Description Usage Arguments Value Author(s) References See Also Examples
Calculates total attribution effects over multiple
periods using Davies and Laker linking method. Used
internally by the Attribution
function.
Arithmetic attribution effects do not naturally link over
time. This function uses Davies and Laker linking method
to compute total attribution effects. Arithmetic excess
returns are decomposed as follows:
Rp - Rb = Allocation + Selection + Interaction
Allocation = ∏^{T}_{t=1}(1+bs_{t})-∏^{T}_{t=1}(1+R_{bt})
Selection = ∏^{T}_{t=1}(1+rs_{t})-∏^{T}_{t=1}(1+R_{bt})
Interaction = ∏^{T}_{t=1}(1+R_{pt})-∏^{T}_{t=1}(1+rs_{t})- ∏^{T}_{t=1}(1+bs_{t})+∏^{T}_{t=1}(1+R_{bt})
Rpi - portfolio returns at period i, Rbi - benchmark returns at period i, rsi - selection notional fund returns at period i, bsi - allocation notional fund returns at period i, T - number of periods
1 | DaviesLaker(Rp, wp, Rb, wb)
|
Rp |
xts of portfolio returns |
wp |
xts of portfolio weights |
Rb |
xts of benchmark returns |
wb |
xts of benchmark weights |
This function returns the data.frame with original attribution effects and total attribution effects over multiple periods
Andrii Babii
Bacon, C. Practical Portfolio Performance
Measurement and Attribution. Wiley. 2004. p. 201-204
Davies, O. and Laker, D. (2001) Multiple-period
performance attribution using the Brinson model. Journal
of Performance Measurement. Fall. p. 12-22
Attribution
Menchero
Grap
Carino
Attribution.geometric
Frongello
1 2 | data(attrib)
DaviesLaker(Rp = attrib.returns[, 1:10], wp = attrib.weights[1, ], Rb = attrib.returns[, 11:20], wb = attrib.weights[2, ])
|
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