Grap: calculates total attribution effects using GRAP smoothing

In R-Finance/PortfolioAttribution: Performance attribution tools used for identifying sources of portfolio return and risk.

Description

Calculates total attribution effects over multiple periods using GRAP linking method. Used internally by the Attribution function. Arithmetic attribution effects do not naturally link over time. This function uses GRAP smoothing algorithm to adjust attribution effects so that they can be summed up over multiple periods Attribution effect are multiplied by the adjustment factor

At' = At * Gt

where

G_{t}=∏^{t-1}_{i=1}(1+R_{pi})\times∏^{n}_{t+1}(1+R_{bi})

At' - adjusted attribution effects at period t, At - unadjusted attribution effects at period t, Rpi - portfolio returns at period i, Rbi - benchmark returns at period i, Rp - total portfolio returns, Rb - total benchmark returns, n - number of periods The total arithmetic excess returns can be explained in terms of the sum of adjusted attribution effects:

R_{p} - R_{b} = ∑^{n}_{t=1}≤ft(Allocation_{t}+Selection_{t}+ Interaction_{t}\right)

Usage

  Grap(rp, rb, attributions, adjusted)

Arguments

rp	xts of portfolio returns
rb	xts of benchmark returns
attributions	xts with attribution effects
adjusted	TRUE/FALSE, whether to show original or smoothed attribution effects for each period

Value

returns a data frame with original attribution effects and total attribution effects over multiple periods

Author(s)

Andrii Babii

References

Bacon, C. Practical Portfolio Performance Measurement and Attribution. Wiley. 2004. p. 196-199
GRAP (Groupe de Recherche en Attribution de Performance) (1997) Synthese des modeles d'attribution de performance. Paris, Mars.

See Also

Attribution
Menchero
Carino
Frongello
Attribution.geometric

Examples

data(attrib)
Grap(rp = attrib.returns[, 21], rb = attrib.returns[, 22], attributions = attrib.allocation, adjusted = FALSE)

R-Finance/PortfolioAttribution documentation built on May 8, 2019, 4:48 a.m.