MC.wgt.CAPM: MC.wgt.CAPM

In raphael210/RFactorModel: A quantative tool for investment by factor Model

Description

compute the wgt vector of multi-factors by CAPM model.

Usage

MC.wgt.CAPM(TSFRs, stat = c("pearson", "spearman"), wgtmin = 0,
  wgtmax = 0.5, targetType = c("sharpe", "return", "risk", "balance"),
  riskaversion = 1, reg_results)

Arguments

TSFRs	a list of object TSFR. See Model.TSFR.
stat	a character string,indicating the methods to compute IC,could be "pearson" or "spearman".
wgtmin	set minimal factor weight.
wgtmax	set maximal factor weight.
targetType	optimization's target type, could be "return" or "risk" or "sharpe" or 'balance',default value is "sharpe".
riskaversion	risk aversion parameter for "balance" target.
reg_results	See reg.TSFR.

Value

a factor weight vector

Examples

mp <- modelPar.default()
factorIDs <- c("F000001","F000004","F000005","F000008")
FactorLists <- buildFactorLists_lcfs(factorIDs)
mps <- getMPs_FactorLists(FactorLists,modelPar=mp)
TSR <- Model.TSR(mp)
TSFRs <- Model.TSFs_byTS(MPs=mps,TS=TSR)
MC.wgt.CAPM(TSFRs)
MC.wgt.CAPM(TSFRs,wgtmin=0.05,wgtmax=0.4,targetType='risk')  
MC.wgt.CAPM(TSFRs,wgtmin=0.05,wgtmax=0.4,targetType='balance',riskaversion = 10) 
-----------------------------------------------------------------------------
MC.wgt.CAPM(reg_results=reg_results) 
MC.wgt.CAPM(wgtmin=0.05,wgtmax=0.4,targetType='balance',reg_results=reg_results) 

raphael210/RFactorModel documentation built on May 26, 2019, 11:06 p.m.