MC.wgt.CAPM: MC.wgt.CAPM

Description Usage Arguments Value Examples

Description

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

Usage

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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

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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.