#librarys for data
library(readxl)
library(dplyr)
library(doParallel)

#reading inner credit portfolio data from excel
inner_credport_data<-read_excel("C:/MYTABLE.xlsx")
#saving inner credit portfolio data as new t1 table -> View t1 and remowe inner data
#subset() function allows me to drop values of 100% provisions that don't affect on stress sum
t1<-subset(inner_credport_data, inner_credport_data$prov_calc_p<100);rm(inner_credport_data)

###########################variables to load###############################
dt<-t1$dt[1]              #stress test date
id<-unique(t1$idclient)   #list of unique id
nid<-NROW(id)             #unique id count
n<-500000                  #number of iterations of MC

n_iter<-as.numeric(n)            #experiment num & seed parameter
prov_calcstress<-as.numeric(n)   #all stress (not applicable in current scenario)
stress_result<-as.numeric(n)     #stress resulting vector
###########################################################################$

system.time({                   #measuring system.time
foreach(i=1:n) %do% {     #cycle NOT parallel
set.seed(i);print(i)             #setting seed number for random generators (replicable)

t2<-data.frame(id=id,r1=runif(nid),r2=runif(nid),r3=runif(nid))   #t2 table - generates random var's
t3<-left_join(t1,t2,by=c("idclient"="id"))                        #t3 table - main with random var's & all data
t31<-subset(t3,t3$r1<0.25)                                        #t31 table contains only clients in stress
t31$prov_calcstress_p<-if_else(is.na(t31$pos_ind)==F, #
                              #правила для ПОС
                              if_else(t31$fl_ul=="ЮЛ", 
                                      #правила для ЮЛ
                                      if_else(t31$prov_calc_p==0.5,1.5,
                                      if_else(t31$prov_calc_p==1,3,
                                      if_else(t31$prov_calc_p==1.5,10,
                                      if_else(t31$prov_calc_p==3,20,
                                      if_else(t31$prov_calc_p==10,35,
                                      if_else(t31$prov_calc_p==20,50,
                                      if_else(t31$prov_calc_p==35,75,
                                      if_else(t31$prov_calc_p==50,75,t31$prov_calc_p)))))))),
                                      #правила для ФЛ
                                      if_else(t31$prov_calc_p>=0 & t31$prov_calc_p<1,1.5,
                                      if_else(t31$prov_calc_p==1,3,
                                      if_else(t31$prov_calc_p==1.5,10,
                                      if_else(t31$prov_calc_p==2,6,
                                      if_else(t31$prov_calc_p==3,if_else(t31$backet=="0 Без просрочки",8,20),       
                                      if_else(t31$prov_calc_p>3 & t31$prov_calc_p<10,20,
                                      if_else(t31$prov_calc_p>=10 & t31$prov_calc_p<20,35,
                                      if_else(t31$prov_calc_p>=20 & t31$prov_calc_p<35,50,
                                      if_else(t31$prov_calc_p>=35 & t31$prov_calc_p<75,75,
                                      if_else(t31$prov_calc_p>=75 & t31$prov_calc_p<=100,100,t31$prov_calc_p))))))))))
                              ), 100)
###########################################условия заданы
#набор данных стресс-тестирования
#номер эксперимента
n_iter[i]<-i 
#сумма всего стрессового резерва в деньгах
#prov_calcstress[i]<-sum(t3$ead*t3$prov_calcstress_p)/100
#сумма стресс-сценария (суммируются 25% клиентов из стресса, остальные берутся как были)
stress_result[i]<-(sum(t31$ead*t31$prov_calcstress_p)-(sum(t31$ead*t31$prov_calc_p)))/100
}   #foreach()
})  #system.time()