apply.paramset: Apply a paramset to the strategy

In R-Finance/quantstrat: Quantitative Strategy Model Framework

Description

This function will run applyStrategy() on portfolio.st, once for each parameter combination as specified by the parameter distributions and constraints in the paramset. Results are gathered and returned as a list containing a slot for each parameter combination.

Usage

apply.paramset(strategy.st, paramset.label, portfolio.st, account.st,
  mktdata = NULL, nsamples = 0, user.func = NULL, user.args = NULL,
  calc = "slave", audit = NULL, packages = NULL, verbose = FALSE,
  paramsets, ...)

Arguments

strategy.st	the name of the strategy object
paramset.label	a label uniquely identifying the paramset within the strategy
portfolio.st	the name of the portfolio
account.st	the name of the account
mktdata	optional xts mktdata object, will be passed unchanged to applyStrategy
nsamples	if > 0 then take a sample of only size nsamples from the paramset
user.func	an optional user-supplied function to be run for each param.combo at the end, either on the slave or on the master (see calc)
user.args	user-supplied list of arguments for user.func
calc	'slave' to run updatePortfolio() and tradesStats() on the slave and return all portfolios and orderbooks as a list: higher parallelization but more data transfer between master and slave; 'master' to have updatePortf() and tradeStats() run at the master and return all portfolios and orderbooks in the .blotter and .strategy environments resp: less parallelization but also less data transfer between slave and master; default is 'slave'
packages	a vector specifying names of R packages to be loaded by the slave, default NULL
audit	a user-specified environment to store a copy of all portfolios, orderbooks and other data from the tests, or NULL to trash this information
verbose	return full information, in particular the .blotter environment, default FALSE
paramsets	a user-sepcified (sub)set of paramsets to run
...	any other passthru parameters

Details

apply.paramset uses the foreach package to start the runs for each parameter combination, and as such allows for parallel processing. It is up to the caller to load and register an appropriate backend, eg. doMC, doParallel or doRedis.

Author(s)

Jan Humme

See Also

add.distribution.constraint, add.distribution.constraint, delete.paramset

R-Finance/quantstrat documentation built on May 8, 2019, 4:50 a.m.