GRS.optimal: Optimal Level of Significance for the GRS test: Normality...
In GRS.test: GRS Test for Portfolio Efficiency, Its Statistical Power Analysis, and Optimal Significance Level Calculation
GRS.optimal R Documentation
Optimal Level of Significance for the GRS test: Normality Assumption
Description
The optimal level is calculated by minimizing expected loss from hypothesis testing
The F-distributions are used to calculate the power, under the normality assumption
Usage
GRS.optimal(T, N, K, theta, ratio, p = 0.5, k = 1, Graph = TRUE)
Arguments
T
sample size
N
the number of portfolio returns
K
the number of risk factors
theta
maximum Sharpe ratio of the K factor portfolios
ratio
theta/thetas, proportion of the potential efficiency
p
prior probability for H0, default is p = 0.5
k
relative loss, k = L2/L1, default is k = 1
Graph
show graph if TRUE. No graph otherwise
Details
Based on the power calculation of the GRS test, as in GRS (1989) <DOI:10.2307/1913625>.
The blue square in the plot is the point where the expected loss is mimimized.
The red horizontal line in the plot indicates the point of the covnentional level of significance (alpha = 0.05).
Value
opt.sig
Optimal level of significance
opt.crit
Critical value corresponding to opt.sig
opt.beta
Type II error probability corresponding to opt.sig
Note
ratio = theta/thetas
thetas = maximum Sharpe ratio of the K factor portfolios: GRS (1989) <DOI:10.2307/1913625>
Author(s)
Jae H. Kim
References
Leamer, E. 1978, Specification Searches: Ad Hoc Inference with Nonexperimental Data, Wiley, New York.
Kim, JH and Ji, P. 2015, Significance Testing in Empirical Finance: A Critical Review and Assessment, Journal of Empirical Finance 34, 1-14.
<DOI:http://dx.doi.org/10.1016/j.jempfin.2015.08.006>
Gibbons, Ross, Shanken, 1989. A test of the efficiency of a given portfolio, Econometrica, 57,1121-1152.
<DOI:10.2307/1913625>
Kim and Shamsuddin, 2017, Empirical Validity of Asset-pricing Models: Application of Optimal Significance Level and Equal Probability Test
See Also
Kim and Choi, 2017, Choosing the Level of Significance: A Decision-theoretic Approach
Examples
GRS.optimal(T=90, N=25, K=3, theta=0.25, ratio=0.4) # Figure 3 of Kim and Shamsuddin (2017)
GRS.test documentation built on July 2, 2022, 1:06 a.m.
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| GRS.optimal | R Documentation |
Optimal Level of Significance for the GRS test: Normality Assumption
Description
The optimal level is calculated by minimizing expected loss from hypothesis testing
The F-distributions are used to calculate the power, under the normality assumption
Usage
GRS.optimal(T, N, K, theta, ratio, p = 0.5, k = 1, Graph = TRUE)
Arguments
T |
sample size |
N |
the number of portfolio returns |
K |
the number of risk factors |
theta |
maximum Sharpe ratio of the K factor portfolios |
ratio |
theta/thetas, proportion of the potential efficiency |
p |
prior probability for H0, default is p = 0.5 |
k |
relative loss, k = L2/L1, default is k = 1 |
Graph |
show graph if TRUE. No graph otherwise |
Details
Based on the power calculation of the GRS test, as in GRS (1989) <DOI:10.2307/1913625>.
The blue square in the plot is the point where the expected loss is mimimized.
The red horizontal line in the plot indicates the point of the covnentional level of significance (alpha = 0.05).
Value
opt.sig |
Optimal level of significance |
opt.crit |
Critical value corresponding to opt.sig |
opt.beta |
Type II error probability corresponding to opt.sig |
Note
ratio = theta/thetas
thetas = maximum Sharpe ratio of the K factor portfolios: GRS (1989) <DOI:10.2307/1913625>
Author(s)
Jae H. Kim
References
Leamer, E. 1978, Specification Searches: Ad Hoc Inference with Nonexperimental Data, Wiley, New York.
Kim, JH and Ji, P. 2015, Significance Testing in Empirical Finance: A Critical Review and Assessment, Journal of Empirical Finance 34, 1-14. <DOI:http://dx.doi.org/10.1016/j.jempfin.2015.08.006>
Gibbons, Ross, Shanken, 1989. A test of the efficiency of a given portfolio, Econometrica, 57,1121-1152. <DOI:10.2307/1913625>
Kim and Shamsuddin, 2017, Empirical Validity of Asset-pricing Models: Application of Optimal Significance Level and Equal Probability Test
See Also
Kim and Choi, 2017, Choosing the Level of Significance: A Decision-theoretic Approach
Examples
GRS.optimal(T=90, N=25, K=3, theta=0.25, ratio=0.4) # Figure 3 of Kim and Shamsuddin (2017)
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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