CoCalc -- estimators.R

GitHub Repository: braverock/portfolioanalytics
Path: blob/master/sandbox/riskbudgetpaper(superseded)/R_Allocation/estimators.R
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# Function for data cleaning
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#-------------------------------------------
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cleaning = function(mData, alpha , trim=1e-3)
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{
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   T=dim(mData)[1];
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   N=dim(mData)[2];
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   MCD = covMcd(mData,alpha=1-alpha)
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   mu = as.matrix(MCD$raw.center) #no reweighting
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   sigma = MCD$raw.cov 
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   invSigma = solve(sigma);
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   vd2t = c();
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   cleaneddata = mData
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   outlierdate = c()
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   # 1. Sort the data in function of their extremeness
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   # Extremeness is proxied by the robustly estimated squared Mahalanbobis distance
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   for(t in c(1:T) )
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   {
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      d2t = as.matrix(mData[t,]-mu)%*%invSigma%*%t(as.matrix(mData[t,]-mu));      
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      vd2t = c(vd2t,d2t);
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   }
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   sortt = sort(vd2t,index.return=TRUE)$ix
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   # 2. Outlier detection
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   # 2.1. Only the alpha most extreme observations can be qualified as outliers
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   T.alpha = floor(T * (1-alpha))+1
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   cleanedt=sortt[c(T.alpha:T)]  
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   # 2.2. multivariate winsorization (Khan et al, 2007) : 
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   # bound the MD of the most exteme observations to a quantile of the chi squared distribution, N df
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   for(t in cleanedt ){
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        if(vd2t[t]>qchisq(1-trim,N)){
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              # print(c("Observation",as.character(date[t]),"is detected as outlier and cleaned") );
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               cleaneddata[t,] = sqrt(qchisq(1-trim,N)/vd2t[t])*mData[t,]; 
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               outlierdate = c(outlierdate,date[t]) } }
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   return(list(cleaneddata,outlierdate))
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}
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# Definition of statistics needed to compute Gaussian and modified VaR and ES for univariate time series
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#---------------------------------------------------------------------------------------------------------
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centeredmoment = function(series,power)
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{
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   location = mean(series);
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   out = sum( (series-location)^power  )/length(series);
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   return(out);
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}
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skew = function(series)
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{
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   m2 = centeredmoment(series,2)
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   m3 = centeredmoment(series,3)
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   out = m3 / m2^(3/2)
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   return(out)
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}
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exkur =  function(series)
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{
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   m2 = centeredmoment(series,2)
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   m4 = centeredmoment(series,4)
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   out = m4 / m2^(2) - 3
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   return(out)
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}
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pvalJB = function(series)
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{
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   m2 = centeredmoment(series,2)
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   m3 = centeredmoment(series,3)
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   m4 = centeredmoment(series,4)
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   skew = m3 / m2^(3/2);
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   exkur = m4 / m2^(2) - 3;
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   JB = ( length(series)/6 )*( skew^2 + (1/4)*(exkur^2) )
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   out = 1-pchisq(JB,df=2)
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}
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gausVaR =  function(series,alpha)
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{
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   location = mean(series);
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   m2 = centeredmoment(series,2)
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   out = - location - qnorm(alpha)*sqrt(m2)
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   return(out)
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}
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gausES =  function(series,alpha)
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{
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   location = mean(series);
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   m2 = centeredmoment(series,2)
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   out = - location + dnorm(qnorm(alpha))*sqrt(m2)/alpha
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   return(out)
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}
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MVaR =  function(series,alpha,r)
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{
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   z = qnorm(alpha)
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   location = mean(series);
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   m2 = centeredmoment(series,2)
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   m3 = centeredmoment(series,3)
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   m4 = centeredmoment(series,4)
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   skew = m3 / m2^(3/2);
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   exkurt = m4 / m2^(2) - 3;
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   h = z + (1/6)*(z^2 -1)*skew 
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   if(r==2){ h = h + (1/24)*(z^3 - 3*z)*exkurt - (1/36)*(2*z^3 - 5*z)*skew^2; }
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   out = - location - h*sqrt(m2)
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   return(out)
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}
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Ipower = function(power,h)
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{
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   fullprod = 1;
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   if( (power%%2)==0 ) #even number: number mod is zero
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   {
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      pstar = power/2;
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      for(j in c(1:pstar))
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      {
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         fullprod = fullprod*(2*j)
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      }
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      I = fullprod*dnorm(h);
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      for(i in c(1:pstar) )
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      { 
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         prod = 1;
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         for(j in c(1:i) )
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         {
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            prod = prod*(2*j)
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         }
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         I = I + (fullprod/prod)*(h^(2*i))*dnorm(h)
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      }
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   }
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   else{
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      pstar = (power-1)/2
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      for(j in c(0:pstar) )
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      {
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         fullprod = fullprod*( (2*j)+1 )
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      }
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      I = -fullprod*pnorm(h);
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      for(i in c(0:pstar) )
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      { 
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         prod = 1;
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         for(j in c(0:i) )
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         {
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            prod = prod*( (2*j) + 1 )
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         }
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         I = I + (fullprod/prod)*(h^(  (2*i) + 1))*dnorm(h)
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      }
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   }
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   return(I)
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}
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MES =  function(series,alpha,r=2)
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{
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   z = qnorm(alpha)
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   location = mean(series);
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   m2 = centeredmoment(series,2)
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   m3 = centeredmoment(series,3)
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   m4 = centeredmoment(series,4)
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   skew = m3 / m2^(3/2);
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   exkurt = m4 / m2^(2) - 3;
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   h = z + (1/6)*(z^2 -1)*skew 
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   if(r==2){ h = h + (1/24)*(z^3 - 3*z)*exkurt - (1/36)*(2*z^3 - 5*z)*skew^2};
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   MES = dnorm(h)
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   MES = MES + (1/24)*(   Ipower(4,h) - 6*Ipower(2,h) + 3*dnorm(h)   )*exkurt
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   MES = MES +  (1/6)*(   Ipower(3,h) - 3*Ipower(1,h)   )*skew;
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   MES = MES + (1/72)*(  Ipower(6,h) -15*Ipower(4,h)+ 45*Ipower(2,h) - 15*dnorm(h) )*(skew^2)
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   MES = - location + (sqrt(m2)/alpha)*MES
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   return(MES)
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}
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operMES =  function(series,alpha,r)
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{
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   z = qnorm(alpha)
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   location = mean(series);
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   m2 = centeredmoment(series,2)
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   m3 = centeredmoment(series,3)
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   m4 = centeredmoment(series,4)
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   skew = m3 / m2^(3/2);
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   exkurt = m4 / m2^(2) - 3;
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   h = z + (1/6)*(z^2 -1)*skew 
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   if(r==2){ h = h + (1/24)*(z^3 - 3*z)*exkurt - (1/36)*(2*z^3 - 5*z)*skew^2};
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   MES = dnorm(h)
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   MES = MES + (1/24)*(   Ipower(4,h) - 6*Ipower(2,h) + 3*dnorm(h)   )*exkurt
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   MES = MES +  (1/6)*(   Ipower(3,h) - 3*Ipower(1,h)   )*skew;
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   MES = MES + (1/72)*(  Ipower(6,h) -15*Ipower(4,h)+ 45*Ipower(2,h) - 15*dnorm(h) )*(skew^2)
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   MES = - location - (sqrt(m2))*min( -MES/alpha , h )
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   return(MES)
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}
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# Definition of statistics needed to compute Gaussian and modified VaR and ES for the return series of portfolios
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# and to compute the contributions to portfolio downside risk, made by the different positions in the portfolio.
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#----------------------------------------------------------------------------------------------------------------
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m2 = function(w,sigma)
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{
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   return(t(w)%*%sigma%*%w)
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}
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derm2 = function(w,sigma)
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{
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   return(2*sigma%*%w)
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}
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m3 = function(w,M3)
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{
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   return(t(w)%*%M3%*%(w%x%w))
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}
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derm3 = function(w,M3)
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{
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   return(3*M3%*%(w%x%w))
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}
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m4 = function(w,M4)
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{
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   return(t(w)%*%M4%*%(w%x%w%x%w))
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}
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derm4 = function(w,M4)
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{
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   return(4*M4%*%(w%x%w%x%w))
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}
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precision = 4;
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Portmean = function(w,mu,precision=4)
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{
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   return( list(  round( t(w)%*%mu , precision) , round ( as.vector(w)*as.vector(mu) , precision ) , round( as.vector(w)*as.vector(mu)/t(w)%*%mu) , precision) )
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}
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Portsd =  function(w,sigma,precision=4)
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{
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   pm2 = m2(w,sigma)
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   dpm2 = derm2(w,sigma)
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   dersd = (0.5*as.vector(dpm2))/sqrt(pm2);
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   contrib = dersd*as.vector(w)
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   return(list(  round( sqrt(pm2) , precision ) , round( contrib , precision ) , round ( contrib/sqrt(pm2) , precision) )) 
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}
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PortgausVaR =  function(alpha,w,mu,sigma,precision=4)
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{
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   location = t(w)%*%mu
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   pm2 = m2(w,sigma)
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   dpm2 = derm2(w,sigma)
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   VaR = - location - qnorm(alpha)*sqrt(pm2)
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   derVaR = - as.vector(mu)- qnorm(alpha)*(0.5*as.vector(dpm2))/sqrt(pm2);
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   contrib = derVaR*as.vector(w) 
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   return(list( round( VaR , precision ) , round ( contrib , precision ) , round( contrib/VaR , precision) )) 
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}
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PortgausES =  function(alpha,w,mu,sigma,precision=4)
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{
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   location = t(w)%*%mu
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   pm2 = m2(w,sigma)
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   dpm2 = derm2(w,sigma)
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   ES = - location + dnorm(qnorm(alpha))*sqrt(pm2)/alpha
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   derES = - as.vector(mu) + (1/alpha)*dnorm(qnorm(alpha))*(0.5*as.vector(dpm2))/sqrt(pm2);
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   contrib = as.vector(w)*derES;
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   return(list( round( ES , precision ) , round( contrib , precision) , round( contrib/ES , precision) )) 
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}
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PortSkew =  function(w,sigma,M3)
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{
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   pm2 = m2(w,sigma)
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   pm3 = m3(w,M3)
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   skew = pm3 / pm2^(3/2);
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   return( skew )
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}
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PortKurt =  function(w,sigma,M4)
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{
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   pm2 = m2(w,sigma)
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   pm4 = m4(w,M4)
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   kurt = pm4 / pm2^(2) ;
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   return( kurt )
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}
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PortMVaR =  function(alpha,w,mu,sigma,M3,M4,precision=4)
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{
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   z = qnorm(alpha)
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   location = t(w)%*%mu
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   pm2 = m2(w,sigma)
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   dpm2 = as.vector( derm2(w,sigma) )
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   pm3 = m3(w,M3)
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   dpm3 = as.vector( derm3(w,M3) )
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   pm4 = m4(w,M4)
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   dpm4 = as.vector( derm4(w,M4) )
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   skew = pm3 / pm2^(3/2);
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   exkurt = pm4 / pm2^(2) - 3;
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   derskew = ( 2*(pm2^(3/2))*dpm3 - 3*pm3*sqrt(pm2)*dpm2 )/(2*pm2^3)
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   derexkurt = ( (pm2)*dpm4 - 2*pm4*dpm2    )/(pm2^3)
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   h = z + (1/6)*(z^2 -1)*skew 
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   h = h + (1/24)*(z^3 - 3*z)*exkurt - (1/36)*(2*z^3 - 5*z)*skew^2; 
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   MVaR = - location - h*sqrt(pm2)
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   derGausVaR = - as.vector(mu)- qnorm(alpha)*(0.5*as.vector(dpm2))/sqrt(pm2);
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   derMVaR = derGausVaR + (0.5*dpm2/sqrt(pm2))*( -(1/6)*(z^2 -1)*skew  - (1/24)*(z^3 - 3*z)*exkurt + (1/36)*(2*z^3 - 5*z)*skew^2 )
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   derMVaR = derMVaR + sqrt(pm2)*( -(1/6)*(z^2 -1)*derskew  - (1/24)*(z^3 - 3*z)*derexkurt + (1/36)*(2*z^3 - 5*z)*2*skew*derskew  )
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   contrib = as.vector(w)*as.vector(derMVaR)
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   return(list(  round( MVaR , precision) , round( contrib , precision ), round (contrib/MVaR , precision ) ) ) 
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}
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resPortMVaR =  function(alpha,w,mu,sigma,resSigma,M3,M4,precision=4)
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{
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   z = qnorm(alpha)
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   location = t(w)%*%mu
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   pm2 = m2(w,sigma)
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   respm2 = m2(w,resSigma)
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   dpm2 = as.vector( derm2(w,sigma) )
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   drespm2 = as.vector( derm2(w,resSigma) )
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   pm3 = m3(w,M3)
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   dpm3 = as.vector( derm3(w,M3) )
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   pm4 = m4(w,M4)
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   dpm4 = as.vector( derm4(w,M4) )
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   skew = pm3 / respm2^(3/2);
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   exkurt = pm4 / respm2^(2) - 3;
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   derskew = ( 2*(respm2^(3/2))*dpm3 - 3*pm3*sqrt(respm2)*drespm2 )/(2*respm2^3)
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   derexkurt = ( (respm2)*dpm4 - 2*pm4*drespm2    )/(respm2^3)
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   h = z + (1/6)*(z^2 -1)*skew 
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   h = h + (1/24)*(z^3 - 3*z)*exkurt - (1/36)*(2*z^3 - 5*z)*skew^2; 
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   MVaR = - location - h*sqrt(pm2)
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   derGausVaR = - as.vector(mu)- qnorm(alpha)*(0.5*as.vector(dpm2))/sqrt(pm2);
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   derMVaR = derGausVaR + (0.5*dpm2/sqrt(pm2))*( -(1/6)*(z^2 -1)*skew  - (1/24)*(z^3 - 3*z)*exkurt + (1/36)*(2*z^3 - 5*z)*skew^2 )
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   derMVaR = derMVaR + sqrt(pm2)*( -(1/6)*(z^2 -1)*derskew  - (1/24)*(z^3 - 3*z)*derexkurt + (1/36)*(2*z^3 - 5*z)*2*skew*derskew  )
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   contrib = as.vector(w)*as.vector(derMVaR)
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   return(list(  round( MVaR , precision) , round( contrib , precision ), round (contrib/MVaR , precision ) ) ) 
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}
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derIpower = function(power,h)
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{
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   fullprod = 1;
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   if( (power%%2)==0 ) #even number: number mod is zero
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   {
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      pstar = power/2;
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      for(j in c(1:pstar))
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      {
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         fullprod = fullprod*(2*j)
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      }
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      I = -fullprod*h*dnorm(h);
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      for(i in c(1:pstar) )
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      { 
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         prod = 1;
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         for(j in c(1:i) )
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         {
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            prod = prod*(2*j)
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         }
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         I = I + (fullprod/prod)*(h^(2*i-1))*(2*i-h^2)*dnorm(h)
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      }
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   }else{
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      pstar = (power-1)/2
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      for(j in c(0:pstar) )
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      {
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         fullprod = fullprod*( (2*j)+1 )
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      }
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      I = -fullprod*dnorm(h);
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      for(i in c(0:pstar) )
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      { 
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         prod = 1;
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         for(j in c(0:i) )
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         {
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            prod = prod*( (2*j) + 1 )
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         }
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         I = I + (fullprod/prod)*(h^(2*i)*(2*i+1-h^2) )*dnorm(h)
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      }
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   }
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   return(I)
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}
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PortMES =  function(alpha,w,mu,sigma,M3,M4,precision=4)
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{
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   z = qnorm(alpha)
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   location = t(w)%*%mu
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   pm2 = m2(w,sigma)
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   dpm2 = as.vector( derm2(w,sigma) )
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   pm3 = m3(w,M3)
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   dpm3 = as.vector( derm3(w,M3) )
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   pm4 = m4(w,M4)
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   dpm4 = as.vector( derm4(w,M4) )
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   skew = pm3 / pm2^(3/2);
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   exkurt = pm4 / pm2^(2) - 3;
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   derskew = ( 2*(pm2^(3/2))*dpm3 - 3*pm3*sqrt(pm2)*dpm2 )/(2*pm2^3)
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   derexkurt = ( (pm2)*dpm4 - 2*pm4*dpm2    )/(pm2^3)
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   h = z + (1/6)*(z^2 -1)*skew 
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   h = h + (1/24)*(z^3 - 3*z)*exkurt - (1/36)*(2*z^3 - 5*z)*skew^2; 
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   derh = (1/6)*(z^2 -1)*derskew + (1/24)*(z^3 - 3*z)*derexkurt - (1/18)*(2*z^3 - 5*z)*skew*derskew
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   E = dnorm(h)
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   E = E + (1/24)*(   Ipower(4,h) - 6*Ipower(2,h) + 3*dnorm(h)   )*exkurt
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   E = E +  (1/6)*(   Ipower(3,h) - 3*Ipower(1,h)   )*skew;
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   E = E + (1/72)*(  Ipower(6,h) -15*Ipower(4,h)+ 45*Ipower(2,h) - 15*dnorm(h) )*(skew^2)
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   E = E/alpha
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   MES = - location + sqrt(pm2)*E
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   derMES = -mu + 0.5*(dpm2/sqrt(pm2))*E
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   derE = (1/24)*(   Ipower(4,h) - 6*Ipower(2,h) + 3*dnorm(h)   )*derexkurt 
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   derE = derE +  (1/6)*(   Ipower(3,h) - 3*Ipower(1,h)   )*derskew
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   derE = derE + (1/36)*(  Ipower(6,h) -15*Ipower(4,h)+ 45*Ipower(2,h) - 15*dnorm(h) )*skew*derskew
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   X = -h*dnorm(h) + (1/24)*(  derIpower(4,h) - 6*derIpower(2,h) -3*h*dnorm(h)  )*exkurt 
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   X = X + (1/6)*( derIpower(3,h) - 3*derIpower(1,h) )*skew 
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   X = X + (1/72)*( derIpower(6,h) - 15*derIpower(4,h) + 45*derIpower(2,h) + 15*h*dnorm(h)  )*skew^2
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   derE = derE+derh*X  # X is a scalar
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   derE = derE/alpha
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   derMES = derMES + sqrt(pm2)*derE
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   contrib = as.vector(w)*as.vector(derMES)
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   return(list(  round( MES , precision ) , round( contrib , precision ), round( contrib/MES, precision )) ) 
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}
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operPortMES =  function(alpha,w,mu,sigma,M3,M4,precision=4)
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{
436
   z = qnorm(alpha)
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   location = t(w)%*%mu
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   pm2 = m2(w,sigma)
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   dpm2 = as.vector( derm2(w,sigma) )
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   pm3 = m3(w,M3)
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   dpm3 = as.vector( derm3(w,M3) )
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   pm4 = m4(w,M4)
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   dpm4 = as.vector( derm4(w,M4) )
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   skew = pm3 / pm2^(3/2);
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   exkurt = pm4 / pm2^(2) - 3;
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448
   derskew = ( 2*(pm2^(3/2))*dpm3 - 3*pm3*sqrt(pm2)*dpm2 )/(2*pm2^3)
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   derexkurt = ( (pm2)*dpm4 - 2*pm4*dpm2    )/(pm2^3)
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   h = z + (1/6)*(z^2 -1)*skew 
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   h = h + (1/24)*(z^3 - 3*z)*exkurt - (1/36)*(2*z^3 - 5*z)*skew^2; 
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   I1 = Ipower(1,h); I2 = Ipower(2,h); I3 = Ipower(3,h); I4 = Ipower(4,h);  I6 = Ipower(6,h); 
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   derh = (1/6)*(z^2 -1)*derskew + (1/24)*(z^3 - 3*z)*derexkurt - (1/18)*(2*z^3 - 5*z)*skew*derskew
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457
   E = dnorm(h)
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   E = E + (1/24)*(   I4 - 6*I2 + 3*dnorm(h)   )*exkurt
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   E = E +  (1/6)*(   I3 - 3*I1   )*skew;
460
   E = E + (1/72)*( I6 -15*I4+ 45*I2 - 15*dnorm(h) )*(skew^2)
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   E = E/alpha
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463
   MES = - location - sqrt(pm2)*min(-E,h)
464

465
   if(-E<=h){
466
      derMES = -mu + 0.5*(dpm2/sqrt(pm2))*E
467
      derE = (1/24)*(   I4 - 6*I2 + 3*dnorm(h)   )*derexkurt 
468
      derE = derE +  (1/6)*(   I3 - 3*I1   )*derskew
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      derE = derE + (1/36)*(  I6 -15*I4 + 45*I2 - 15*dnorm(h) )*skew*derskew
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      X = -h*dnorm(h) + (1/24)*(  derIpower(4,h) - 6*derIpower(2,h) -3*h*dnorm(h)  )*exkurt 
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      X = X + (1/6)*( derIpower(3,h) - 3*derIpower(1,h) )*skew 
472
      X = X + (1/72)*( derIpower(6,h) - 15*derIpower(4,h) + 45*derIpower(2,h) + 15*h*dnorm(h)  )*skew^2
473
      derE = derE+derh*X  # X is a scalar
474
      derE = derE/alpha
475
      derMES = derMES + sqrt(pm2)*derE }else{
476
      derMES = -mu - 0.5*(dpm2/sqrt(pm2))*h - sqrt(pm2)*derh ;  }
477
   contrib = as.vector(w)*as.vector(derMES)
478
   return(list( round( MES, precision) , round( contrib , precision ) , round(contrib/MES,precision) ) ) 
479
}
480

481

482
resoperPortMES =  function(alpha,w,mu,sigma,resSigma,M3,M4,precision=4)
483
{
484
   z = qnorm(alpha)
485
   location = t(w)%*%mu
486
   pm2 = m2(w,sigma)
487
   respm2 = m2(w,resSigma)
488
   dpm2 = as.vector( derm2(w,sigma) )
489
   drespm2 = as.vector( derm2(w,resSigma) )
490
   pm3 = m3(w,M3)
491
   dpm3 = as.vector( derm3(w,M3) )
492
   pm4 = m4(w,M4)
493
   dpm4 = as.vector( derm4(w,M4) )
494

495
   skew = pm3 / respm2^(3/2);
496
   exkurt = pm4 / respm2^(2) - 3;
497

498
   derskew = ( 2*(respm2^(3/2))*dpm3 - 3*pm3*sqrt(respm2)*drespm2 )/(2*respm2^3)
499
   derexkurt = ( (respm2)*dpm4 - 2*pm4*drespm2    )/(respm2^3)
500

501
   h = z + (1/6)*(z^2 -1)*skew 
502
   h = h + (1/24)*(z^3 - 3*z)*exkurt - (1/36)*(2*z^3 - 5*z)*skew^2; 
503
   I1 = Ipower(1,h); I2 = Ipower(2,h); I3 = Ipower(3,h); I4 = Ipower(4,h);  I6 = Ipower(6,h); 
504

505
   derh = (1/6)*(z^2 -1)*derskew + (1/24)*(z^3 - 3*z)*derexkurt - (1/18)*(2*z^3 - 5*z)*skew*derskew
506

507
   E = dnorm(h)
508
   E = E + (1/24)*(   I4 - 6*I2 + 3*dnorm(h)   )*exkurt
509
   E = E +  (1/6)*(   I3 - 3*I1   )*skew;
510
   E = E + (1/72)*( I6 -15*I4+ 45*I2 - 15*dnorm(h) )*(skew^2)
511
   E = E/alpha
512

513
   MES = - location - sqrt(pm2)*min(-E,h)
514

515
   if(-E<=h){
516
      derMES = -mu + 0.5*(dpm2/sqrt(pm2))*E
517
      derE = (1/24)*(   I4 - 6*I2 + 3*dnorm(h)   )*derexkurt 
518
      derE = derE +  (1/6)*(   I3 - 3*I1   )*derskew
519
      derE = derE + (1/36)*(  I6 -15*I4 + 45*I2 - 15*dnorm(h) )*skew*derskew
520
      X = -h*dnorm(h) + (1/24)*(  derIpower(4,h) - 6*derIpower(2,h) -3*h*dnorm(h)  )*exkurt 
521
      X = X + (1/6)*( derIpower(3,h) - 3*derIpower(1,h) )*skew 
522
      X = X + (1/72)*( derIpower(6,h) - 15*derIpower(4,h) + 45*derIpower(2,h) + 15*h*dnorm(h)  )*skew^2
523
      derE = derE+derh*X  # X is a scalar
524
      derE = derE/alpha
525
      derMES = derMES + sqrt(pm2)*derE }else{
526
      derMES = -mu - 0.5*(dpm2/sqrt(pm2))*h - sqrt(pm2)*derh ;  }
527
   contrib = as.vector(w)*as.vector(derMES)
528
   return(list( round( MES, precision) , round( contrib , precision ) , round(contrib/MES,precision) ) ) 
529
}
530

531
realportES = function(data,w,VaR,precision=4)
532
{
533
    T = dim(data)[1]
534
    N = dim(data)[2]
535
    c_exceed = 0;
536
    r_exceed = 0;
537
    realizedcontrib = rep(0,N);
538
    for(t in c(1:T) )
539
    {
540
       rt = as.vector(data[t,])
541
       rp = sum(w*rt)
542
       if(rp<=-VaR){
543
          c_exceed = c_exceed + 1;
544
          r_exceed = r_exceed + rp;
545
          for( i in c(1:N) ){
546
             realizedcontrib[i] =realizedcontrib[i] + w[i]*rt[i] }
547
       }
548
    }
549
    realizedcontrib=as.numeric(realizedcontrib)/r_exceed ; 
550
    return( list(round(-r_exceed/c_exceed,precision),c_exceed,round(realizedcontrib,precision)) )
551
}
552

553
realportVaR = function(data,w,alpha,precision=4)
554
{
555
    portret = c();
556
    T = dim(data)[1]
557
    N = dim(data)[2]
558
    for( t in c(1:T) ){
559
       portret = c(portret,sum(w*as.numeric(data[t,])))
560
    }
561
    VaR = sort(portret)[floor(alpha*T)]
562
    return(-VaR)
563
}
564
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