In AZASRS/AZASRS: ASRS Database R API

knitr::opts_chunk$set(echo = TRUE)
library(tidyverse)
library(purrr)
library(AZASRS)

Calculate Private Market Metrics

The first entry for the build_grouped_pm_metrics function is ... - this is where you can insert the breakdown you'd like.

For example, to simply see by fund, you could use build_grouped_pm_metrics(pm_fund_common_name)

For inception to date, simply use itd = TRUE

# ITD category metrics
df = build_grouped_pm_metrics(pm_fund_portfolio, pm_fund_category_description, 
                              itd = TRUE)
df

For any date range other than ITD, simply enter a start and end date. Note that certain metrics will be NA. This will be true for any metrics that require itd=TRUE

# Last quarter's portfolio metrics
value_date = get_value_date()
start_date = calc_add_qtrs(value_date, -1)

df = build_grouped_pm_metrics(pm_fund_common_name,
                              start_date = start_date,
                              end_date = value_date)
df

If doing more than 1 calculation!

Setup all data

con = AZASRS_DATABASE_CONNECTION()
nav_daily = get_pm_nav_daily(con = con)
cf_daily = get_pm_cash_flow_daily(con = con)
bench_daily = get_benchmark_daily_index(con = con, benchmark_type = "PVT", return_tibble = TRUE)
bench_relationships = get_benchmark_fund_relationship(con = con, bench_type = "PVT", return_tibble = TRUE)
pm_fund_info = get_pm_fund_info(con = con)

Then call based off of variable dates

cash_adjusted = FALSE
itd = FALSE
start_date = "2014-12-31"
end_date = get_value_date(con = con)

df = build_grouped_pm_metrics(pm_fund_common_name,
                               con = con,
                               start_date = start_date,
                               end_date = end_date,
                               itd = itd,
                               cash_adjusted = cash_adjusted,
                               nav_daily = nav_daily,
                               cf_daily = cf_daily,
                               bench_daily = bench_daily,
                               bench_relationships = bench_relationships,
                               pm_fund_info = pm_fund_info)

df

For ALL date ranges :)

date_ranges <- tibble()
for (i in c(1, 4, 12, 20, 40)) {
  date_range <- build_lagged_date_range_df(
    start_date = "2004-06-30",
    end_date = end_date, n_qtrs = i
  ) %>%
    mutate(n_qtrs = i)
  date_ranges <- bind_rows(date_ranges, date_range)
}

date_range_itd <- build_lagged_date_range_df(
  start_date = "2004-06-30",
  end_date = end_date, n_qtrs = 1
) %>%
  mutate(n_qtrs = 1)