything related to finance. Investopedia is the go-to destination for investors who want to make smarter financial decisions.

With a squad of data scientists and financial experts by its side, Investopedia offers financial information for its many visitors.


Started by a professor named Sandeep Jain at JIIT Noida, geeksforgeeks is a well-known computer science portal. Here you can find the answers to questions related to programming, algorithms, data structures and interview preparation material. The website is divided into different categories for delivering information and the blogs serve the purpose well.

Stack overflow

Created in 2008 by Jeff Atwood and Joel Spolsky, Stack overflow is a question answer community for programmers but has some very informative and interesting blog articles as well. They have a collection of blog articles on different topics relating to computer languages, technology professionals, the use of programming languages in medicine etc.

Question and Answer communities for programmers

Going forward, let us find out the best question and answer communities. These are the communities for programmers or quants to discuss, get the answers to certain questions and to also answer the questions of others in order to help them with their quantitative journey. These communities are:

Stack Exchange

Stack Exchange is a network of 177 communities that are created and run by experts and enthusiasts who are passionate about a specific topic. They also build libraries of high-quality questions and answers, focused on each community’s area of expertise.

One thing most important to note is that this community is more than just a casual “chit-chat” or in simple words, they are not up for discussions. Instead, they believe in the straightforward approach of asking questions and a group of people replying to the answer.

The best answers reach the top and the person who asked the question can mark one answer that works for him/her as the “accepted” one.


Quora is an American question-and-answer website where questions are asked, answered, followed, and edited by internet users. In addition to other topics, Quora offers users access to programming questions as well.

Research papers

Now, we move on to those websites or quant sites that offer some quality research papers based on topics related to Algorithmic and Quantitative trading. Some original work coming from credible resources is the real treasure for a quant.


Arxiv is an open-access repository ⁽¹⁾ of electronic preprints ⁽²⁾ and postprints ⁽³⁾ (known as e-prints ⁽⁾) approved for posting after moderation, but not peer review. It consists of scientific papers in the fields of mathematics, electrical engineering, computer science, statistics, mathematical finance, economics, etc. All the research papers can be accessed online as they are available with open-access.


SSRN was founded in 1994 by two financial economists named Michael Jensen and Wayne Marr. They have a number of specialised research networks  On the basis of a number of PDF files, backlinks and Google Scholar results.in January 2013, SSRN was ranked the biggest open-access repository in the world by Ranking Web of Repositories (an initiative by Cybermetrics Lab).


ScienceDirect is a website that was launched in March 1997. This website hosts over 18 million pieces of content from more than 4,000 academic journals and 30,000 e-books from a publisher called Elsevier. The access to the full-text requires subscription, while the bibliographic metadata ⁽⁾ is free to read.


Quantpedia is known as the encyclopaedia of quantitative trading strategies. They have thousands of financial research papers listed on their website.

With a mission to process financial academic research into a more user-friendly form to help anyone who seeks new quantitative trading strategy ideas, they have 70 freely available strategies.


ResearchGate is a European commercial social networking site for scientists and researchers to share papers, ask and answer questions, and find collaborators. While reading articles does not require registration, people who wish to become site members need to have an email address at a recognized institution or they need to be manually confirmed as a published researcher in order to sign up for an account.

Self-paced learning portals

By now, you already have a tremendous amount of “quant sites” in your knowledge bank. Let us find some free courses available online with some of them giving you hands-on experience in algorithmic trading techniques.


Quantra is an e-learning portal that specialises in Algorithmic & Quantitative Trading. Quantra offers self-paced courses that are a mix of videos, audios, presentations, multiple choice questions, and highly interactive exercises.

Quantra has been highly appreciated for all the good reasons, including high-quality courses released by them that will support your journey to become a successful algo trader.

For example, the ‘Mean Reversion Strategies in Python’ which is authored by Dr. E. P. Chan is curated by an expert with a focus exactly on trading with this particular type of trading strategy.

Some of the free courses available on Quantra are:

MIT OpenCourseWare

Also known as OCW, it is a web publication of most of the MIT course content. Anyone can freely access the content. They have two freely available courses available on their website:

  • Investments – This course will help you to learn how to make good investment-related decisions by acquiring in-depth knowledge of analytical thinking, mathematical derivation, and financial markets.
  • Topics in Mathematics with Applications in Finance – This one helps undergraduate and graduate students with the mathematical concepts and techniques used in the financial industry.


Founded by Stanford professors Andrew Ng and Daphne Koller, Coursera is a venture-backed, education-focused technology company that offers online courses in various domains.

They have some amazing courses that can also help you get online certification. I recently discovered that you can sign-up and enjoy the 7-day free trial account where most of the courses will be unlocked for you.

Here is a list of some of the relevant courses that you can access in the 7-day free trial account:

  • Trading Algorithms – The course is designed for investors and money managers who want to acquire the skills required to design their own trading strategies.
  • Advanced Trading Algorithms – This course will provide you with eight ready-made trading strategies that are based on rigorous academic research. This course will also help you design your own trading strategy, backtest it and measure the performance. The learner will also be taught scientific ways of backtesting without succumbing to either look ahead or survival bias.
  • Trading Strategies in Emerging Markets Specialization – In case you are an investor or a money manager and are looking to develop skills that can help you develop and test your own trading strategies in emerging markets then this is the course for you.


A number of websites are available online for quants but there are few which make it to the best-rated category. Different websites cater to the knowledge of the quants in the form of quant blogs, articles, research papers, courses, questions and answers communities, and market data sources.

Learn more about algorithmic trading and get on to the exciting and thrilling journey of becoming a quant with our course on Algorithmic Trading for Beginners.

Algorithmic trading for beginners is a learning track with different courses imparting essential skills required for different Quant trading desk roles. Learn the fundamentals of stock markets and how to retrieve financial market data with the courses. Also, you will learn to create and backtest trading strategies such as day trading, event-driven, SARIMA, ARCH, GARCH, volatility and statistical arbitrage trading strategies.

Hence, this bundle of courses is perfect for traders and quants who want to learn and use Python in trading.

Disclaimer: All data and information provided in this article are for informational purposes only. QuantInsti® makes no representations as to accuracy, completeness, currentness, suitability, or validity of any information in this article and will not be liable for any errors, omissions, or delays in this information or any losses, injuries, or damages arising from its display or use. All information is provided on an as-is basis.


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