Feature Parity with numpy-financial?

[alecloudenback]

Numpy-financial functions:

• fv(rate, nper, pmt, pv[, when]) | Compute the future value.
• ipmt(rate, per, nper, pv[, fv, when]) | Compute the interest portion of a payment.
• irr(values) | Return the Internal Rate of Return (IRR).
• mirr(values, finance_rate, reinvest_rate) | Modified internal rate of return.
• nper(rate, pmt, pv[, fv, when]) | Compute the number of periodic payments.
• npv(rate, values) | Returns the NPV (Net Present Value) of a cash flow series.
• pmt(rate, nper, pv[, fv, when]) | Compute the payment against loan principal plus interest.
• ppmt(rate, per, nper, pv[, fv, when]) | Compute the payment against loan principal.
• pv(rate, nper, pmt[, fv, when]) | Compute the present value.
• rate(nper, pmt, pv, fv[, when, guess, tol, …]) | Compute the rate of interest per period.

Not sure that we actually want to have all of these. ActuaryUtilities provides a more flexible interface, I think?

E.g. for present value, the above definition restricts you:

• npv you can have a vector of rates, but not specify the timepoints. And the rate needs to be constant
• pv is the old calculator bond formula. Great for doing a super simple bond calc, but for everything else...?

In contrast, with ActuaryUtilities present_value(rate,cfs,times) or pv:

• rate can be a constant or a curve
• cfs can vary
• times lets you specify when cashflows occur and they can be of varying magnitude and at uneven times