R/PrivateFund.R
In bplloyd/CorePE: What the package does (short line)
#' @include calc_drawdownRate.R
#' @include calc_distributionRate.R
#' @include get_privateHoldings.R
#' @include get_privateCommitments.R
#' @include get_privateCashFlows.R
#' @include get_privateValuations.R
#' @include calc_privatePerformance.R
#' @include cull_data.R
#' @include calc_PME.R
#' @include captureErrors.R
#' @include aggregatePrivates.R
setOldClass(c("xts"))
#----------------------PrivateFund class definition---------------------------------------------------------
setClass("PrivateFund",
representation = list(Name = "character",
Stats = "list",
CashFlows = "ANY",
FMV = "ANY",
Commitments = "ANY",
PeriodData = "ANY",
Holdings = "data.frame",
PME_Benchmark = "ANY",
UnderlyingVintages = "list",
UnderlyingStrategies = "list",
UnderlyingFunds = "list",
InitialCommitment = "numeric",
TotalCommitment = "numeric",
Vintage = "numeric",
Strategy = "character",
Active = "integer",
ID = "numeric",
Freq = "character",
Multiplier = "numeric",
ErrorList = "list"
))
#----------------------PrivateFund init function---------------------------------------------------------
setMethod("initialize",
"PrivateFund",
function(.Object,
name = NA_character_,
id = NA_integer_,
strategy=NA_character_,
vintage=NA_integer_,
initialCommitment = NA_real_,
totalCommitment = NA_real_,
commitments = NULL,
cashFlows=NULL,
fmv = NULL,
periodData = NULL,
holdings = NULL,
pme_bm = NULL,
underlyingVintages = list(),
underlyingStrategies = list(),
underlyingFunds = list(),
freq = "d",
dataFreq = "m",
multiplier = 1e+06,
active = NA_integer_,
loadVintages = F,
loadStrategies = F,
loadFunds = F
){
i = 1
errorListName = paste0("errorList_", i)
while(exists(errorListName, envir = globalenv())){
i = i + 1
errorListName = paste0("errorList_", i)
}
assign(x = errorListName, value = list(), envir = globalenv())
if(is.na(id)){
.Object@Vintage = vintage
.Object@Strategy = strategy
.Object@ID = id
.Object@Active = active
if(is.na(name)){
if(is.na(vintage) & is.na(strategy))
name = "Core"
else if(!is.na(vintage) & is.na(strategy))
name = paste0("Core - ", vintage, " Vintage")
else if(is.na(vintage) & !is.na(strategy))
name = paste0("Core - ", strategy)
else
name = paste0("Core - ", vintage, " ", strategy)
}
if(!is.na(active)){
if(active == 1){
name = paste0(name, " (Active Funds Only")
}
if(active == 0){
name = paste0(name, " (Inactive Funds Only")
}
}
} else {
.Object@ID = id
#holdings = get_privateHoldings(id = id, strategy = strategy, vintage = vintage, active = active)
holdings = captureErrors(func = get_privateHoldings,
captureList = errorListName,
default = NULL,
id = id,
strategy = strategy,
vintage = vintage,
active = active)
.Object@Vintage = as.integer(holdings$Vintage)
.Object@Strategy = as.character(holdings$Strategy)
.Object@Active = as.integer(holdings$Active)
.Object@InitialCommitment = as.numeric(holdings$Initial_Commitment_USD)/multiplier
if(is.na(name))
name = as.character(holdings$Holding_Name[1])
}
if(is.null(holdings))
{
#holdings = get_privateHoldings(id = id, strategy = strategy, vintage = vintage, active = active)
holdings = captureErrors(func = get_privateHoldings,
captureList = errorListName,
default = NULL,
id = id,
strategy = strategy,
vintage = vintage,
active = active)
}
if(is.null(commitments))
{
#commitments = get_privateCommitments(id = id, strategy = strategy, vintage = vintage, active = active, freq = freq, multiplier = multiplier)
commitments = captureErrors(func = get_privateCommitments,
captureList = errorListName,
default = NULL,
id = id,
strategy = strategy,
vintage = vintage,
active = active,
freq = freq,
multiplier = multiplier)
}
if(is.na(totalCommitment)){
if(!is.null(commitments))
totalCommitment = sum(commitments, na.rm = T)
else
totalCommitment = NA_real_
}
if(is.na(initialCommitment)){
if((!is.null(holdings)) & (nrow(holdings) > 0))
initialCommitment = sum(holdings$Initial_Commitment_USD, na.rm = T)/multiplier
else
initialCommitment = NA_real_
}
if(is.null(cashFlows)){
#cashFlows = get_privateCashFlows(id = id, strategy = strategy, vintage = vintage, active = active, freq = freq, distIsPositive = T, multiplier = multiplier)
cashFlows = captureErrors(func = get_privateCashFlows,
captureList = errorListName,
default = NULL,
id = id,
strategy = strategy,
vintage = vintage,
active = active,
freq = freq,
multiplier = multiplier,
distIsPositive = T)
}
if(is.null(fmv)){
#fmv = get_privateValuations(id = id, strategy = strategy, vintage = vintage, active = active, freq = freq, multiplier = multiplier)
fmv = captureErrors(func = get_privateValuations,
captureList = errorListName,
default = NULL,
id = id,
strategy = strategy,
vintage = vintage,
active = active,
freq = freq,
multiplier = multiplier)
}
if(is.null(fmv)){
fmv_end = 0
} else {
fmv_end = fmv[nrow(fmv),]
}
if(is.null(pme_bm)){
pme_bm = as.data.frame(loadIndices("SPTR"))
}
# pme = calc_PME(cashFlows[, "CashFlows_Net"], fmv = fmv, bm = publicBM)
# commit = sum(commitments)
# called_net = sum(cashFlows[, "Calls_Total_Net"])
# called_gross = sum(cashFlows[, "Calls_Total_Gross"])
# dists = sum(cashFlows[, "Distributions_Total"])
# fmv_end = fmv[nrow(fmv)]
#
# perf = try(calc_privatePerformance(cashFlows, fmv))
# pme_perf = try(calc_privatePerformance(cashFlows, pme))
#
# cf_stats = data.frame(Net = c(commit, called_net)
# )
#
#
# colnames(cf_stats)[2:3] = c("Called_w_Fees", "Called_wo_Fees")
#
# stats = list(Performance = try(calc_privatePerformance(cashFlows, fmv)),
# PME_Performance = try(calc_privatePerformance(cashFlows, pme)),
# CashFlows = try(cf_stats))
if(!is.na(totalCommitment)){
if(is.null(cashFlows)){
called_net = 0
called_gross = 0
dists = 0
pme = NULL
pme_perf = NULL
perf = NULL
} else {
#pme = calc_PME(cashFlows[, "CashFlows_Net"], fmv = fmv, bm = publicBM)
pme = captureErrors(func = calc_PME,
captureList = errorListName,
default = NULL,
cf = cashFlows,
fmv = fmv,
bm = pme_bm)
#pme_perf = try(calc_privatePerformance(cashFlows, pme))
pme_perf = captureErrors(func = calc_privatePerformance,
captureList = errorListName,
default = NULL,
cf = cashFlows,
fmv = pme)
#perf = try(calc_privatePerformance(cashFlows, fmv))
perf = captureErrors(func = calc_privatePerformance,
captureList = errorListName,
default = NULL,
cf = cashFlows,
fmv = fmv)
called_net = sum(cashFlows[, "Calls_Total_Net"])
called_gross = sum(cashFlows[, "Calls_Total_Gross"])
dists = sum(cashFlows[, "Distributions_Total"])
}
cf_stats = data.frame(Committed = totalCommitment,
Called_w_Fees = called_net,
Called_wo_Fees = called_gross,
Distributed = dists,
CashFlows_Net = dists - called_net,
CashFlows_Gross = dists - called_gross,
FMV = fmv_end)
colnames(cf_stats)[2:3] = c("Called_w_Fees", "Called_wo_Fees")
stats = list(Performance = perf,
PME_Performance = pme_perf,
CashFlows = cf_stats)
} else {
stats = list(Performance = NULL,
PME_Performance = NULL,
CashFlows = NULL)
}
.Object@Commitments = commitments
.Object@TotalCommitment = totalCommitment
.Object@InitialCommitment = initialCommitment
.Object@Holdings = holdings
.Object@CashFlows = cashFlows
.Object@FMV = fmv
.Object@Freq = freq
.Object@Multiplier = multiplier
.Object@Name = name
.Object@UnderlyingFunds = underlyingFunds
.Object@UnderlyingVintages = underlyingVintages
.Object@UnderlyingStrategies = underlyingStrategies
.Object@Stats = stats
.Object@PME_Benchmark = pme_bm
#.Object@PeriodData = cull_Data(.Object, dataFreq)
.Object@PeriodData = captureErrors(func = cull_data,
captureList = errorListName,
default = NULL,
pef = .Object,
freq = dataFreq)
if(loadVintages){
.Object@UnderlyingVintages = loadUnderlying(.Object, "v", errorListName)
}
if(loadStrategies){
# underlyingStrategies = list(Aggregated = list(), Underlying = loadUnderlying(coreFund, mode = "s"))
.Object@UnderlyingStrategies = loadUnderlying(.Object, mode = "s", errorListName)
}
if(loadFunds){
#underlyingFunds = loadUnderlying(.Object, mode = "f")
.Object@UnderlyingFunds = loadUnderlying(.Object, mode = "f", errorListName)
}
.Object@ErrorList = globalenv()[[errorListName]]
rm(list = c(errorListName), envir = globalenv())
.Object
})
#----------------------PrivateFund get_data_ggplot definition---------------------------------------------------------
# setGeneric(name = "get_data_ggplot", function(pef, cols, melt_cols = cols, cumulative_cols = NA_character_, scaledBy =NA_character_, underlying = NA_character_, date_filter=NA_character_) standardGeneric("get_data_ggplot"))
# setMethod(f = "get_data_ggplot",
# c("PrivateFund", "character", "character", "character", "character", "character", "character" ),
# function(pef, cols, melt_cols = cols, cumulative_cols = NA_character_, scaledBy = NA_character_, underlying = NA_character_, date_filter=NA_character_) {
# melt_cols = cols
# if(is.na(underlying)) {
# if(is.na(date_filter)) {
# xts_data = pef@PeriodData[ , cols]
# } else {
# xts_data = pef@PeriodData[date_filter, cols]
# }
#
# if(!is.na(cumulative_cols)) {
# xts_data[, cumulative_cols] = cumsum(zoo::na.fill(xts_data[, cumulative_cols], 0))
# }
#
# if(!is.na(scaledBy)) {
# xts_data = xts_data/abs(sum(na.omit(pef@PeriodData[, scaledBy])))
# }
#
#
# df = data.frame(date = zoo::index(xts_data), xts_data)
# df_melt = data.table::melt(data = df,
# #id.vars = names(df)[which(!(names(df) %in% melt_cols))],
# measure.vars = melt_cols,
# variable.name = "cashflow")
# } else if(tolower(substr(underlying,1,1)) == "v"){
# df_list = lapply(pef@UnderlyingVintages$Underlying,
# function(v) get_data_ggplot(v, cols, melt_cols=cols, cumulative_cols, scaledBy, underlying = NA_character_,date_filter))
# names(df_list) = names(pef@UnderlyingVintages$Underlying)
#
# for(i in 1:length(df_list)) {
# v = names(df_list)[[i]]
# if(i == 1) {
# df_melt = cbind(df_list[[i]], vintage = rep(v, nrow(df_list[[i]])))
# } else {
# df_melt = rbind(df_melt, cbind(df_list[[i]], vintage = rep(v, nrow(df_list[[i]]))))
# }
# }
# }
# return(df_melt)
# }
# )
#----------------------PrivateFund constructor definition---------------------------------------------------------
PrivateFund = function(name = NA_character_,
id = NA_integer_,
strategy=NA_character_,
vintage=NA_integer_,
initialCommitment = NA_real_,
totalCommitment = NA_real_,
commitments = NULL,
cashFlows=NULL,
fmv = NULL,
periodData = NULL,
holdings = NULL,
pme_bm = NULL,
underlyingFunds = list(),
underlyingVintages = list(),
underlyingStrategies = list(),
freq = "d",
dataFreq = "m",
multiplier = 1e+06,
active = NA_integer_,
loadVintages = F,
loadStrategies = F,
loadFunds = F)
{
new("PrivateFund",
name = name,
id = id,
strategy = strategy,
vintage = vintage,
initialCommitment = initialCommitment,
totalCommitment = totalCommitment,
commitments = commitments,
cashFlows = cashFlows,
fmv = fmv,
periodData = periodData,
holdings = holdings,
pme_bm = pme_bm,
underlyingFunds = underlyingFunds,
underlyingStrategies = underlyingStrategies,
underlyingVintages = underlyingVintages,
freq = freq,
dataFreq = dataFreq,
multiplier = multiplier,
active = as.integer(active),
loadVintages = loadVintages,
loadStrategies = loadStrategies,
loadFunds = loadFunds
)
}
#----------------------PrivateFund privateIRR definition---------------------------------------------------------
# setMethod(f = "privateIRR",
# c("PrivateFund", "Period"),
# function(pef, per)
# {
# cf_net = pef@CashFlows$CashFlows_Net
# cf_gross = pef@CashFlows$CashFlows_Gross
# fmv = pef@FMV
#
# perf_start = max(end(cf_net), end(cf_gross), end(fmv)) %m-% per
# cf_net = cf_net[which(zoo::index(cf_net) >= perf_start)]
# cf_gross = cf_gross[which(zoo::index(cf_gross) >= perf_start)]
# fmv = fmv[which(zoo::index(fmv)>=perf_start)]
#
# cf_net = rbind(-fmv[1], cf_net, fmv[nrow(fmv)])
# cf_gross = rbind(-fmv[1], cf_gross, fmv[nrow(fmv)])
#
#
# return(UnderlyingFunds)
# }
# )
#----------------------PrivateFund loadUnderlying definition---------------------------------------------------------
setGeneric(name = "loadUnderlying", function(pef, mode, errorListName) standardGeneric("loadUnderlying"))
setMethod(f = "loadUnderlying",
c("PrivateFund", "character", "character"),
function(pef, mode, errorListName){
mode = tolower(strtrim(mode, 1))
freq = tolower(pef@Freq)
active = pef@Active
pme_bm = pef@PME_Benchmark
if(mode == "f"){
ids = pef@Holdings$Holding_ID
names(ids) = as.character(pef@Holdings$Holding_Name)
#underlying = lapply(ids, function(id)try(PrivateFund(id = id, freq = freq)))
underlying = lapply(ids,
function(id) captureErrors(func = PrivateFund,
captureList = errorListName,
default = NULL,
id = id,
freq = freq,
pme_bm = pme_bm))
} else if (mode == "v"){
vintages = sort(unique(pef@Holdings$Vintage))
strategy = pef@Strategy
names(vintages) = vintages
#underlying = lapply(vintages, function(v)try(PrivateFund(vintage = v, strategy = strategy, freq = freq)))
underlying = lapply(vintages,
function(v) captureErrors(func = PrivateFund,
captureList = errorListName,
default = NULL,
strategy = strategy,
vintage = v,
freq = freq,
active = active,
pme_bm = pme_bm))
# cf_agg = matrix(unlist(lapply(underlying,
# function(v){if(class(v) == "PrivateFund"){v@Stats$CashFlows}else{rep(0, 5)}})), ncol = 5, byrow = T)
# row.names(cf_agg) = names(underlying)
# colnames(cf_agg) = names(underlying[[1]]@Stats$CashFlows)
# if(any(as.numeric(row.names(cf_agg)[2:nrow(cf_agg)]) - as.numeric(row.names(cf_agg))[1:(nrow(cf_agg)-1)] > 1)){
# allYears = as.character(as.numeric(row.names(cf_agg)[1]):as.numeric(row.names(cf_agg)[nrow(cf_agg)]))
# missingYears = allYears[which(!(allYears %in% row.names(cf_agg)))]
# for(y in as.numeric(missingYears)){
# yearInsert = matrix(rep(0, 5), ncol = 5)
# cf_agg_temp = cf_agg[which(as.numeric(row.names(cf_agg)) > y),]
# if(!is.matrix(cf_agg_temp)){
# cf_agg_temp = matrix(cf_agg_temp, ncol = 5)
# row.names(cf_agg_temp) = row.names(cf_agg)[nrow(cf_agg)]
# }
# cf_agg = rbind(cf_agg[which(as.numeric(row.names(cf_agg)) < y),], yearInsert)
# row.names(cf_agg)[nrow(cf_agg)] = y
# cf_agg = rbind(cf_agg, cf_agg_temp)
# }
# }
#
# cf_agg_total = apply(cf_agg, 2, sum, na.rm = T)
#
# cf_agg = rbind(cf_agg, TOTAL = cf_agg_total)
cf_agg = captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying,
stats = "CashFlows")
perf_net_agg = captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying,
stats = "Performance",
net=T)
perf_gross_agg = captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying,
stats = "Performance",
net=F)
pme_net_agg = captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying,
stats = "PME_Performance",
net=T)
pme_gross_agg = captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying,
stats = "PME_Performance",
net=F)
underlying = list(Underlying = underlying,
Aggregated = list(CashFlows = cf_agg,
Performance = list(Net = perf_net_agg,
Gross = perf_gross_agg),
PME = list(Net = pme_net_agg,
Gross = pme_gross_agg)))
} else if (mode == "s"){
vintages = sort(unique(pef@Holdings$Vintage))
names(vintages) = vintages
strategies = sort(unique(pef@Holdings$Strategy))
names(strategies) = strategies
# underlying = lapply(strategies,
# function(s) lapply(vintages,
# function(v) try(PrivateFund(vintage = v, strategy = s, freq = freq))))
underlying = lapply(strategies,
function(s) lapply(vintages,
function(v) captureErrors(func = PrivateFund,
captureList = errorListName,
default = NULL,
strategy = s,
vintage = v,
freq = freq,
active = active,
pme_bm = pme_bm)))
cf_agg = lapply(strategies,
function(s) captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying[[s]],
stats = "CashFlows"))
perf_net_agg = lapply(strategies,
function(s) captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying[[s]],
stats = "Performance",
net = T))
perf_gross_agg = lapply(strategies,
function(s) captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying[[s]],
stats = "Performance",
net = F))
pme_net_agg = lapply(strategies,
function(s) captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying[[s]],
stats = "PME_Performance",
net = T))
pme_gross_agg = lapply(strategies,
function(s) captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying[[s]],
stats = "PME_Performance",
net = F))
underlying = list(Underlying = underlying,
Aggregated = list(CashFlows = cf_agg,
Performance = list(Net = perf_net_agg,
Gross = perf_gross_agg),
PME = list(Net = pme_net_agg,
Gross = pme_gross_agg)))
}
return(underlying)
}
)
#----------------------PrivateFund compareHoldings definition---------------------------------------------------------
setGeneric(name = "compareHoldings", function(pef) standardGeneric("compareHoldings"))
setMethod(f = "compareHoldings",
c("PrivateFund"),
function(pef)
{
ids = pef@Holdings$Holding_ID
if(length(ids)>1)
{
if(length(pef@UnderlyingFunds) == 0){
names(ids) = as.character(pef@Holdings$Holding_Name)
freq = tolower(pef@Freq)
UnderlyingFunds = lapply(ids, function(id)new("PrivateFund", ID = id, Freq = freq))
}
else{
UnderlyingFunds = pef@UnderlyingFunds
}
comparisons = vector(mode = "list", length = 2)
names(comparisons) = c("Performance", "CashFlows")
comparisons$Performance = vector(mode = "list", length = ncol(pef@Stats$Performance))
names(comparisons$Performance) = colnames(pef@Stats$Performance)
comparisons$CashFlows = vector(mode = "list", length = ncol(pef@Stats$CashFlows))
names(comparisons$CashFlows) = colnames(pef@Stats$CashFlows)
for(comp in names(comparisons$Performance))
{
comparisons$Performance[[comp]] = vector(mode = "list", length = 2)
names(comparisons$Performance[[comp]]) = c("Total", "Underlying")
comparisons$Performance[[comp]]$Total = pef@Stats$Performance["NetFees", comp]
for(fund in UnderlyingFunds)
{
df = data.frame(fund@Stats$Performance["NetFees", comp], row.names = fund@Name)
colnames(df) = comp
if(is.null(comparisons$Performance[[comp]]$Underlying))
comparisons$Performance[[comp]]$Underlying = df
else
comparisons$Performance[[comp]]$Underlying = rbind(comparisons$Performance[[comp]]$Underlying, df)
}
ord = order(comparisons$Performance[[comp]]$Underlying, decreasing = T)
comparisons$Performance[[comp]]$Underlying = data.frame(comparisons$Performance[[comp]]$Underlying[ord, comp],
row.names = row.names(comparisons$Performance[[comp]]$Underlying)[ord])
colnames(comparisons$Performance[[comp]]$Underlying) = comp
}
for(comp in names(comparisons$CashFlows))
{
comparisons$CashFlows[[comp]] = vector(mode = "list", length = 2)
names(comparisons$CashFlows[[comp]]) = c("Total", "Underlying")
comparisons$CashFlows[[comp]]$Total = pef@Stats$CashFlows[, comp]
for(fund in UnderlyingFunds)
{
df = data.frame(fund@Stats$CashFlows[ , comp], row.names = fund@Name)
colnames(df) = comp
if(is.null(comparisons$CashFlows[[comp]]$Underlying))
comparisons$CashFlows[[comp]]$Underlying = df
else
comparisons$CashFlows[[comp]]$Underlying = rbind(comparisons$CashFlows[[comp]]$Underlying, df)
}
ord = order(comparisons$CashFlows[[comp]]$Underlying, decreasing = T)
comparisons$CashFlows[[comp]]$Underlying = data.frame(comparisons$CashFlows[[comp]]$Underlying[ord, comp],
row.names = row.names(comparisons$CashFlows[[comp]]$Underlying)[ord])
colnames(comparisons$CashFlows[[comp]]$Underlying) = comp
}
#
# if(tolower(substr(comparison, 1, 1)) == "i")
# {
# comp = "IRR"
# df = data.frame(IRR = pef@Performance$`2016-12-31`["NetFees", comp], row.names = c("Total"))
#
# }
# else
# {
# comp = "RollingMultiple"
# df = data.frame(IRR = pef@Performance[[1]]["NetFees", comp], row.names = c("Total"))
# }
# for(fund in UnderlyingFunds){
# newdf = data.frame(fund@Performance[[1]]["NetFees", comp], row.names = c(fund@Name))
# colnames(newdf) = comp
# rownames(newdf) = fund@Name
# df = rbind(df, newdf)
# }
return(comparisons)
}
# return(df)
}
)
#----------------------PrivateFund print definition---------------------------------------------------------
setMethod("print",
signature(c(x="PrivateFund")),
function(x)
{
pef = x
#perf = pef@Stats$Performance
# commit = sum(pef@Commitments)
# called_net = sum(pef@CashFlows[, "Calls_Total_Net"])
# called_gross = sum(pef@CashFlows[, "Calls_Total_Gross"])
# dists = sum(pef@CashFlows[, "Distributions_Total"])
# cf_stats = data.frame(Committed = commit,
# Called_Net = called_net,
# Called_Gross = called_gross,
# Distributed = dists)
cat('\nCash Flow Stats-------------------------------------------\n')
#print(cf_stats)
print(pef@Stats$CashFlows)
cat('\n\n')
cat('Performance Stats-------------------------------------------\n')
#print(perf)
print(pef@Stats$Performance)
})
#----------------------PrivateFund modelDistributions definition---------------------------------------------------------
# setMethod(f = "modelDistributions",
# c("PrivateFund"),
#
# function(pef)
# {
# require(yuima)
# dist_rate = data[, "DistributionRate"]
# fmv = data[zoo::index(dist_rate), "FMV"]
# dist_start = zoo::index(fmv[fmv!=0])[2]
# dist_rate = zoo::na.fill(dist_rate[zoo::index(dist_rate) >= dist_start], 0)
#
# param.init_shift = list(a = 1.1, b = -2, sigma = 1)
#
# low.par = list(a = 0, b = -1e+09, sigma = 0)
# upp.par = list(a = 1e+09, b = 0, sigma = 100)
# prior <-
# list(
# a=list(measure.type="code",df="dnorm(z,0,1)"),
# b=list(measure.type="code",df="dnorm(z,0,1)"),
# sigma=list(measure.type="code",df="dnorm(z,0,1)")
# )
#
# mod = setModel(drift = "(a + b*x)", diffusion = "sigma*sqrt(x)", solve.variable = "x")
# }
# )
bplloyd/CorePE documentation built on May 30, 2019, 9:41 p.m.
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#' @include calc_drawdownRate.R
#' @include calc_distributionRate.R
#' @include get_privateHoldings.R
#' @include get_privateCommitments.R
#' @include get_privateCashFlows.R
#' @include get_privateValuations.R
#' @include calc_privatePerformance.R
#' @include cull_data.R
#' @include calc_PME.R
#' @include captureErrors.R
#' @include aggregatePrivates.R
setOldClass(c("xts"))
#----------------------PrivateFund class definition---------------------------------------------------------
setClass("PrivateFund",
representation = list(Name = "character",
Stats = "list",
CashFlows = "ANY",
FMV = "ANY",
Commitments = "ANY",
PeriodData = "ANY",
Holdings = "data.frame",
PME_Benchmark = "ANY",
UnderlyingVintages = "list",
UnderlyingStrategies = "list",
UnderlyingFunds = "list",
InitialCommitment = "numeric",
TotalCommitment = "numeric",
Vintage = "numeric",
Strategy = "character",
Active = "integer",
ID = "numeric",
Freq = "character",
Multiplier = "numeric",
ErrorList = "list"
))
#----------------------PrivateFund init function---------------------------------------------------------
setMethod("initialize",
"PrivateFund",
function(.Object,
name = NA_character_,
id = NA_integer_,
strategy=NA_character_,
vintage=NA_integer_,
initialCommitment = NA_real_,
totalCommitment = NA_real_,
commitments = NULL,
cashFlows=NULL,
fmv = NULL,
periodData = NULL,
holdings = NULL,
pme_bm = NULL,
underlyingVintages = list(),
underlyingStrategies = list(),
underlyingFunds = list(),
freq = "d",
dataFreq = "m",
multiplier = 1e+06,
active = NA_integer_,
loadVintages = F,
loadStrategies = F,
loadFunds = F
){
i = 1
errorListName = paste0("errorList_", i)
while(exists(errorListName, envir = globalenv())){
i = i + 1
errorListName = paste0("errorList_", i)
}
assign(x = errorListName, value = list(), envir = globalenv())
if(is.na(id)){
.Object@Vintage = vintage
.Object@Strategy = strategy
.Object@ID = id
.Object@Active = active
if(is.na(name)){
if(is.na(vintage) & is.na(strategy))
name = "Core"
else if(!is.na(vintage) & is.na(strategy))
name = paste0("Core - ", vintage, " Vintage")
else if(is.na(vintage) & !is.na(strategy))
name = paste0("Core - ", strategy)
else
name = paste0("Core - ", vintage, " ", strategy)
}
if(!is.na(active)){
if(active == 1){
name = paste0(name, " (Active Funds Only")
}
if(active == 0){
name = paste0(name, " (Inactive Funds Only")
}
}
} else {
.Object@ID = id
#holdings = get_privateHoldings(id = id, strategy = strategy, vintage = vintage, active = active)
holdings = captureErrors(func = get_privateHoldings,
captureList = errorListName,
default = NULL,
id = id,
strategy = strategy,
vintage = vintage,
active = active)
.Object@Vintage = as.integer(holdings$Vintage)
.Object@Strategy = as.character(holdings$Strategy)
.Object@Active = as.integer(holdings$Active)
.Object@InitialCommitment = as.numeric(holdings$Initial_Commitment_USD)/multiplier
if(is.na(name))
name = as.character(holdings$Holding_Name[1])
}
if(is.null(holdings))
{
#holdings = get_privateHoldings(id = id, strategy = strategy, vintage = vintage, active = active)
holdings = captureErrors(func = get_privateHoldings,
captureList = errorListName,
default = NULL,
id = id,
strategy = strategy,
vintage = vintage,
active = active)
}
if(is.null(commitments))
{
#commitments = get_privateCommitments(id = id, strategy = strategy, vintage = vintage, active = active, freq = freq, multiplier = multiplier)
commitments = captureErrors(func = get_privateCommitments,
captureList = errorListName,
default = NULL,
id = id,
strategy = strategy,
vintage = vintage,
active = active,
freq = freq,
multiplier = multiplier)
}
if(is.na(totalCommitment)){
if(!is.null(commitments))
totalCommitment = sum(commitments, na.rm = T)
else
totalCommitment = NA_real_
}
if(is.na(initialCommitment)){
if((!is.null(holdings)) & (nrow(holdings) > 0))
initialCommitment = sum(holdings$Initial_Commitment_USD, na.rm = T)/multiplier
else
initialCommitment = NA_real_
}
if(is.null(cashFlows)){
#cashFlows = get_privateCashFlows(id = id, strategy = strategy, vintage = vintage, active = active, freq = freq, distIsPositive = T, multiplier = multiplier)
cashFlows = captureErrors(func = get_privateCashFlows,
captureList = errorListName,
default = NULL,
id = id,
strategy = strategy,
vintage = vintage,
active = active,
freq = freq,
multiplier = multiplier,
distIsPositive = T)
}
if(is.null(fmv)){
#fmv = get_privateValuations(id = id, strategy = strategy, vintage = vintage, active = active, freq = freq, multiplier = multiplier)
fmv = captureErrors(func = get_privateValuations,
captureList = errorListName,
default = NULL,
id = id,
strategy = strategy,
vintage = vintage,
active = active,
freq = freq,
multiplier = multiplier)
}
if(is.null(fmv)){
fmv_end = 0
} else {
fmv_end = fmv[nrow(fmv),]
}
if(is.null(pme_bm)){
pme_bm = as.data.frame(loadIndices("SPTR"))
}
# pme = calc_PME(cashFlows[, "CashFlows_Net"], fmv = fmv, bm = publicBM)
# commit = sum(commitments)
# called_net = sum(cashFlows[, "Calls_Total_Net"])
# called_gross = sum(cashFlows[, "Calls_Total_Gross"])
# dists = sum(cashFlows[, "Distributions_Total"])
# fmv_end = fmv[nrow(fmv)]
#
# perf = try(calc_privatePerformance(cashFlows, fmv))
# pme_perf = try(calc_privatePerformance(cashFlows, pme))
#
# cf_stats = data.frame(Net = c(commit, called_net)
# )
#
#
# colnames(cf_stats)[2:3] = c("Called_w_Fees", "Called_wo_Fees")
#
# stats = list(Performance = try(calc_privatePerformance(cashFlows, fmv)),
# PME_Performance = try(calc_privatePerformance(cashFlows, pme)),
# CashFlows = try(cf_stats))
if(!is.na(totalCommitment)){
if(is.null(cashFlows)){
called_net = 0
called_gross = 0
dists = 0
pme = NULL
pme_perf = NULL
perf = NULL
} else {
#pme = calc_PME(cashFlows[, "CashFlows_Net"], fmv = fmv, bm = publicBM)
pme = captureErrors(func = calc_PME,
captureList = errorListName,
default = NULL,
cf = cashFlows,
fmv = fmv,
bm = pme_bm)
#pme_perf = try(calc_privatePerformance(cashFlows, pme))
pme_perf = captureErrors(func = calc_privatePerformance,
captureList = errorListName,
default = NULL,
cf = cashFlows,
fmv = pme)
#perf = try(calc_privatePerformance(cashFlows, fmv))
perf = captureErrors(func = calc_privatePerformance,
captureList = errorListName,
default = NULL,
cf = cashFlows,
fmv = fmv)
called_net = sum(cashFlows[, "Calls_Total_Net"])
called_gross = sum(cashFlows[, "Calls_Total_Gross"])
dists = sum(cashFlows[, "Distributions_Total"])
}
cf_stats = data.frame(Committed = totalCommitment,
Called_w_Fees = called_net,
Called_wo_Fees = called_gross,
Distributed = dists,
CashFlows_Net = dists - called_net,
CashFlows_Gross = dists - called_gross,
FMV = fmv_end)
colnames(cf_stats)[2:3] = c("Called_w_Fees", "Called_wo_Fees")
stats = list(Performance = perf,
PME_Performance = pme_perf,
CashFlows = cf_stats)
} else {
stats = list(Performance = NULL,
PME_Performance = NULL,
CashFlows = NULL)
}
.Object@Commitments = commitments
.Object@TotalCommitment = totalCommitment
.Object@InitialCommitment = initialCommitment
.Object@Holdings = holdings
.Object@CashFlows = cashFlows
.Object@FMV = fmv
.Object@Freq = freq
.Object@Multiplier = multiplier
.Object@Name = name
.Object@UnderlyingFunds = underlyingFunds
.Object@UnderlyingVintages = underlyingVintages
.Object@UnderlyingStrategies = underlyingStrategies
.Object@Stats = stats
.Object@PME_Benchmark = pme_bm
#.Object@PeriodData = cull_Data(.Object, dataFreq)
.Object@PeriodData = captureErrors(func = cull_data,
captureList = errorListName,
default = NULL,
pef = .Object,
freq = dataFreq)
if(loadVintages){
.Object@UnderlyingVintages = loadUnderlying(.Object, "v", errorListName)
}
if(loadStrategies){
# underlyingStrategies = list(Aggregated = list(), Underlying = loadUnderlying(coreFund, mode = "s"))
.Object@UnderlyingStrategies = loadUnderlying(.Object, mode = "s", errorListName)
}
if(loadFunds){
#underlyingFunds = loadUnderlying(.Object, mode = "f")
.Object@UnderlyingFunds = loadUnderlying(.Object, mode = "f", errorListName)
}
.Object@ErrorList = globalenv()[[errorListName]]
rm(list = c(errorListName), envir = globalenv())
.Object
})
#----------------------PrivateFund get_data_ggplot definition---------------------------------------------------------
# setGeneric(name = "get_data_ggplot", function(pef, cols, melt_cols = cols, cumulative_cols = NA_character_, scaledBy =NA_character_, underlying = NA_character_, date_filter=NA_character_) standardGeneric("get_data_ggplot"))
# setMethod(f = "get_data_ggplot",
# c("PrivateFund", "character", "character", "character", "character", "character", "character" ),
# function(pef, cols, melt_cols = cols, cumulative_cols = NA_character_, scaledBy = NA_character_, underlying = NA_character_, date_filter=NA_character_) {
# melt_cols = cols
# if(is.na(underlying)) {
# if(is.na(date_filter)) {
# xts_data = pef@PeriodData[ , cols]
# } else {
# xts_data = pef@PeriodData[date_filter, cols]
# }
#
# if(!is.na(cumulative_cols)) {
# xts_data[, cumulative_cols] = cumsum(zoo::na.fill(xts_data[, cumulative_cols], 0))
# }
#
# if(!is.na(scaledBy)) {
# xts_data = xts_data/abs(sum(na.omit(pef@PeriodData[, scaledBy])))
# }
#
#
# df = data.frame(date = zoo::index(xts_data), xts_data)
# df_melt = data.table::melt(data = df,
# #id.vars = names(df)[which(!(names(df) %in% melt_cols))],
# measure.vars = melt_cols,
# variable.name = "cashflow")
# } else if(tolower(substr(underlying,1,1)) == "v"){
# df_list = lapply(pef@UnderlyingVintages$Underlying,
# function(v) get_data_ggplot(v, cols, melt_cols=cols, cumulative_cols, scaledBy, underlying = NA_character_,date_filter))
# names(df_list) = names(pef@UnderlyingVintages$Underlying)
#
# for(i in 1:length(df_list)) {
# v = names(df_list)[[i]]
# if(i == 1) {
# df_melt = cbind(df_list[[i]], vintage = rep(v, nrow(df_list[[i]])))
# } else {
# df_melt = rbind(df_melt, cbind(df_list[[i]], vintage = rep(v, nrow(df_list[[i]]))))
# }
# }
# }
# return(df_melt)
# }
# )
#----------------------PrivateFund constructor definition---------------------------------------------------------
PrivateFund = function(name = NA_character_,
id = NA_integer_,
strategy=NA_character_,
vintage=NA_integer_,
initialCommitment = NA_real_,
totalCommitment = NA_real_,
commitments = NULL,
cashFlows=NULL,
fmv = NULL,
periodData = NULL,
holdings = NULL,
pme_bm = NULL,
underlyingFunds = list(),
underlyingVintages = list(),
underlyingStrategies = list(),
freq = "d",
dataFreq = "m",
multiplier = 1e+06,
active = NA_integer_,
loadVintages = F,
loadStrategies = F,
loadFunds = F)
{
new("PrivateFund",
name = name,
id = id,
strategy = strategy,
vintage = vintage,
initialCommitment = initialCommitment,
totalCommitment = totalCommitment,
commitments = commitments,
cashFlows = cashFlows,
fmv = fmv,
periodData = periodData,
holdings = holdings,
pme_bm = pme_bm,
underlyingFunds = underlyingFunds,
underlyingStrategies = underlyingStrategies,
underlyingVintages = underlyingVintages,
freq = freq,
dataFreq = dataFreq,
multiplier = multiplier,
active = as.integer(active),
loadVintages = loadVintages,
loadStrategies = loadStrategies,
loadFunds = loadFunds
)
}
#----------------------PrivateFund privateIRR definition---------------------------------------------------------
# setMethod(f = "privateIRR",
# c("PrivateFund", "Period"),
# function(pef, per)
# {
# cf_net = pef@CashFlows$CashFlows_Net
# cf_gross = pef@CashFlows$CashFlows_Gross
# fmv = pef@FMV
#
# perf_start = max(end(cf_net), end(cf_gross), end(fmv)) %m-% per
# cf_net = cf_net[which(zoo::index(cf_net) >= perf_start)]
# cf_gross = cf_gross[which(zoo::index(cf_gross) >= perf_start)]
# fmv = fmv[which(zoo::index(fmv)>=perf_start)]
#
# cf_net = rbind(-fmv[1], cf_net, fmv[nrow(fmv)])
# cf_gross = rbind(-fmv[1], cf_gross, fmv[nrow(fmv)])
#
#
# return(UnderlyingFunds)
# }
# )
#----------------------PrivateFund loadUnderlying definition---------------------------------------------------------
setGeneric(name = "loadUnderlying", function(pef, mode, errorListName) standardGeneric("loadUnderlying"))
setMethod(f = "loadUnderlying",
c("PrivateFund", "character", "character"),
function(pef, mode, errorListName){
mode = tolower(strtrim(mode, 1))
freq = tolower(pef@Freq)
active = pef@Active
pme_bm = pef@PME_Benchmark
if(mode == "f"){
ids = pef@Holdings$Holding_ID
names(ids) = as.character(pef@Holdings$Holding_Name)
#underlying = lapply(ids, function(id)try(PrivateFund(id = id, freq = freq)))
underlying = lapply(ids,
function(id) captureErrors(func = PrivateFund,
captureList = errorListName,
default = NULL,
id = id,
freq = freq,
pme_bm = pme_bm))
} else if (mode == "v"){
vintages = sort(unique(pef@Holdings$Vintage))
strategy = pef@Strategy
names(vintages) = vintages
#underlying = lapply(vintages, function(v)try(PrivateFund(vintage = v, strategy = strategy, freq = freq)))
underlying = lapply(vintages,
function(v) captureErrors(func = PrivateFund,
captureList = errorListName,
default = NULL,
strategy = strategy,
vintage = v,
freq = freq,
active = active,
pme_bm = pme_bm))
# cf_agg = matrix(unlist(lapply(underlying,
# function(v){if(class(v) == "PrivateFund"){v@Stats$CashFlows}else{rep(0, 5)}})), ncol = 5, byrow = T)
# row.names(cf_agg) = names(underlying)
# colnames(cf_agg) = names(underlying[[1]]@Stats$CashFlows)
# if(any(as.numeric(row.names(cf_agg)[2:nrow(cf_agg)]) - as.numeric(row.names(cf_agg))[1:(nrow(cf_agg)-1)] > 1)){
# allYears = as.character(as.numeric(row.names(cf_agg)[1]):as.numeric(row.names(cf_agg)[nrow(cf_agg)]))
# missingYears = allYears[which(!(allYears %in% row.names(cf_agg)))]
# for(y in as.numeric(missingYears)){
# yearInsert = matrix(rep(0, 5), ncol = 5)
# cf_agg_temp = cf_agg[which(as.numeric(row.names(cf_agg)) > y),]
# if(!is.matrix(cf_agg_temp)){
# cf_agg_temp = matrix(cf_agg_temp, ncol = 5)
# row.names(cf_agg_temp) = row.names(cf_agg)[nrow(cf_agg)]
# }
# cf_agg = rbind(cf_agg[which(as.numeric(row.names(cf_agg)) < y),], yearInsert)
# row.names(cf_agg)[nrow(cf_agg)] = y
# cf_agg = rbind(cf_agg, cf_agg_temp)
# }
# }
#
# cf_agg_total = apply(cf_agg, 2, sum, na.rm = T)
#
# cf_agg = rbind(cf_agg, TOTAL = cf_agg_total)
cf_agg = captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying,
stats = "CashFlows")
perf_net_agg = captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying,
stats = "Performance",
net=T)
perf_gross_agg = captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying,
stats = "Performance",
net=F)
pme_net_agg = captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying,
stats = "PME_Performance",
net=T)
pme_gross_agg = captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying,
stats = "PME_Performance",
net=F)
underlying = list(Underlying = underlying,
Aggregated = list(CashFlows = cf_agg,
Performance = list(Net = perf_net_agg,
Gross = perf_gross_agg),
PME = list(Net = pme_net_agg,
Gross = pme_gross_agg)))
} else if (mode == "s"){
vintages = sort(unique(pef@Holdings$Vintage))
names(vintages) = vintages
strategies = sort(unique(pef@Holdings$Strategy))
names(strategies) = strategies
# underlying = lapply(strategies,
# function(s) lapply(vintages,
# function(v) try(PrivateFund(vintage = v, strategy = s, freq = freq))))
underlying = lapply(strategies,
function(s) lapply(vintages,
function(v) captureErrors(func = PrivateFund,
captureList = errorListName,
default = NULL,
strategy = s,
vintage = v,
freq = freq,
active = active,
pme_bm = pme_bm)))
cf_agg = lapply(strategies,
function(s) captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying[[s]],
stats = "CashFlows"))
perf_net_agg = lapply(strategies,
function(s) captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying[[s]],
stats = "Performance",
net = T))
perf_gross_agg = lapply(strategies,
function(s) captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying[[s]],
stats = "Performance",
net = F))
pme_net_agg = lapply(strategies,
function(s) captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying[[s]],
stats = "PME_Performance",
net = T))
pme_gross_agg = lapply(strategies,
function(s) captureErrors(func = aggregatePrivates,
captureList = errorListName,
default = NULL,
underlying = underlying[[s]],
stats = "PME_Performance",
net = F))
underlying = list(Underlying = underlying,
Aggregated = list(CashFlows = cf_agg,
Performance = list(Net = perf_net_agg,
Gross = perf_gross_agg),
PME = list(Net = pme_net_agg,
Gross = pme_gross_agg)))
}
return(underlying)
}
)
#----------------------PrivateFund compareHoldings definition---------------------------------------------------------
setGeneric(name = "compareHoldings", function(pef) standardGeneric("compareHoldings"))
setMethod(f = "compareHoldings",
c("PrivateFund"),
function(pef)
{
ids = pef@Holdings$Holding_ID
if(length(ids)>1)
{
if(length(pef@UnderlyingFunds) == 0){
names(ids) = as.character(pef@Holdings$Holding_Name)
freq = tolower(pef@Freq)
UnderlyingFunds = lapply(ids, function(id)new("PrivateFund", ID = id, Freq = freq))
}
else{
UnderlyingFunds = pef@UnderlyingFunds
}
comparisons = vector(mode = "list", length = 2)
names(comparisons) = c("Performance", "CashFlows")
comparisons$Performance = vector(mode = "list", length = ncol(pef@Stats$Performance))
names(comparisons$Performance) = colnames(pef@Stats$Performance)
comparisons$CashFlows = vector(mode = "list", length = ncol(pef@Stats$CashFlows))
names(comparisons$CashFlows) = colnames(pef@Stats$CashFlows)
for(comp in names(comparisons$Performance))
{
comparisons$Performance[[comp]] = vector(mode = "list", length = 2)
names(comparisons$Performance[[comp]]) = c("Total", "Underlying")
comparisons$Performance[[comp]]$Total = pef@Stats$Performance["NetFees", comp]
for(fund in UnderlyingFunds)
{
df = data.frame(fund@Stats$Performance["NetFees", comp], row.names = fund@Name)
colnames(df) = comp
if(is.null(comparisons$Performance[[comp]]$Underlying))
comparisons$Performance[[comp]]$Underlying = df
else
comparisons$Performance[[comp]]$Underlying = rbind(comparisons$Performance[[comp]]$Underlying, df)
}
ord = order(comparisons$Performance[[comp]]$Underlying, decreasing = T)
comparisons$Performance[[comp]]$Underlying = data.frame(comparisons$Performance[[comp]]$Underlying[ord, comp],
row.names = row.names(comparisons$Performance[[comp]]$Underlying)[ord])
colnames(comparisons$Performance[[comp]]$Underlying) = comp
}
for(comp in names(comparisons$CashFlows))
{
comparisons$CashFlows[[comp]] = vector(mode = "list", length = 2)
names(comparisons$CashFlows[[comp]]) = c("Total", "Underlying")
comparisons$CashFlows[[comp]]$Total = pef@Stats$CashFlows[, comp]
for(fund in UnderlyingFunds)
{
df = data.frame(fund@Stats$CashFlows[ , comp], row.names = fund@Name)
colnames(df) = comp
if(is.null(comparisons$CashFlows[[comp]]$Underlying))
comparisons$CashFlows[[comp]]$Underlying = df
else
comparisons$CashFlows[[comp]]$Underlying = rbind(comparisons$CashFlows[[comp]]$Underlying, df)
}
ord = order(comparisons$CashFlows[[comp]]$Underlying, decreasing = T)
comparisons$CashFlows[[comp]]$Underlying = data.frame(comparisons$CashFlows[[comp]]$Underlying[ord, comp],
row.names = row.names(comparisons$CashFlows[[comp]]$Underlying)[ord])
colnames(comparisons$CashFlows[[comp]]$Underlying) = comp
}
#
# if(tolower(substr(comparison, 1, 1)) == "i")
# {
# comp = "IRR"
# df = data.frame(IRR = pef@Performance$`2016-12-31`["NetFees", comp], row.names = c("Total"))
#
# }
# else
# {
# comp = "RollingMultiple"
# df = data.frame(IRR = pef@Performance[[1]]["NetFees", comp], row.names = c("Total"))
# }
# for(fund in UnderlyingFunds){
# newdf = data.frame(fund@Performance[[1]]["NetFees", comp], row.names = c(fund@Name))
# colnames(newdf) = comp
# rownames(newdf) = fund@Name
# df = rbind(df, newdf)
# }
return(comparisons)
}
# return(df)
}
)
#----------------------PrivateFund print definition---------------------------------------------------------
setMethod("print",
signature(c(x="PrivateFund")),
function(x)
{
pef = x
#perf = pef@Stats$Performance
# commit = sum(pef@Commitments)
# called_net = sum(pef@CashFlows[, "Calls_Total_Net"])
# called_gross = sum(pef@CashFlows[, "Calls_Total_Gross"])
# dists = sum(pef@CashFlows[, "Distributions_Total"])
# cf_stats = data.frame(Committed = commit,
# Called_Net = called_net,
# Called_Gross = called_gross,
# Distributed = dists)
cat('\nCash Flow Stats-------------------------------------------\n')
#print(cf_stats)
print(pef@Stats$CashFlows)
cat('\n\n')
cat('Performance Stats-------------------------------------------\n')
#print(perf)
print(pef@Stats$Performance)
})
#----------------------PrivateFund modelDistributions definition---------------------------------------------------------
# setMethod(f = "modelDistributions",
# c("PrivateFund"),
#
# function(pef)
# {
# require(yuima)
# dist_rate = data[, "DistributionRate"]
# fmv = data[zoo::index(dist_rate), "FMV"]
# dist_start = zoo::index(fmv[fmv!=0])[2]
# dist_rate = zoo::na.fill(dist_rate[zoo::index(dist_rate) >= dist_start], 0)
#
# param.init_shift = list(a = 1.1, b = -2, sigma = 1)
#
# low.par = list(a = 0, b = -1e+09, sigma = 0)
# upp.par = list(a = 1e+09, b = 0, sigma = 100)
# prior <-
# list(
# a=list(measure.type="code",df="dnorm(z,0,1)"),
# b=list(measure.type="code",df="dnorm(z,0,1)"),
# sigma=list(measure.type="code",df="dnorm(z,0,1)")
# )
#
# mod = setModel(drift = "(a + b*x)", diffusion = "sigma*sqrt(x)", solve.variable = "x")
# }
# )
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