ActuaryUtilities

cfs = [5, 5, 105]
times    = [1, 2, 3]

discount_rate = 0.03

present_value(discount_rate, cfs, times)           # 105.65
duration(Macaulay(), discount_rate, cfs, times)    #   2.86
duration(discount_rate, cfs, times)                #   2.78
convexity(discount_rate, cfs, times)               #  10.62

A collection of common functions/manipulations used in Actuarial Calculations.

• duration:
  • Calculate the Macaulay, Modified, or DV01 durations for a set of cashflows
  • Calculate the KeyRate(time) (a.k.a. KeyRateZero)duration or KeyRatePar(time) duration
• convexity for price sensitivity
• Flexible interest rate models via the FinanceModels.jl package.
• internal_rate_of_return or irr to calculate the IRR given cashflows (including at timepoints like Excel's XIRR)
• breakeven to calculate the breakeven time for a set of cashflows
• accum_offset to calculate accumulations like survivorship from a mortality vector
• spread will calculate the spread needed between two yield curves to equate a set of cashflows

• Calculate risk measures for a given vector of risks:
  • CTE for the Conditional Tail Expectation
  • VaR for the percentile/Value at Risk
  • WangTransform for the Wang Transformation
  • ProportionalHazard for proportional hazards
  • DualPower for dual power measure

• duration:
  • Calculate the duration given an issue date and date (a.k.a. policy duration)

• functions which return a rate/yield will return a FinanceCore.Rate object. E.g. irr(cashflows) will return a Rate(0.05,Periodic(1)) instead of just a 0.05 (float64) to convey the compounding frequency. This is compatible across the JuliaActuary ecosystem and can be used anywhere you would otherwise use a simple floating point rate.

A couple of other notes:

• rate(...) will return the scalar rate value from a Rate struct:

julia> r = Rate(0.05,Periodic(1));

julia> rate(r) 
0.05

• You can still pass a simple floating point rate to various methods. E.g. these two are the same (the default compounding convention is periodic once per period):

discount(0.05,cashflows)

r = Rate(0.05,Periodic(1));
discount(r,cashflows)

• convert between rates with:

r = Rate(0.05,Periodic(1));

convert(Periodic(2),  r)   # convert to compounded twice per timestep
convert(Continuous(2),r)   # convert to compounded twice per timestep

For more on Rates, see FinanceCore.jl. FinanceModels.jl also provides a rich and flexible set of yield models to use.

Full documentation is available here.

See JuliaActuary.org for instructions on running this example.

Functions often use a mix of interest_rates, cashflows, and timepoints. When calling functions, the general order of the arguments is 1) interest rates, 2) cashflows, and 3) timepoints.