power.sropt_test {SharpeR} | R Documentation |
Power calculations for optimal Sharpe ratio tests
Description
Compute power of test, or determine parameters to obtain target power.
Usage
power.sropt_test(df1=NULL,df2=NULL,zeta.s=NULL,
sig.level=0.05,power=NULL,ope=1)
Arguments
df1 |
the number of assets in the portfolio. |
df2 |
the number of observations. |
zeta.s |
the 'signal-to-noise' parameter, defined as ... |
sig.level |
Significance level (Type I error probability). |
power |
Power of test (1 minus Type II error probability). |
ope |
the number of observations per 'epoch'. For convenience of
interpretation, The Sharpe ratio is typically quoted in 'annualized'
units for some epoch, that is, 'per square root epoch', though returns
are observed at a frequency of |
Details
Suppose you perform a single-sample test for significance of the
optimal Sharpe ratio based on the corresponding single-sample T^2-test.
Given any four of: the effect size (the population optimal SNR,
\zeta_*
), the number of assets, the number of observations,
and the type I and type II rates, this function computes the fifth.
See ‘The Sharpe Ratio: Statistics and Applications’, section 6.3.3.
Exactly one of the parameters df1
, df2
,
zeta.s
, power
, and
sig.level
must be passed as NULL, and that parameter is determined
from the others. Notice that sig.level
has non-NULL default, so NULL
must be explicitly passed if you want to compute it.
Value
Object of class power.htest
, a list of the arguments
(including the computed one) augmented with method
, note
and n.epoch
elements, the latter is the number of epochs
under the given annualization (ope
), NA
if none given.
Author(s)
Steven E. Pav shabbychef@gmail.com
References
Pav, S. E. "The Sharpe Ratio: Statistics and Applications." CRC Press, 2021.
See Also
Other sropt:
as.sropt()
,
confint.sr()
,
dsropt()
,
is.sropt()
,
pco_sropt()
,
reannualize()
,
sropt_test()
,
sropt
Examples
anex <- power.sropt_test(8,4*253,1,0.05,NULL,ope=253)