R/CalcAddon.R
In sa-ccr/SACCR: SA Counterparty Credit Risk under CRR2
Defines functions
CalcAddon
Documented in
CalcAddon
#' Calculates the amount of the addon for each heding/nettting set
#'
#' @title Calculates the Addon amount
#' @param trades_tree A tree structure with the input trades
#' @param MF (Optional) The Maturity Factor based on the collateral agreement
#' @param simplified (optional) When TRUE, the add-ons will be calculated as per the simplified SA-CCR
#' @param OEM (optional) When TRUE, the add-ons will be calculated as per the Original Exposure Method
#' @return The aggregate amount of the addon summed up for all the asset classes
#' @export
#' @author Tasos Grivas <tasos@@openriskcalculator.com>
#' @references Regulation (EU) 2019/876 of the European Parliament and of the Council of 20 May 2019
#' http://data.europa.eu/eli/reg/2019/876/oj
#'
CalcAddon <- function(trades_tree, MF, simplified = FALSE, OEM = FALSE) {
## function which will calculate the Add-On for all the trade classes
superv <- LoadSupervisoryData()
if(simplified) superv[,'Correlation']=1
asset_classes = trades_tree$`Asset Classes`$children
asset_class_names = names(asset_classes)
trades_tree$addon = 0
# going through each trade class
for (i in 1:length(asset_class_names))
{
#picking up the trades belonging to this specific trade class
asset_class_node = asset_classes[[asset_class_names[i]]]
asset_class_node$addon = 0
if(asset_class_names[i]=='FX')
{
ccypairs <- asset_class_node$`Currency Pairs`$children
# for the FX case the Hedging sets will be created based on the ccy pair
ccypairs_names <- names(ccypairs)
ccypairs_addon <- array(data<-0,dim<-length(ccypairs))
# going through all the ccy pairs found
for (j in 1:length(ccypairs_names))
{
ccypairs_trades <- ccypairs[[ccypairs_names[j]]]$Trades$children
ccypairs[[ccypairs_names[j]]]$add_on = 0
ccypairs_trades_names = names(ccypairs_trades)
# for each of the trade calculate the Adjusted Notional and their contribution to the addon of the hedging set
for (l in 1:length(ccypairs_trades_names))
{
ccypairs_trade = ccypairs_trades[[ccypairs_trades_names[l]]]
ccypairs_trade$exposure_details = SingleTradeAddon(ccypairs_trade$trade,MF)
# aggregating the add-on contribution for a specific hedging set
if(OEM)
{ ccypairs[[ccypairs_names[j]]]$add_on <- ccypairs[[ccypairs_names[j]]]$add_on + ccypairs_trade$trade_details$Notional*ccypairs_trade$trade_details$Ei
}else
{ ccypairs[[ccypairs_names[j]]]$add_on <- ccypairs[[ccypairs_names[j]]]$add_on + ccypairs_trade$exposure_details$effective_notional }
}
if(OEM)
{ supervisory_factor = 0.04
}else
{
factor_mult = CalculateFactorMult(ccypairs_names[j])
# getting the supervisory factor
supervisory_factor <- factor_mult*superv$Supervisory_factor[superv$Asset_Class==ccypairs_trade$trade$TradeGroup]
}
ccypairs[[ccypairs_names[j]]]$supervisory_factor = supervisory_factor
ccypairs_addon[j] = supervisory_factor*ccypairs[[ccypairs_names[j]]]$add_on
ccypairs[[ccypairs_names[j]]]$add_on = abs(ccypairs_addon[j])
}
asset_class_node$addon = sum(abs(ccypairs_addon))
trades_tree$addon = trades_tree$addon + asset_class_node$addon
}else if(asset_class_names[i]=='OtherExposure')
{
riskfactors <- asset_class_node$`Other SubClasses`$children
# for the FX case the Hedging sets will be created based on the ccy pair
riskfactors_names <- names(riskfactors)
riskfactors_addon <- array(data<-0,dim<-length(riskfactors))
# going through all the ccy pairs found
for (j in 1:length(riskfactors_names))
{
riskfactors_trades <- riskfactors[[riskfactors_names[j]]]$Trades$children
riskfactors[[riskfactors_names[j]]]$add_on = 0
riskfactors_trades_names = names(riskfactors_trades)
# for each of the trade calculate the Adjusted Notional and their contribution to the addon of the hedging set
for (l in 1:length(riskfactors_trades_names))
{
riskfactors_trade = riskfactors_trades[[riskfactors_trades_names[l]]]
riskfactors_trade$exposure_details = SingleTradeAddon(riskfactors_trade$trade,MF)
# aggregating the add-on contribution for a specific hedging set
riskfactors[[riskfactors_names[j]]]$add_on <- riskfactors[[riskfactors_names[j]]]$add_on + riskfactors_trade$exposure_details$effective_notional
}
factor_mult = CalculateFactorMult(riskfactors_names[j])
# getting the supervisory factor
supervisory_factor <- 0.08*factor_mult
riskfactors[[riskfactors_names[j]]]$supervisory_factor = supervisory_factor
riskfactors_addon[j] = supervisory_factor*riskfactors[[riskfactors_names[j]]]$add_on
riskfactors[[riskfactors_names[j]]]$add_on = abs(riskfactors_addon[j])
}
asset_class_node$addon = sum(abs(riskfactors_addon))
trades_tree$addon = trades_tree$addon + asset_class_node$addon
}else if(asset_class_names[i]=='IRD')
{
# picking up the currencies found in the IRD trades which will be the first-level grouping applied
currencies <- asset_class_node$Currencies$children
currencies_names <- names(currencies)
for (j in 1:length(currencies_names))
{
currencies_buckets <- currencies[[currencies_names[j]]]$Timebuckets$children
currencies_buckets_names = names(currencies_buckets)
for (k in 1:length(currencies_buckets_names))
{
currencies_buckets[[currencies_buckets_names[k]]]$effective_notional = 0
#picking up all the trades belonging to a specific timebucket
timebuckets_trades <- currencies_buckets[[currencies_buckets_names[k]]]$Trades$children
timebuckets_trades_names = names(timebuckets_trades)
if(OEM)
{ supervisory_factor = 0.005
}else
{
factor_mult = CalculateFactorMult(currencies_names[j])
supervisory_factor <- factor_mult*superv$Supervisory_factor[superv$Asset_Class==timebuckets_trades[[1]]$trade$TradeGroup&superv$SubClass==timebuckets_trades[[1]]$trade$SubClass]
}
currencies[[currencies_names[j]]]$supervisory_factor = supervisory_factor
exotic_identifier = ''
digital_eff_notional = 0
for (l in 1:length(timebuckets_trades_names))
{
timebuckets_trade = timebuckets_trades[[timebuckets_trades_names[l]]]
timebuckets_trade$exposure_details = SingleTradeAddon(timebuckets_trade$trade,MF)
if(OEM)
{ currencies_buckets[[currencies_buckets_names[k]]]$effective_notional = currencies_buckets[[currencies_buckets_names[k]]]$effective_notional + timebuckets_trade$trade_details$Notional*timebuckets_trade$trade_details$Ei
}else
{ currencies_buckets[[currencies_buckets_names[k]]]$effective_notional = currencies_buckets[[currencies_buckets_names[k]]]$effective_notional + timebuckets_trade$exposure_details$effective_notional }
if(!is.null(timebuckets_trade$trade$Exotic_Type)&length(timebuckets_trade$trade$Exotic_Type)!=0)
{
if(exotic_identifier!='')
{ exotic_identifier = timebuckets_trade$trade$Exotic_Type
digital_eff_notional = digital_eff_notional + timebuckets_trade$exposure_details$effective_notional
}else if(exotic_identifier==timebuckets_trade$trade$Exotic_Type)
{
digital_eff_notional = digital_eff_notional + timebuckets_trade$exposure_details$effective_notional
excess_notional = abs(digital_eff_notional) - abs(timebuckets_trade$trade_details$Notional/supervisory_factor)
currencies_buckets[[currencies_buckets_names[k]]]$effective_notional = currencies_buckets[[currencies_buckets_names[k]]]$effective_notional - max(excess_notional,0)
exotic_identifier = ''
digital_eff_notional = 0
}
}
}
# aggregating the add-on timebuckets recognizing correlation between each time bucket
if(simplified)
currencies[[currencies_names[j]]]$effective_notional <- sum(abs(unlist(lapply(currencies_buckets,function(x) x$effective_notional))),na.rm = TRUE)
else
currencies[[currencies_names[j]]]$effective_notional = (sum(currencies_buckets[["1"]]$effective_notional^2,currencies_buckets[["2"]]$effective_notional^2,currencies_buckets[["3"]]$effective_notional^2,1.4*currencies_buckets[["2"]]$effective_notional*currencies_buckets[["3"]]$effective_notional,1.4*currencies_buckets[["2"]]$effective_notional*currencies_buckets[["1"]]$effective_notional,0.6*currencies_buckets[["2"]]$effective_notional*currencies_buckets[["1"]]$effective_notional,na.rm = TRUE))^0.5
currencies[[currencies_names[j]]]$addon <- supervisory_factor*currencies[[currencies_names[j]]]$effective_notional
}
# adding up the addon of each currency after multiplying with the supervisory factor
asset_class_node$addon <- asset_class_node$addon + currencies[[currencies_names[j]]]$addon
}
trades_tree$addon = trades_tree$addon + asset_class_node$addon
}else if(asset_class_names[i]=='Credit')
{
asset_class_node$addon = 0
refEntities <- asset_class_node$`Reference Entities`$children
# for the FX case the Hedging sets will be created based on the ccy pair
refEntities_names <- names(refEntities)
refEntities_addon <- array(data<-0,dim<-length(refEntities))
# for the Credit case the Hedging sets will be created based on the reference entity
supervisory_corel <- array(data<-0,dim<-length(refEntities_names))
for (j in 1:length(refEntities_names))
{
refEntities_trades <- refEntities[[refEntities_names[j]]]$Trades$children
refEntities[[refEntities_names[j]]]$add_on = 0
refEntities_trades_names = names(refEntities_trades)
for (k in 1:length(refEntities_trades_names))
{
refEntities_trade = refEntities_trades[[refEntities_trades_names[k]]]
refEntities_trade$exposure_details = SingleTradeAddon(refEntities_trade$trade,MF)
if(OEM)
{ refEntities[[refEntities_names[j]]]$add_on <- refEntities[[refEntities_names[j]]]$add_on + refEntities_trade$trade_details$Notional*refEntities_trade$trade_details$Ei
}else
{ refEntities[[refEntities_names[j]]]$add_on <- refEntities[[refEntities_names[j]]]$add_on + refEntities_trade$exposure_details$effective_notional }
}
AssetClass<-ifelse(class(refEntities_trade$trade)=='CDS','CreditSingle','CreditIndex')
if(OEM)
{ supervisory_factor = 0.06
}else
{ factor_mult = CalculateFactorMult(refEntities_names[j])
supervisory_factor <- factor_mult*superv$Supervisory_factor[superv$Asset_Class==AssetClass&superv$SubClass==refEntities_trade$trade$SubClass]
}
refEntities[[refEntities_names[j]]]$add_on <- refEntities[[refEntities_names[j]]]$add_on*supervisory_factor
supervisory_corel[j] <- superv$Correlation[superv$Asset_Class==AssetClass&superv$SubClass==refEntities_trade$trade$SubClass]
refEntities_addon[j] = refEntities[[refEntities_names[j]]]$add_on
refEntities[[refEntities_names[j]]]$supervisory_corel = supervisory_corel[j]
refEntities[[refEntities_names[j]]]$supervisory_factor = supervisory_factor
}
systematic_component <- (sum(refEntities_addon*supervisory_corel))^2
idiosynchratic_component <- sum((rep(1,length(refEntities))-supervisory_corel^2)*refEntities_addon^2)
asset_class_node$systematic_component = systematic_component
asset_class_node$idiosynchratic_component = idiosynchratic_component
asset_class_node$addon <- sqrt(systematic_component + idiosynchratic_component)
trades_tree$addon = trades_tree$addon + asset_class_node$addon
}else if(asset_class_names[i]=='Commodity')
{
AssetClass <-'Commodity'
HedgingSets <- asset_class_node$`Hedging Sets`$children
HedgingSets_names <- names(HedgingSets)
# for the commodities case the Hedging sets will be created based on the commodity sector on a first
# level (energy,metals etc) and on a second level based on the actual commodities (oil, silver etc)
HedgingSets_addon = 0
for (j in 1:length(HedgingSets_names))
{
com_types <- HedgingSets[[HedgingSets_names[j]]]$`Commodities Types`$children
com_types_names = names(com_types)
com_types_addon = 0
com_types_addon_sq = 0
for (k in 1:length(com_types_names))
{
com_types[[com_types_names[k]]]$addon = 0
com_types[[com_types_names[k]]]$effective_notional = 0
com_types_trades <- com_types[[com_types_names[k]]]$Trades$children
com_types_trades_names <- names(com_types_trades)
for (l in 1:length(com_types_trades_names))
{
com_types_trade = com_types_trades[[com_types_trades_names[l]]]
com_types_trade$exposure_details = SingleTradeAddon(com_types_trade$trade,MF)
if(OEM)
{ com_types[[com_types_names[k]]]$addon <- com_types[[com_types_names[k]]]$addon + com_types_trade$exposure_details$effective_notional + com_types_trade$trade_details$Notional*com_types_trade$trade_details$Ei
}else
{ com_types[[com_types_names[k]]]$addon <- abs(com_types[[com_types_names[k]]]$addon + com_types_trade$exposure_details$effective_notional)}
com_types[[com_types_names[k]]]$effective_notional = com_types[[com_types_names[k]]]$effective_notional + com_types_trade$exposure_details$effective_notional
}
if(OEM)
factor_mult = 1
else
factor_mult = CalculateFactorMult(HedgingSets_names[j])
supervisory_factor <- factor_mult*ifelse(com_types_trade$trade$commodity_type=='Electricity',0.4,0.18)
com_types[[com_types_names[k]]]$addon <- com_types[[com_types_names[k]]]$addon*supervisory_factor
com_types[[com_types_names[k]]]$supervisory_factor = supervisory_factor
com_types_addon = com_types_addon + com_types[[com_types_names[k]]]$addon
com_types_addon_sq = com_types_addon_sq + com_types[[com_types_names[k]]]$addon^2
#com_types[[com_types_names[k]]]$com_types_addon = com_types_addon
}
supervisory_corel <- 0.4
HedgingSets[[HedgingSets_names[j]]]$addon <- sqrt((com_types_addon*supervisory_corel)^2 + (1-supervisory_corel^2)*com_types_addon_sq)
HedgingSets[[HedgingSets_names[j]]]$supervisory_corel = supervisory_corel
HedgingSets_addon = HedgingSets_addon + HedgingSets[[HedgingSets_names[j]]]$addon
}
asset_class_node$addon <- asset_class_node$addon + HedgingSets_addon
trades_tree$addon = trades_tree$addon + asset_class_node$addon
}else if(asset_class_names[i]=='EQ')
{
asset_class_node$addon = 0
refEntities <- asset_class_node$`Reference Entities`$children
# for the FX case the Hedging sets will be created based on the ccy pair
refEntities_names <- names(refEntities)
refEntities_addon <- array(data<-0,dim<-length(refEntities))
# for the Equity case the Hedging sets will be created based on the reference entity
supervisory_corel <- array(data<-0,dim<-length(refEntities_names))
for (j in 1:length(refEntities_names))
{
refEntities_trades <- refEntities[[refEntities_names[j]]]$Trades$children
refEntities[[refEntities_names[j]]]$add_on = 0
refEntities_trades_names = names(refEntities_trades)
for (k in 1:length(refEntities_trades_names))
{
refEntities_trade = refEntities_trades[[refEntities_trades_names[k]]]
refEntities_trade$exposure_details = SingleTradeAddon(refEntities_trade$trade,MF)
if(OEM)
{ refEntities[[refEntities_names[j]]]$add_on <- refEntities[[refEntities_names[j]]]$add_on + refEntities_trade$exposure_details$effective_notional
}else
{ refEntities[[refEntities_names[j]]]$add_on <- refEntities[[refEntities_names[j]]]$add_on + refEntities_trade$exposure_details$effective_notional }
}
AssetClass<-asset_class_names[i]
if(OEM)
{ supervisory_factor = 0.32
}else
{ factor_mult = CalculateFactorMult(refEntities_names[j])
supervisory_factor <- factor_mult*superv$Supervisory_factor[superv$Asset_Class==AssetClass&superv$SubClass==refEntities_trade$trade$SubClass]}
refEntities[[refEntities_names[j]]]$add_on <- refEntities[[refEntities_names[j]]]$add_on*supervisory_factor
supervisory_corel[j] <- superv$Correlation[superv$Asset_Class==AssetClass&superv$SubClass==refEntities_trade$trade$SubClass]
refEntities_addon[j] = refEntities[[refEntities_names[j]]]$add_on
refEntities[[refEntities_names[j]]]$supervisory_corel = supervisory_corel[j]
refEntities[[refEntities_names[j]]]$supervisory_factor = supervisory_factor
}
systematic_component <- (sum(refEntities_addon*supervisory_corel))^2
idiosynchratic_component <- sum((rep(1,length(refEntities))-supervisory_corel^2)*refEntities_addon^2)
asset_class_node$addon <- sqrt(systematic_component + idiosynchratic_component)
asset_class_node$systematic_component = systematic_component
asset_class_node$idiosynchratic_component = idiosynchratic_component
trades_tree$addon = trades_tree$addon + asset_class_node$addon
}
}
sapply(trades_tree$leaves, function(x) x$trade = NULL)
if(!missing(MF))
trades_tree$maturity_factor = MF
return(trades_tree)
}
sa-ccr/SACCR documentation built on July 9, 2021, 10:18 p.m.
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Defines functions CalcAddon
Documented in CalcAddon
#' Calculates the amount of the addon for each heding/nettting set
#'
#' @title Calculates the Addon amount
#' @param trades_tree A tree structure with the input trades
#' @param MF (Optional) The Maturity Factor based on the collateral agreement
#' @param simplified (optional) When TRUE, the add-ons will be calculated as per the simplified SA-CCR
#' @param OEM (optional) When TRUE, the add-ons will be calculated as per the Original Exposure Method
#' @return The aggregate amount of the addon summed up for all the asset classes
#' @export
#' @author Tasos Grivas <tasos@@openriskcalculator.com>
#' @references Regulation (EU) 2019/876 of the European Parliament and of the Council of 20 May 2019
#' http://data.europa.eu/eli/reg/2019/876/oj
#'
CalcAddon <- function(trades_tree, MF, simplified = FALSE, OEM = FALSE) {
## function which will calculate the Add-On for all the trade classes
superv <- LoadSupervisoryData()
if(simplified) superv[,'Correlation']=1
asset_classes = trades_tree$`Asset Classes`$children
asset_class_names = names(asset_classes)
trades_tree$addon = 0
# going through each trade class
for (i in 1:length(asset_class_names))
{
#picking up the trades belonging to this specific trade class
asset_class_node = asset_classes[[asset_class_names[i]]]
asset_class_node$addon = 0
if(asset_class_names[i]=='FX')
{
ccypairs <- asset_class_node$`Currency Pairs`$children
# for the FX case the Hedging sets will be created based on the ccy pair
ccypairs_names <- names(ccypairs)
ccypairs_addon <- array(data<-0,dim<-length(ccypairs))
# going through all the ccy pairs found
for (j in 1:length(ccypairs_names))
{
ccypairs_trades <- ccypairs[[ccypairs_names[j]]]$Trades$children
ccypairs[[ccypairs_names[j]]]$add_on = 0
ccypairs_trades_names = names(ccypairs_trades)
# for each of the trade calculate the Adjusted Notional and their contribution to the addon of the hedging set
for (l in 1:length(ccypairs_trades_names))
{
ccypairs_trade = ccypairs_trades[[ccypairs_trades_names[l]]]
ccypairs_trade$exposure_details = SingleTradeAddon(ccypairs_trade$trade,MF)
# aggregating the add-on contribution for a specific hedging set
if(OEM)
{ ccypairs[[ccypairs_names[j]]]$add_on <- ccypairs[[ccypairs_names[j]]]$add_on + ccypairs_trade$trade_details$Notional*ccypairs_trade$trade_details$Ei
}else
{ ccypairs[[ccypairs_names[j]]]$add_on <- ccypairs[[ccypairs_names[j]]]$add_on + ccypairs_trade$exposure_details$effective_notional }
}
if(OEM)
{ supervisory_factor = 0.04
}else
{
factor_mult = CalculateFactorMult(ccypairs_names[j])
# getting the supervisory factor
supervisory_factor <- factor_mult*superv$Supervisory_factor[superv$Asset_Class==ccypairs_trade$trade$TradeGroup]
}
ccypairs[[ccypairs_names[j]]]$supervisory_factor = supervisory_factor
ccypairs_addon[j] = supervisory_factor*ccypairs[[ccypairs_names[j]]]$add_on
ccypairs[[ccypairs_names[j]]]$add_on = abs(ccypairs_addon[j])
}
asset_class_node$addon = sum(abs(ccypairs_addon))
trades_tree$addon = trades_tree$addon + asset_class_node$addon
}else if(asset_class_names[i]=='OtherExposure')
{
riskfactors <- asset_class_node$`Other SubClasses`$children
# for the FX case the Hedging sets will be created based on the ccy pair
riskfactors_names <- names(riskfactors)
riskfactors_addon <- array(data<-0,dim<-length(riskfactors))
# going through all the ccy pairs found
for (j in 1:length(riskfactors_names))
{
riskfactors_trades <- riskfactors[[riskfactors_names[j]]]$Trades$children
riskfactors[[riskfactors_names[j]]]$add_on = 0
riskfactors_trades_names = names(riskfactors_trades)
# for each of the trade calculate the Adjusted Notional and their contribution to the addon of the hedging set
for (l in 1:length(riskfactors_trades_names))
{
riskfactors_trade = riskfactors_trades[[riskfactors_trades_names[l]]]
riskfactors_trade$exposure_details = SingleTradeAddon(riskfactors_trade$trade,MF)
# aggregating the add-on contribution for a specific hedging set
riskfactors[[riskfactors_names[j]]]$add_on <- riskfactors[[riskfactors_names[j]]]$add_on + riskfactors_trade$exposure_details$effective_notional
}
factor_mult = CalculateFactorMult(riskfactors_names[j])
# getting the supervisory factor
supervisory_factor <- 0.08*factor_mult
riskfactors[[riskfactors_names[j]]]$supervisory_factor = supervisory_factor
riskfactors_addon[j] = supervisory_factor*riskfactors[[riskfactors_names[j]]]$add_on
riskfactors[[riskfactors_names[j]]]$add_on = abs(riskfactors_addon[j])
}
asset_class_node$addon = sum(abs(riskfactors_addon))
trades_tree$addon = trades_tree$addon + asset_class_node$addon
}else if(asset_class_names[i]=='IRD')
{
# picking up the currencies found in the IRD trades which will be the first-level grouping applied
currencies <- asset_class_node$Currencies$children
currencies_names <- names(currencies)
for (j in 1:length(currencies_names))
{
currencies_buckets <- currencies[[currencies_names[j]]]$Timebuckets$children
currencies_buckets_names = names(currencies_buckets)
for (k in 1:length(currencies_buckets_names))
{
currencies_buckets[[currencies_buckets_names[k]]]$effective_notional = 0
#picking up all the trades belonging to a specific timebucket
timebuckets_trades <- currencies_buckets[[currencies_buckets_names[k]]]$Trades$children
timebuckets_trades_names = names(timebuckets_trades)
if(OEM)
{ supervisory_factor = 0.005
}else
{
factor_mult = CalculateFactorMult(currencies_names[j])
supervisory_factor <- factor_mult*superv$Supervisory_factor[superv$Asset_Class==timebuckets_trades[[1]]$trade$TradeGroup&superv$SubClass==timebuckets_trades[[1]]$trade$SubClass]
}
currencies[[currencies_names[j]]]$supervisory_factor = supervisory_factor
exotic_identifier = ''
digital_eff_notional = 0
for (l in 1:length(timebuckets_trades_names))
{
timebuckets_trade = timebuckets_trades[[timebuckets_trades_names[l]]]
timebuckets_trade$exposure_details = SingleTradeAddon(timebuckets_trade$trade,MF)
if(OEM)
{ currencies_buckets[[currencies_buckets_names[k]]]$effective_notional = currencies_buckets[[currencies_buckets_names[k]]]$effective_notional + timebuckets_trade$trade_details$Notional*timebuckets_trade$trade_details$Ei
}else
{ currencies_buckets[[currencies_buckets_names[k]]]$effective_notional = currencies_buckets[[currencies_buckets_names[k]]]$effective_notional + timebuckets_trade$exposure_details$effective_notional }
if(!is.null(timebuckets_trade$trade$Exotic_Type)&length(timebuckets_trade$trade$Exotic_Type)!=0)
{
if(exotic_identifier!='')
{ exotic_identifier = timebuckets_trade$trade$Exotic_Type
digital_eff_notional = digital_eff_notional + timebuckets_trade$exposure_details$effective_notional
}else if(exotic_identifier==timebuckets_trade$trade$Exotic_Type)
{
digital_eff_notional = digital_eff_notional + timebuckets_trade$exposure_details$effective_notional
excess_notional = abs(digital_eff_notional) - abs(timebuckets_trade$trade_details$Notional/supervisory_factor)
currencies_buckets[[currencies_buckets_names[k]]]$effective_notional = currencies_buckets[[currencies_buckets_names[k]]]$effective_notional - max(excess_notional,0)
exotic_identifier = ''
digital_eff_notional = 0
}
}
}
# aggregating the add-on timebuckets recognizing correlation between each time bucket
if(simplified)
currencies[[currencies_names[j]]]$effective_notional <- sum(abs(unlist(lapply(currencies_buckets,function(x) x$effective_notional))),na.rm = TRUE)
else
currencies[[currencies_names[j]]]$effective_notional = (sum(currencies_buckets[["1"]]$effective_notional^2,currencies_buckets[["2"]]$effective_notional^2,currencies_buckets[["3"]]$effective_notional^2,1.4*currencies_buckets[["2"]]$effective_notional*currencies_buckets[["3"]]$effective_notional,1.4*currencies_buckets[["2"]]$effective_notional*currencies_buckets[["1"]]$effective_notional,0.6*currencies_buckets[["2"]]$effective_notional*currencies_buckets[["1"]]$effective_notional,na.rm = TRUE))^0.5
currencies[[currencies_names[j]]]$addon <- supervisory_factor*currencies[[currencies_names[j]]]$effective_notional
}
# adding up the addon of each currency after multiplying with the supervisory factor
asset_class_node$addon <- asset_class_node$addon + currencies[[currencies_names[j]]]$addon
}
trades_tree$addon = trades_tree$addon + asset_class_node$addon
}else if(asset_class_names[i]=='Credit')
{
asset_class_node$addon = 0
refEntities <- asset_class_node$`Reference Entities`$children
# for the FX case the Hedging sets will be created based on the ccy pair
refEntities_names <- names(refEntities)
refEntities_addon <- array(data<-0,dim<-length(refEntities))
# for the Credit case the Hedging sets will be created based on the reference entity
supervisory_corel <- array(data<-0,dim<-length(refEntities_names))
for (j in 1:length(refEntities_names))
{
refEntities_trades <- refEntities[[refEntities_names[j]]]$Trades$children
refEntities[[refEntities_names[j]]]$add_on = 0
refEntities_trades_names = names(refEntities_trades)
for (k in 1:length(refEntities_trades_names))
{
refEntities_trade = refEntities_trades[[refEntities_trades_names[k]]]
refEntities_trade$exposure_details = SingleTradeAddon(refEntities_trade$trade,MF)
if(OEM)
{ refEntities[[refEntities_names[j]]]$add_on <- refEntities[[refEntities_names[j]]]$add_on + refEntities_trade$trade_details$Notional*refEntities_trade$trade_details$Ei
}else
{ refEntities[[refEntities_names[j]]]$add_on <- refEntities[[refEntities_names[j]]]$add_on + refEntities_trade$exposure_details$effective_notional }
}
AssetClass<-ifelse(class(refEntities_trade$trade)=='CDS','CreditSingle','CreditIndex')
if(OEM)
{ supervisory_factor = 0.06
}else
{ factor_mult = CalculateFactorMult(refEntities_names[j])
supervisory_factor <- factor_mult*superv$Supervisory_factor[superv$Asset_Class==AssetClass&superv$SubClass==refEntities_trade$trade$SubClass]
}
refEntities[[refEntities_names[j]]]$add_on <- refEntities[[refEntities_names[j]]]$add_on*supervisory_factor
supervisory_corel[j] <- superv$Correlation[superv$Asset_Class==AssetClass&superv$SubClass==refEntities_trade$trade$SubClass]
refEntities_addon[j] = refEntities[[refEntities_names[j]]]$add_on
refEntities[[refEntities_names[j]]]$supervisory_corel = supervisory_corel[j]
refEntities[[refEntities_names[j]]]$supervisory_factor = supervisory_factor
}
systematic_component <- (sum(refEntities_addon*supervisory_corel))^2
idiosynchratic_component <- sum((rep(1,length(refEntities))-supervisory_corel^2)*refEntities_addon^2)
asset_class_node$systematic_component = systematic_component
asset_class_node$idiosynchratic_component = idiosynchratic_component
asset_class_node$addon <- sqrt(systematic_component + idiosynchratic_component)
trades_tree$addon = trades_tree$addon + asset_class_node$addon
}else if(asset_class_names[i]=='Commodity')
{
AssetClass <-'Commodity'
HedgingSets <- asset_class_node$`Hedging Sets`$children
HedgingSets_names <- names(HedgingSets)
# for the commodities case the Hedging sets will be created based on the commodity sector on a first
# level (energy,metals etc) and on a second level based on the actual commodities (oil, silver etc)
HedgingSets_addon = 0
for (j in 1:length(HedgingSets_names))
{
com_types <- HedgingSets[[HedgingSets_names[j]]]$`Commodities Types`$children
com_types_names = names(com_types)
com_types_addon = 0
com_types_addon_sq = 0
for (k in 1:length(com_types_names))
{
com_types[[com_types_names[k]]]$addon = 0
com_types[[com_types_names[k]]]$effective_notional = 0
com_types_trades <- com_types[[com_types_names[k]]]$Trades$children
com_types_trades_names <- names(com_types_trades)
for (l in 1:length(com_types_trades_names))
{
com_types_trade = com_types_trades[[com_types_trades_names[l]]]
com_types_trade$exposure_details = SingleTradeAddon(com_types_trade$trade,MF)
if(OEM)
{ com_types[[com_types_names[k]]]$addon <- com_types[[com_types_names[k]]]$addon + com_types_trade$exposure_details$effective_notional + com_types_trade$trade_details$Notional*com_types_trade$trade_details$Ei
}else
{ com_types[[com_types_names[k]]]$addon <- abs(com_types[[com_types_names[k]]]$addon + com_types_trade$exposure_details$effective_notional)}
com_types[[com_types_names[k]]]$effective_notional = com_types[[com_types_names[k]]]$effective_notional + com_types_trade$exposure_details$effective_notional
}
if(OEM)
factor_mult = 1
else
factor_mult = CalculateFactorMult(HedgingSets_names[j])
supervisory_factor <- factor_mult*ifelse(com_types_trade$trade$commodity_type=='Electricity',0.4,0.18)
com_types[[com_types_names[k]]]$addon <- com_types[[com_types_names[k]]]$addon*supervisory_factor
com_types[[com_types_names[k]]]$supervisory_factor = supervisory_factor
com_types_addon = com_types_addon + com_types[[com_types_names[k]]]$addon
com_types_addon_sq = com_types_addon_sq + com_types[[com_types_names[k]]]$addon^2
#com_types[[com_types_names[k]]]$com_types_addon = com_types_addon
}
supervisory_corel <- 0.4
HedgingSets[[HedgingSets_names[j]]]$addon <- sqrt((com_types_addon*supervisory_corel)^2 + (1-supervisory_corel^2)*com_types_addon_sq)
HedgingSets[[HedgingSets_names[j]]]$supervisory_corel = supervisory_corel
HedgingSets_addon = HedgingSets_addon + HedgingSets[[HedgingSets_names[j]]]$addon
}
asset_class_node$addon <- asset_class_node$addon + HedgingSets_addon
trades_tree$addon = trades_tree$addon + asset_class_node$addon
}else if(asset_class_names[i]=='EQ')
{
asset_class_node$addon = 0
refEntities <- asset_class_node$`Reference Entities`$children
# for the FX case the Hedging sets will be created based on the ccy pair
refEntities_names <- names(refEntities)
refEntities_addon <- array(data<-0,dim<-length(refEntities))
# for the Equity case the Hedging sets will be created based on the reference entity
supervisory_corel <- array(data<-0,dim<-length(refEntities_names))
for (j in 1:length(refEntities_names))
{
refEntities_trades <- refEntities[[refEntities_names[j]]]$Trades$children
refEntities[[refEntities_names[j]]]$add_on = 0
refEntities_trades_names = names(refEntities_trades)
for (k in 1:length(refEntities_trades_names))
{
refEntities_trade = refEntities_trades[[refEntities_trades_names[k]]]
refEntities_trade$exposure_details = SingleTradeAddon(refEntities_trade$trade,MF)
if(OEM)
{ refEntities[[refEntities_names[j]]]$add_on <- refEntities[[refEntities_names[j]]]$add_on + refEntities_trade$exposure_details$effective_notional
}else
{ refEntities[[refEntities_names[j]]]$add_on <- refEntities[[refEntities_names[j]]]$add_on + refEntities_trade$exposure_details$effective_notional }
}
AssetClass<-asset_class_names[i]
if(OEM)
{ supervisory_factor = 0.32
}else
{ factor_mult = CalculateFactorMult(refEntities_names[j])
supervisory_factor <- factor_mult*superv$Supervisory_factor[superv$Asset_Class==AssetClass&superv$SubClass==refEntities_trade$trade$SubClass]}
refEntities[[refEntities_names[j]]]$add_on <- refEntities[[refEntities_names[j]]]$add_on*supervisory_factor
supervisory_corel[j] <- superv$Correlation[superv$Asset_Class==AssetClass&superv$SubClass==refEntities_trade$trade$SubClass]
refEntities_addon[j] = refEntities[[refEntities_names[j]]]$add_on
refEntities[[refEntities_names[j]]]$supervisory_corel = supervisory_corel[j]
refEntities[[refEntities_names[j]]]$supervisory_factor = supervisory_factor
}
systematic_component <- (sum(refEntities_addon*supervisory_corel))^2
idiosynchratic_component <- sum((rep(1,length(refEntities))-supervisory_corel^2)*refEntities_addon^2)
asset_class_node$addon <- sqrt(systematic_component + idiosynchratic_component)
asset_class_node$systematic_component = systematic_component
asset_class_node$idiosynchratic_component = idiosynchratic_component
trades_tree$addon = trades_tree$addon + asset_class_node$addon
}
}
sapply(trades_tree$leaves, function(x) x$trade = NULL)
if(!missing(MF))
trades_tree$maturity_factor = MF
return(trades_tree)
}
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