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Приложение
Код для нахождения скошенности риск-нейтрального
распределения в статистическом пакете R:
#Задание переменных
skew=skews=skewl=numeric()
for(i in 1:nrow(close)){
##Скошенность ближайшего опциона
mat=exec-index(close)[i]
mat[mat<0]=NA[-active[[i]]]=NA=as.numeric(rrus[i])=as.numeric(rusa[i])=which(mat==min(mat,na.rm=T))=as.numeric(exec[matt[1]]-index(close)[i])/365=days=which(colnames(closef)==cont[matt][1])=as.numeric(as.numeric(closef[i,f])*exp(-rrus[i]*(days)))=as.numeric(as.numeric(closef[i,f]))=intersect(intersect(which(type=="C"),which(strike>spot)),matt)=intersect(intersect(which(type=="P"),which(strike<spot)),matt)=sort(as.numeric(close[i,calls]),decreasing=T)=sort(as.numeric(close[i,puts]))_c=strike[calls][match(c,as.numeric(close[i,calls]))]_p=strike[puts][match(p,as.numeric(close[i,puts]))]=spot+p-str_p*exp(-days*r)(all(length(calls)>1,length(puts)>1)){(!(is.na(spot))){=extract.ew.density(initial.values = c(NA, NA, NA), r, 0, days, spot, c(p,c),
##Скошенность опциона с экспирацией больше двух месяцев
mat=exec-index(close)[i][mat<60]=NA[-active[[i]]]=NA=as.numeric(rrus[i])=as.numeric(rusa[i])=which(mat==min(mat,na.rm=T))=as.numeric(exec[matt[1]]-index(close)[i])/365=which(colnames(closef)==cont[matt][1])=as.numeric(as.numeric(closef[i,f])*exp(-rrus[i]*(days)))=as.numeric(as.numeric(closef[i,f]))=intersect(intersect(which(type=="C"),which(strike>spot)),matt)=intersect(intersect(which(type=="P"),which(strike<spot)),matt)(all(length(calls)>1,length(puts)>1)){=sort(as.numeric(close[i,calls]),decreasing=T)=sort(as.numeric(close[i,puts]))_c=strike[calls][match(c,as.numeric(close[i,calls]))]_p=strike[puts][match(p,as.numeric(close[i,puts]))]=spot+p-str_p*exp(-days*r)(all(length(calls)>1,length(puts)>1)){(!(is.na(spot))){=extract.ew.density(initial.values = c(NA, NA, NA), r, 0, days, spot, c(p,c),
c(str_p,str_c))[i]=z$skew}}}
##Линейная экстраполяция скошенности
skew[i]=skews[i]*(days-0.17)/(days-days1)+skewl[i]*(0.17-days1)/(days-
days1)}