exposureHeterogeneity: Factor exposure heterogeneity from a beta screening

In PeerPerformance: Luck-Corrected Peer Performance Analysis in R

Factor exposure heterogeneity from a beta screening

Description

Aggregates the per-fund equal-performance ratios of a screen_beta = TRUE alphaScreening into the factor-by-factor heterogeneity measure of Ardia et al. (2023). For each coefficient k (the alpha and each factor beta) it reports the average equal-exposure ratio \pi^0_k = \frac1N\sum_i \pi^0_{i,k} and the heterogeneity 1-\pi^0_k: the share of peers that are significantly differentiated on coefficient k. A value close to one indicates large heterogeneity (much room to differentiate); close to zero, homogeneity.

Usage

exposureHeterogeneity(object)

Arguments

object

A SCREENING object produced with screen_beta = TRUE.

Value

A data.frame of class exposureHeterogeneity with columns coefficient, equalExposure (\pi^0_k), and heterogeneity (1-\pi^0_k).

Author(s)

David Ardia and Kris Boudt.

References

Ardia, D., Bluteau, K., Lortie-Cloutier, G., Tran, D. (2023). Factor exposure heterogeneity in green and brown stocks. Finance Research Letters 55, Part A, 103900.

See Also

alphaScreening.

Examples

data("hfdata")
set.seed(1234)
fac <- matrix(rnorm(nrow(hfdata) * 2), ncol = 2,
              dimnames = list(NULL, c("MKT", "SMB")))
sc <- alphaScreening(hfdata[, 1:20], factors = fac, screen_beta = TRUE,
                     control = list(nCore = 1))
exposureHeterogeneity(sc)

PeerPerformance documentation built on Aug. 3, 2026, 1:08 a.m.