[Quant Investing] The Core of Portfolio Diversification: Correlation and Beta Analysis Method (Python Tool)
[Quant Investing] The Core of Portfolio Diversification, Correlation and Beta Analysis (with a custom Python tool)
When building a portfolio, it's not enough to simply include several good stocks. Understanding how each stock relates to the market and how they move relative to each other is key to risk management. In this post, we will delve into how to analyze the correlation and beta of two stocks using a Python program developed in-house. These two indicators are essential for establishing a successful asset allocation strategy.
Stock-to-Stock Correlation and Beta Analysis Program Using Python
1. What is Correlation?
Correlation is a statistical indicator that shows how similar the movements between two assets are. The correlation coefficient has a value between -1 and +1, with the following meanings:
- Closer to +1: The two stocks move in a very similar direction. For example, Samsung Electronics and SK Hynix have a high positive correlation.
- Closer to -1: The two stocks move in opposite directions. Stocks and gold often show a negative correlation.
- Closer to 0: There is almost no significant relationship between the two stocks. This is advantageous for maximizing the effect of diversification.
Holding assets with low correlation together is an important strategy to reduce portfolio volatility and pursue stable returns.
2. What is Beta?
Beta is an indicator that shows how much the price volatility of an individual stock is relative to the volatility of the entire market. It is calculated based on the movement of a market index (e.g., S&P 500 or KOSPI).
- Beta > 1: The stock has higher volatility than the market. If the market rises by 10%, this stock is likely to rise by more than 10%.
- Beta < 1: The stock has lower volatility than the market. If the market falls by 10%, this stock is likely to fall by less than 10%.
- Beta < 0: The stock moves in the opposite direction to the market. It tends to fall when the market rises.
Beta allows you to understand how sensitive your portfolio is to market conditions, which serves as a criterion for distinguishing between aggressive and defensive investing.
3. Prerequisites for Using the Program
3.1 Python Installation
To run this program, you need to install Python and a few essential libraries. If you haven't installed Python yet, please download and install it from the official website via the link below.
3.2 Library Installation
Once Python is installed, open the command prompt (CMD) or terminal and enter the command below to install the necessary libraries all at once.
pip install yfinance PySide6 pandas numpy matplotlib certifi
4. How to Download and Run the Code File
The full code for the analysis program can be downloaded from the link below. After downloading the file, you can run the GUI program directly using Python without any separate installation process.
5. Data Input and Result Screen
5.1 Initial Screen and Data Input
When you run the program, a screen with multiple tabs will appear. Select the 'Correlation & Beta Analysis' tab and enter the desired stocks and period for analysis.
▲ Input screen for the 'Correlation & Beta Analysis' tab
On the screen above, you can select the codes and markets of the two stocks you want to analyze, as well as the market index to be used for comparison. In this example, Samsung Electronics (005930, KOSPI) and Apple (AAPL, US) are compared, and the KOSPI (^KS11) is selected as the market index for beta calculation. The period is set from September 1, 2020 to September 1, 2025.
5.2 Result Screen
After entering all the information and clicking the 'Analyze Correlation & Beta' button, the program automatically retrieves and analyzes the data. Once the analysis is complete, you can see the results as shown below.
▲ Analysis Result Screen: ① Text results and ② 30-day moving correlation graph
The result screen is divided into two main sections. First, Box ① shows the correlation and beta analysis results in text. The correlation coefficient of the two stocks is displayed along with a sentence interpreting its meaning. In addition, each stock's beta coefficient relative to the market index is also shown, allowing for a quick understanding of market sensitivity.
Next, the graph in Box ② shows the trend of the 30-day moving correlation between the two stocks. This graph allows you to visually understand how the relationship between the two assets has changed over time.
6. Final Conclusion: The First Step to Risk Management
Correlation and beta analysis are important indicators that help investors evaluate the structural stability of their portfolios, going beyond simply observing stock price fluctuations. Calculating and visualizing these indicators directly is a great help in objectively verifying investment ideas.
The program on this blog was created for educational purposes. Furthermore, the content of this blog is for reference in investment judgments only, and investment decisions should be made at the individual's own discretion and responsibility. Under no circumstances can the information on this blog be used as evidence for legal liability regarding investment outcomes.
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