Yunikarn

05/09/2026

I have updated my Company Valuation course with a new section on sensitivity and scenario analysis.

The new material demonstrates how changes in key assumptions, such as growth rates, margins and the cost of capital, affect company value. It also explains how to construct and interpret alternative valuation scenarios.

Using the coupon link below, you can access the complete course for USD 9.99:

31/08/2026

I take you on an office tour in Aberdeen:

YUNIKARN publishes educational content in finance, applied mathemat...

25/06/2026

In this video, I test Guidy AI, a new tool developed by my friends at 365 Data Science, using Stata 17. The example is simple but useful: I ask Guidy to guide me through importing an Excel file into Stata. Instead of only giving written instructions, Guidy highlights the exact steps inside the software, showing where to click and what to do next.

This can be very helpful if you are learning a new software package, following a tutorial, or trying to complete a task without constantly switching between a video, written instructions, and the actual application.

https://youtu.be/jIIGA31kfGIY

You can download Guidy for free!

* Using Guidy AI with Stata 17
* Importing an Excel file into Stata
* Step-by-step software guidance
* How AI can support learning by doing

In this video, I test Guidy AI, a new tool developed by my friends ...

13/03/2026

I’m excited to share that my "book" (well, it is a lot more than that), Advanced Machine Learning and AI Applications in Finance, is now available on 365 Data Science.

The "book" is designed for learners who want to move beyond basic models and explore how modern machine learning and AI techniques are applied in financial analysis and decision-making.

In the course, we cover topics such as:
• Advanced machine learning methods for financial data
• AI applications in investment analysis and risk modelling
• Practical workflows using Python and modern ML tools
• Real-world finance use cases and datasets

It has been a real pleasure working with the team at 365 Data Science. They were absolutely awesome throughout the entire process—professional, supportive, and deeply committed to creating high-quality learning experiences. A big thank you to the entire team for the collaboration!

If you’re interested in machine learning, AI, and their applications in finance, you can explore the course here:

https://lnkd.in/ezy2Yt2F

This link will take you to a page that’s not on LinkedIn

19/02/2026

Recently, the media has covered student loans in the UK, focusing on high interest rates. Data - not feelings! We explore the data on balances, new loans, interest payments, and repayments. The problem is much worse than you might expect from media coverage. Is the current system sustainable?

*Hashtags*


https://youtu.be/ddx2FjDcGcw

10/02/2026

𝐅𝐫𝐞𝐞 𝐥𝐢𝐯𝐞 𝐬𝐞𝐬𝐬𝐢𝐨𝐧: 𝐑𝐢𝐬𝐤-𝐛𝐚𝐬𝐞𝐝 𝐏𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨𝐬 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧 𝐡𝐨𝐬𝐭𝐞𝐝 𝐛𝐲 Packt
𝐓𝐡𝐮𝐫𝐬𝐝𝐚𝐲, 12 February 2026, 11:00 𝐚𝐦 (𝐆𝐌𝐓)
90 𝐦𝐢𝐧𝐮𝐭𝐞𝐬 𝐨𝐟 𝐡𝐚𝐧𝐝𝐬-𝐨𝐧 𝐰𝐨𝐫𝐤 𝐰𝐢𝐭𝐡 𝐝𝐚𝐭𝐚 𝐚𝐧𝐝 𝐏𝐲𝐭𝐡𝐨𝐧

How can we allocate capital across asset classes such as stocks, commodities, and cryptocurrencies while balancing risk and return? In this free online session, we will explore portfolio optimisation in Python, moving beyond standard mean-variance approaches towards risk-based portfolios.

A basic understanding of Python is helpful (installation, IDEs, virtual environments). No strong background in finance or portfolio theory is required; the necessary concepts will be introduced during the session.

𝐎𝐮𝐭𝐥𝐢𝐧𝐞
1. Python setup
2. Getting data using APIs
3. Mean-variance optimisation
4. Portfolio optimisation in Python (CVXPY and PyPortfolioOpt)
5. Limitations of mean-variance optimisation
6. Risk-based portfolios
7. The Minimum-Risk Portfolio (MRP)
8. The Maximum Diversification Portfolio (MDP)
9. Performance comparison and backtesting

𝐑𝐞𝐠𝐢𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧
The event is free, but registration is required:

🎓 Free Virtual Workshop: Risk-Based Portfolio Optimization in Python Smarter portfolio construction using Python - balance risk, diversification, and…

29/01/2026

𝐅𝐫𝐞𝐞 𝐥𝐢𝐯𝐞 𝐬𝐞𝐬𝐬𝐢𝐨𝐧: 𝐑𝐢𝐬𝐤-𝐛𝐚𝐬𝐞𝐝 𝐏𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨𝐬 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧 𝐡𝐨𝐬𝐭𝐞𝐝 𝐛𝐲 Packt
𝐓𝐡𝐮𝐫𝐬𝐝𝐚𝐲, 12 𝐉𝐚𝐧𝐮𝐚𝐫𝐲 2026, 11:00 𝐚𝐦 (𝐆𝐌𝐓)
90 𝐦𝐢𝐧𝐮𝐭𝐞𝐬 𝐨𝐟 𝐡𝐚𝐧𝐝𝐬-𝐨𝐧 𝐰𝐨𝐫𝐤 𝐰𝐢𝐭𝐡 𝐝𝐚𝐭𝐚 𝐚𝐧𝐝 𝐏𝐲𝐭𝐡𝐨𝐧

How can we allocate capital across asset classes such as stocks, commodities, and cryptocurrencies while balancing risk and return? In this free online session, we will explore portfolio optimisation in Python, moving beyond standard mean-variance approaches towards risk-based portfolios.

A basic understanding of Python is helpful (installation, IDEs, virtual environments). No strong background in finance or portfolio theory is required; the necessary concepts will be introduced during the session.

𝐎𝐮𝐭𝐥𝐢𝐧𝐞
1. Python setup
2. Getting data using APIs
3. Mean-variance optimisation
4. Portfolio optimisation in Python (CVXPY and PyPortfolioOpt)
5. Limitations of mean-variance optimisation
6. Risk-based portfolios
7. The Minimum-Risk Portfolio (MRP)
8. The Maximum Diversification Portfolio (MDP)
9. Performance comparison and backtesting

𝐑𝐞𝐠𝐢𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧
The event is free, but registration is required:
https://luma.com/uj5bo4fl

Thanks, Abhishek Kaushik, for organizing this event!

Join us and have Fun with Python!

🎓 Free Virtual Workshop: Risk-Based Portfolio Optimization in Python Smarter portfolio construction using Python - balance risk, diversification, and…

19/11/2025

I started trading at the age of 16 - no risk - no fun - and no idea what I was doing. Of course, there is a lot you can learn to make your trading more effective.

If you are into trading and Python (of course), have a look at Jason Strimpel's algo trading event hosted by . There is a discount for early registration using EARLY20.

Join us for a hands-on, weekday edition of Algorithmic Trading with Python, this time with live trade ex*****on in real market conditions

07/07/2025

We discuss our new book on Business Analytics with Python. Are you a business student, analyst, or professional looking to master business analytics with Python? Well, I’ve got something exciting for you—our new book, Business Analytics with Python: Essential Skills for Business Students, is now available on Amazon!

https://youtu.be/OR0EwGWarOY

07/07/2025

We work through a simple example with one explanatory variable. Starting with the sum of squared residuals, we derive the slope coefficient of the regression line. It is useful to standardise variables by subtracting their mean to remove the need for a constant term.

https://youtu.be/cgMZ4Gw8nJE