TrackingError: Calculate Tracking Error of returns against a benchmark

In JFE: Tools and GUI for Analyzing Time Series Data of Just Finance and Econometrics

Calculate Tracking Error of returns against a benchmark

Description

A measure of the unexplained portion of performance relative to a benchmark.

Usage

TrackingError(Ra, Rb, scale = NA)

Arguments

Ra	an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns
Rb	return vector of the benchmark asset
scale	number of periods in a year (daily scale = 252, monthly scale = 12, quarterly scale = 4)

Details

Tracking error is calculated by taking the square root of the average of the squared deviations between the investment's returns and the benchmark's returns, then multiplying the result by the square root of the scale of the returns.

TrackingError = \sqrt{\sum\frac{(R_{a}-R_{b})^{2}}{len(R_{a})\sqrt{scale}}}

Author(s)

Ho Tsung-wu <[e-mail]>, College of Management, National Taiwan Normal University.

References

Sharpe, W.F. The Sharpe Ratio,Journal of Portfolio Management,Fall 1994, 49-58.
See also package PerformanceAnalytics.

See Also

InformationRatio TrackingError

Examples

  data(assetReturns)
	assetReturns=assetReturns["2011::2018"] #short sample for fast example
	Ra=assetReturns[, -29]
	Rb=assetReturns[,29] #DJI

  TrackingError(Ra, Rb)

JFE documentation built on Aug. 28, 2023, 9:06 a.m.