Request QuantJourney - trading approaches and backtesting with python

I've been subscribed to free emails from https://quantjourney.dev since this summer, and I'm really impressed with the quality of their free articles.

They provide a lot of practical information (new approaches) about trading strategies, all with ready-to-use Python code.

All the information is focused on backtesting different trading approaches in Python at maximum speed. They also cover fetching data for backtests without survivorship bias.

You can read more details on their Substack https://quantjourney.substack.com/ (you can also subscribe to evaluate the quality of content).
A little more information is on their home page https://quantjourney.dev/.

And now, the author proposes a paid subscription.
Here are the conditions to join - https://quantjourney.dev/membership/membership/

I propose joining for a one-year subscription to get access to the Private GitHub repository with full code. With that, we will be able to use all his approaches.

What will we get:

Read and learn from 150+ Posts on Backtesting, Strategies, Alpha, and a get code Quant Framework

To get access to CODE on GitHub and FULL archive of posts please:
full code with over 5000 lines of code and 1000+ hours of work you have to buy paid subscription.

✋ For Advanced Users: In Quant Journey, we already have over 60 in-depth posts available and more than 52,000 lines of code that you can use, modify, and fully adapt to your trading style. Adding 6-10 posts a month along with new code.

Examples of articles, you can see more articles here https://quantjourney.substack.com/s/framework

added a new post and code on Forecasting in Backtesting. It's crucial for strategy development, it combines return forecasts, regime analysis, and signals for smarter decisions. The new ForecastPredictor incorporates ML models (Random Forests, XGBoost, LightGBM) and advanced volatility estimators (Garman-Klass, Parkinson, etc.). Enjoy reading!

***
Added post on Efficient Multi-Asset Portfolio Management and introduced PortfolioData and InstrumentData Classes. This is quite a big as fully vectorized approach, which is super fast, and efficient. Enjoy reading and testing yourself!

 

right now got promo price, 375$ per year for full access with code

https://buy.stripe.com/00g2a9bvEgOJ5GMaEJ?utm_source=substack&utm_medium=email






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Black Friday Promo up to 50% OFF (Limited Time Offer)
Jakub
Nov 25







READ IN APP

Hi there,

This Black Friday only: Join our community of 3,500+ subscribers and unlock our premium library of 150+ in-depth posts - all for less than the cost of a weekly coffee . Access advanced investment strategies, quantitative analysis, and practical coding implementations that could transform your trading approach.


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Most Popular Posts Our Subscribers Love:



Decoding 101 Financial Alpha Strategies: A Parsing Approach
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Jun 7
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Alpha Design
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Momentum & Value Factors - introduction Metrics Calculation Class
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Stop-Loss, Take-Profit, Triple-Barrier & Time-Exit: Advanced Strategies for Backtesting
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Executing orders with Interactive Brokers - Order Management System (OMS) + RabbitMQ
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For python traders, have a look at the latest free email from quanjourney.
Multifactor strategies with code tested very easy with his custom test library.
Tried to upload pdf from email, but forum engine does not allow this, file about 3mb seem is too large

 

Black friday ends 30 november.
Really, nobody want to join?

Black Friday, unlock 150+ premium posts and gain the tools, insights, and frameworks to find and refine your edge. Join 3,500+ subscribers mastering advanced investment strategies, quantitative analysis, and practical coding techniques - and 150+ active users already leveraging our Quant Journey Framework to accelerate their trading strategies.

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Up. Top material for python+trading lovers.

 

@GOODMEN @Admin can you create a group buy?
The previous topic from the same author was popular https://clubbingbuy.com/threads/python-for-quant-finance.13637/page-4#post-411328