Not exact matches
To
test robustness of influencers, they consider: (1) subsamples to
test consistency over time; (2) daily and monthly measurements to
test consistency across
sampling frequencies (except consumer price indexes, available only monthly); and, (3) contemporaneous and one period - lagged (predictive) relationships.
To
test robustness of findings, they: (1) account for one - way trading frictions ranging from 0.02 % to 0.05 % across assets; (2) consider five subperiods to
test consistency over time; and, (3) perform out - of -
sample tests using the first part of each subperiod to select the best rules and roughly the last year to measure performance of these rules out - of -
sample.
To
test the
robustness of the strategy's performance, we consider a
sample period commencing with inception of SPDR S&P 500 (SPY) as a convenient and low - cost proxy for the S&P 500 Index.
It is therefore customary in the field to
test phenotypic
robustness by studying not only the protein encoded by the most probabilistic sequence at a given node, but also the proteins encoded by alternative reconstructions derived from random
sampling from the posterior probability distribution at the node.
We also
tested its
robustness with a smaller
sample size in only one population (as in the Danish
samples studied here), and under admixture (Supplementary Note 5, Supplementary Fig. 7).