Securities Market Line (SML)

The securities Market Line (SML) is a graphical representation of the Capital Asset Pricing Model (CAPM). Essentially, it displays the expected rate of return of an individual security as a function of systematic, non-diversifiable risk (its beta).

Assume that the historical market return is 12%, and the risk-free rate is 5%. The expected return of a security can then be represented as:

Ri=5%+β×(12%5%)R^{_{i}} = 5\% + \beta \times \left ( 12\% - 5\% \right )

The Securities Market Line will therefore represent the linear relationship between Ri and Beta.

If the CAPM model holds true, then all the securities should lie on the SML.

As we can see, the market has a beta of 1. If the beta of the stock is greater than 1, this means the stock’s prices are more volatile than the market, and vice versa. For example, if a stock has a beta of 1.2, this means that a 1% change in the market index will bring about a 1.2% change in the stock’s price. Stocks with high beta are considered to be more risky compared to the ones with low beta.

SML provides a cross-sectional analysis across different stocks. The average returns of two stocks will be proportional to their betas.

One important use of SML is that it can help in identifying underprices and overpriced stocks.

Consider two stocks X and Y. Both have a Beta of 0.5. However, X gives less returns than suggested by the SML, and Y gives more market returns. Both these securities are mis-priced. An arbitrageur can see this opportunity. He will short-sell Security X and use the money to purchase Security Y. If you spotted this opportunity earlier, then you will make good profits in your trade.

Membership
Learn the skills required to excel in data science and data analytics covering R, Python, machine learning, and AI.
I WANT TO JOIN
JOIN 30,000 DATA PROFESSIONALS

Free Guides - Getting Started with R and Python

Enter your name and email address below and we will email you the guides for R programming and Python.

Saylient AI Logo

Take the Next Step in Your Data Career

Join our membership for lifetime unlimited access to all our data analytics and data science learning content and resources.