# Sharpe Ratio Formula Calculator

Sharpe ratio formula calculator helps you find out the attractiveness of a risky investment. In other words, the Sharpe ratio of risky investment is equal to the volatility of net worth. The concept of the Sharp ratio calculation is firmly connected to the Capital Asset Pricing Model (CAPM) that helps you find out what is the expected return of your asset or investment according to its inherent risk level.

## Conducting Sharpe ratio calculation

To understand the background of the Sharpe ratio formula, as the first step we need to get some insights in the parameters it uses.

The Sharpe ratio formula is the following:

`Sharpe ratio = Risk Premium / Ïƒ`

`risk premium = Ra - Rf`

where:

**Risk premium**is the additional return that an investor requires to hold a risky asset rather than one that is risk-free. The CAPM calulator provides more insight for measuring risk premium together with some more explanation of risky and risk-free assets.**Ra**is the return of asset or investment.**Rf**is the risk-free return.**Ïƒ**or sigma stands for the standard deviation of a risky asset. A risky asset or investment means that it can have numerous possible outcomes. The usual measure of the spread of these possible outcomes is the standard deviation or variance. To see the statistical representation of the standard deviation, you may have a look at binomial distribution calculator.

To explain the variable *sigma* or *standard deviation* in a financial context, we aligned the following illustration that gives you more insight in a visual way. The three graphs display three different investments of possible returns.

Investment A and B offer an expected return of 10%, but A has a much wider spread of possible outcomes. Its *standard deviation* is 15%; the *standard deviation* of B is 7.5%. Investors, generally, avert uncertainty and would prefer B to A. Comparing B to C, the *standard deviation* is the same; however, the expected return is 20% from C, and only 10% from B. Most investors prefer high expected return and would, therefore, prefer C to B.

The following graph shows how the *expected return* and *standard deviation* change if you decide to set up a simple portfolio by holding a different combination of two stocks. The curved blue line represents the expected return and risk that you could achieve by various combinations of the two stocks. For example, if you invest 40% of your money in Ford and the remainder in Johnson & Johnson, your expected return is 12.3%, which is 40% of the way between the expected returns on the two stocks. The *standard deviation* is 15.9%, which is less than 40% of the way between the standard deviations of the two stocks. It is because diversification reduces risk.

However, in the real world, you are not limited to invest only in two stocks. Therefore the number of combinations are immense. In the below graph the spots represent different stocks with their *expected return* and *standard deviation*. There are many possible combinations of *expected return* and *standard deviation* from investing in a mix of these stocks. Like a reasonable investor, most probably you prefer high *expected returns* and dislike high *standard deviations*, so you would prefer portfolios along the red line. These are the **efficient portfolios**.

Taking into account the possibility of lending and borrowing further extends the range of investments possibilities. On the following graph, the red line represents the scope of *efficient portfolios*.

To find the most efficient one, you need to draw the steepest straight line from **rf** to the curved red line of *efficient portfolios*. That line will be tangent to the red curve. The *efficient portfolio* at the tangency point is the best choice as it gives you the *highest expected return* with the *lowest standard deviation*. However, also, it offers the *highest ratio of risk premium to standard deviation*. So probably you already know that the **Sharpe ratio formula** represent this ratio which is the tangency point on the red curve.