**Portfolio optimization focuses on selecting the optimal combination of assets to maximize return and minimize risk. That involves determining the most appropriate weights for each asset.**
The historical performance of the assets, their correlations with each other, and other relevant factors are considered. The goal is to create a well-diversified portfolio with a balanced relationship between risk and return.
In this guide, you’ll learn how portfolio optimization works using the Markowitz model with the Sharpe Ratio. We’ve already explained the [Sharpe Ratio in detail in another article](/investment-research/portfolio-allocation-how-to-analyze-a-stock-portfolio-using-python/), which we highly recommend you read first.
Here’s an overview of the topics:
* **How do you optimize a portfolio?**
* **Data access and creating a demo portfolio**
* **Technical requirements**
* **Metrics and Exploratory Data Analysis**
* **Portfolio Optimization from Scratch**
* **Portfolio Optimization using SciPy**
* **Calculate the Efficient Frontier**
* **Portfolio performance against a benchmark**
* **Conclusion**
Let’s get started to find the optimal portfolio allocation using the Markowitz Model. 😃
The [full article](https://steady.page/en/tinztwins-hub/posts/9aa29849-33a7-46e1-a697-4eea805b4cc7) is available in our members-only area.
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