summary.sfm: Summarizing a fitted time series factor model

In factorAnalytics: Factor Analytics

Description

summary method for object of class sfm. Returned object is of class summary.sfm.

Usage

## S3 method for class 'sfm'
summary(object, se.type = c("Default", "HC", "HAC"),
  n.top = 3, ...)

## S3 method for class 'summary.sfm'
print(x, digits = 3, ...)

Arguments

object	an object of class sfm returned by fitSfm.
se.type	one of "Default", "HC" or "HAC"; option for computing HC/HAC standard errors and t-statistics. Default is "Default".
n.top	scalar; number of largest and smallest weights to display for each factor mimicking portfolio. Default is 3.
...	futher arguments passed to or from other methods.
x	an object of class summary.sfm.
digits	number of significants digits to use when printing. Default is 3.

Details

The default summary method for a fitted lm object computes the standard errors and t-statistics under the assumption of homoskedasticty. Argument se.type gives the option to compute heteroskedasticity-consistent (HC) or heteroskedasticity-autocorrelation-consistent (HAC) standard errors and t-statistics using coeftest.

Value

Returns an object of class summary.sfm. The print method for class summary.sfm outputs the call, coefficients (with standard errors and t-statistics), r-squared and residual volatilty (under the homoskedasticity assumption) for all assets as well as a summary of the factor mimicking portfolio weights.

Object of class summary.sfm is a list of length N+2 containing:

call	the function call to fitSfm
se.type	standard error type as input
sum.list	list of summaries for the N fit objects of class lm for each asset in the factor model.
mimic.sum	list of data.frame objects containing n.top largest and smallest weights for each factor mimicking portfolio.

Author(s)

Sangeetha Srinivasan

See Also

fitSfm, summary.lm

Examples

data(StockReturns)
# fit the factor model with PCA
fit <- fitSfm(r.M, k=2)

# summary of factor model fit for all assets
summary(fit, "HAC")

factorAnalytics documentation built on April 15, 2017, 11:18 a.m.