# fmbasics - Financial Market Building Blocks [](https://CRAN.R-project.org/package=fmbasics) [](https://github.com/imanuelcostigan/fmbasics/actions?workflow=R-CMD-check) [](https://codecov.io/github/imanuelcostigan/fmbasics?branch=master) Implements basic financial market objects like currencies, currency pairs, interest rates and interest rate indices. You will be able to use Benchmark instances of these objects which have been defined using their most common conventions or those defined by International Swap Dealer Association (ISDA, ) legal documentation. ## Basic objects You can create instances of key currencies and currency pairs (and of course create your own implementations): ``` r library("fmdates") library("fmbasics") AUD() #> AUD AUDUSD() #> AUDUSD ``` These come with implementations of handy methods: ``` r library("lubridate") to_fx_value(dates = ymd(20171230), tenor = "spot", x = AUDUSD()) #> [1] "2018-01-03" to_fx_value(ymd(20171230), months(3), AUDUSD()) #> [1] "2018-04-03" ``` You can create instances of key IBOR or ONIA interest rate indices: ``` r USDLIBOR(months(3)) #> 3m USD LIBOR EONIA() #> EONIA ``` These also come with implementations of handy methods: ``` r to_reset(dates = as.Date("2017-01-20"), index = USDLIBOR(months(3))) #> [1] "2017-01-18" to_value(as.Date("2017-01-20"), USDLIBOR(months(3))) #> [1] "2017-01-24" to_maturity(as.Date("2017-01-20"), USDLIBOR(months(3))) #> [1] "2017-04-20" ``` ## Interest rates and discount factors You can create and perform basic manipulation of interest rates and discount factors: ``` r rr <- InterestRate(value = 0.01, compounding = Inf, day_basis = "act/365") as_DiscountFactor(rr, d1 = ymd(20170120), d2 = ymd(20210120)) #> 0.960763116514576, 2017-01-20--2021-01-20 # Convert to different rate basis as_InterestRate(rr, day_basis = "act/360") #> 0.9863014%, CONTINUOUS, ACT/360 as_InterestRate(rr, compounding = 2, day_basis = "act/360") #> 0.9887373%, SEMI-ANNUAL, ACT/360 dd <- DiscountFactor(0.75, d1 = ymd(20170120), d2 = ymd(20210120)) as_InterestRate(dd, compounding = Inf, day_basis = "act/360") #> 7.088675%, CONTINUOUS, ACT/360 ``` ## Pricing objects It is also possible to create and interpolate on zero coupon interest rate curves: ``` r zc <- build_zero_curve() plot(zc$pillar_times, zc$pillar_zeros, xlab = 'Years', ylab = 'Zero') ```  ``` r interpolate(zc, year_frac(zc$reference_date, ymd(20170331), "act/365")) #> [1] 0.0187453 interpolate_zeros(zc, ymd(20170331)) #> 1.87453%, CONTINUOUS, ACT/365 interpolate_fwds(zc, ymd(20170331), ymd(20170630)) #> 1.837274%, SIMPLE, ACT/365 interpolate_dfs(zc, ymd(20170331), ymd(20170630)) #> 0.995440285935839, 2017-03-31--2017-06-30 ``` Basic support for creating and interpolating volatility surfaces is possible: ``` r # vs <- build_vol_surface() # at <- tibble::tibble( # maturity = as.Date(c("2020-03-31", "2021-03-31")), # smile = c(0.40, 0.80) # ) # interpolate(vs, at) ``` Further details can be found in this package’s help pages and vignettes (`vignette(package = "fmbasics")`)