param_portf: Create a named list of model parameters that can be passed...

In algoquant/HighFreq: High Frequency Time Series Management

Create a named list of model parameters that can be passed into portfolio optimization functions.

Description

Create a named list of model parameters that can be passed into portfolio optimization functions.

Usage

param_portf(
  method = "sharpem",
  singmin = 1e-05,
  dimax = 0L,
  confl = 0.1,
  alphac = 0,
  rankw = FALSE,
  centerw = FALSE,
  scalew = "voltarget",
  voltarget = 0.01
)

Arguments

method	A character string specifying the method for calculating the portfolio weights (the default is method = "sharpem").
singmin	A numeric threshold level for discarding small singular values in order to regularize the inverse of the covariance matrix of returns (the default is 1e-5).
dimax	An integer equal to the number of singular values used for calculating the reduced inverse of the covariance matrix of returns matrix (the default is dimax = 0 - standard matrix inverse using all the singular values).
confl	The confidence level for calculating the quantiles of returns (the default is confl = 0.75).
alphac	The shrinkage intensity of returns (with values between 0 and 1 - the default is 0).
rankw	A Boolean specifying whether the weights should be ranked (the default is rankw = FALSE).
centerw	A Boolean specifying whether the weights should be centered (the default is centerw = FALSE).
scalew	A character string specifying the method for scaling the weights (the default is scalew = "voltarget").
voltarget	A numeric volatility target for scaling the weights (the default is 0.01)

Details

The function param_portf() creates a named list of model parameters that can be passed into portfolio optimization functions. For example into the functions calc_weights() and back_test(). See the function calc_weights() for more details.

The function param_portf() simplifies the creation of portfolio optimization parameter lists. The users can create a parameter list with the default values, or they can specify custom parameter values.

Value

A named list of model parameters that can be passed into portfolio optimization functions.

Examples

## Not run: 
# Create a default list of portfolio optimization parameters
controlv <- HighFreq::param_portf()
unlist(controlv)
# Create a custom list of portfolio optimization parameters
controlv <- HighFreq::param_portf(method="regular", dimax=4)
unlist(controlv)

## End(Not run)

algoquant/HighFreq documentation built on Oct. 26, 2024, 9:20 p.m.