Returns the Treynor ratio.
Syntax
NxTreynor($R_p$, $R_f$, Freq, $\beta$)
 $R_p$
 is the portfolio rate of returns data series (a onedimensional array of cells (e.g., rows or columns)).
 $R_f$
 is the riskfree simple returns data (a single value or a onedimensional array of cells (e.g., rows or columns)). If missing, a zero(0) riskfree 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: $$\textrm{Treynor Ratio} = \frac{R_pR_f}{\beta}$$ Where:
 $R_p$ is the return of a given portfolio or strategy.
 $R_f$ is the riskfree return.
 $\beta$ is the CAPM Beta of the portfolio.
 The riskfree 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 riskfree rate could be a U.S. Treasury rate or yield, such as a onemonth Tbill.
 The Treynor ratio measures how successful an investment is in providing compensation to 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 they will not be included in the calculations.
 If the riskfree rate of return argument contains one value, it is assumed the value is the annual percentage riskfree rate of returns.
Examples
Example 1:


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 0691042896
 Tsay, Ruey S.; Analysis of Financial Time Series John Wiley & SONS. (2005), ISBN 0471690740
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