Returns the Treynor ratio.
Syntax
NxTreynor($R_p$, $R_f$, Freq, $\beta$)
- $R_p$
- is the portfolio rate of returns data series (a one-dimensional array of cells (e.g., rows or columns)).
- $R_f$
- is the risk-free simple returns data (a single value or a one-dimensional array of cells (e.g., rows or columns)). If missing, a zero(0) risk-free return is assumed.
- Freq
- is the data sampling frequency per year (i.e., number of data points in one year) (e.g., 12=monthly, 4=quarterly, etc.). If missing, a monthly frequency is assumed.
- $\beta$
- is the portfolio's Capital Asset Pricing Model (CAPM) beta.
Status
The NxTreynor function is available starting with NumXL version 1.68 CAMEL.
Remarks
- The Treynor ratio is a performance metric for determining how much excess return was generated for each unit of risk taken by the portfolio.
- The Treynor ratio is expressed as follows: $$\textrm{Treynor Ratio} = \frac{R_p-R_f}{\beta}$$ Where:
- $R_p$ is the return of a given portfolio or strategy.
- $R_f$ is the risk-free return.
- $\beta$ is the CAPM Beta of the portfolio.
- The risk-free rate of return is the return of an investment with zero risks, meaning it's the return investors could expect for taking no risk. The risk-free rate could be a U.S. Treasury rate or yield, such as a one-month T-bill.
- The Treynor ratio measures how successful an investment is in compensating investors for taking on investment risk.
- By definition, all values in the input data set (i.e., $R_p$) must be greater than -1.0.
- The input data series may include missing values (e.g., #N/A, #VALUE!, #NUM!, empty cell) but will not be included in the calculations.
- If the risk-free rate of return argument contains one value, it is assumed the value is the annual percentage risk-free rate of returns.
Examples
Example 1:
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Formula | Description (Result) |
---|---|
=NxTreynore(\$B\$2:\$B\$14,12, 0.02, 1.1) | Treynor (Fund) (0.146876) |
=NxTreynore(\$C\$2:\$C\$14,12, 0.02, 1.0) | Treynor (Index) (0.028069) |
Files Examples
Related Links
References
- Hamilton, J .D.; Time Series Analysis, Princeton University Press (1994), ISBN 0-691-04289-6
- Tsay, Ruey S.; Analysis of Financial Time Series John Wiley & SONS. (2005), ISBN 0-471-690740
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