Add more profit measures

[alecloudenback]

There's already breakeven, irr, embedded_value (via pv) Add

• moic: multiple on invested capital
• mirr: modified irr (ref Feature Parity with numpy-financial? #27)

[leeyuntien]

Has mirr been implemented? If not maybe i can take a stab.

[alecloudenback]

Has mirr been implemented? If not maybe i can take a stab.

Nope, it hasn't! Go for it :)

[KuldeepBorkar]

@alecloudenback could you please tell me where npv (net present value) is implemented so that I can use it to implement mirr

[alecloudenback]

@alecloudenback could you please tell me where npv (net present value) is implemented so that I can use it to implement mirr

ActuaryUtilities.jl/src/financial_math.jl

Lines 1 to 136 in bf6e13b

	"""
	present_value(interest, cashflows::Vector, timepoints)
	present_value(interest, cashflows::Vector)
	Discount the `cashflows` vector at the given `interest_interestrate`, with the cashflows occurring
	at the times specified in `timepoints`. If no `timepoints` given, assumes that cashflows happen at times 1,2,...,n.
	The `interest` can be an `InterestCurve`, a single scalar, or a vector wrapped in an `InterestCurve`.
	# Examples
	```julia-repl
	julia> present_value(0.1, [10,20],[0,1])
	28.18181818181818
	julia> present_value(Yields.Forward([0.1,0.2]), [10,20],[0,1])
	28.18181818181818 # same as above, because first cashflow is at time zero
	```
	Example on how to use real dates using the [DayCounts.jl](https://github.com/JuliaFinance/DayCounts.jl) package
	```jldoctest
	using DayCounts
	dates = Date(2012,12,31):Year(1):Date(2013,12,31)
	times = map(d -> yearfrac(dates[1], d, DayCounts.Actual365Fixed()),dates) # [0.0,1.0]
	present_value(0.1, [10,20],times)
	# output
	28.18181818181818
	```
	"""
	function present_value(yc::T, cashflows, timepoints) where {T <: Yields.AbstractYield}
	s = 0.0
	for (cf,t) in zip(cashflows,timepoints)
	v = discount(yc,t)
	@muladd s = s + v * cf
	end
	# sum(discount(yc,t) * cf for (t,cf) in zip(timepoints, cashflows))
	s
	end
	function present_value(yc::T, cashflows) where {T <: Yields.AbstractYield}
	present_value(yc,cashflows,1:length(cashflows))
	end
	function present_value(i, x)
	v = 1.0
	v_factor = discount(i,0,1)
	pv = 0.0
	for (t,cf) in enumerate(x)
	v = v * v_factor
	@muladd pv = pv + v * cf
	end
	return pv
	end
	function present_value(i, v, times)
	return present_value(Yields.Constant(i), v, times)
	end
	# Interest Given is an array, assume forwards.
	function present_value(i::AbstractArray, v)
	yc = Yields.Forward(i)
	return sum(discount(yc, t) * cf for (t,cf) in enumerate(v))
	end
	# Interest Given is an array, assume forwards.
	function present_value(i::AbstractArray, v, times)
	yc = Yields.Forward(i, times)
	return sum(discount(yc, t) * cf for (cf, t) in zip(v,times))
	end
	"""
	pv()
	An alias for `present_value`.
	"""
	pv = present_value
	"""
	present_value(interest, cashflows::Vector, timepoints)
	present_value(interest, cashflows::Vector)
	Efficiently calculate a vector representing the present value of the given cashflows at each period prior to the given timepoint.
	# Examples
	```julia-repl
	julia> present_values(0.00, [1,1,1])
	[3,2,1]
	julia> present_values(Yields.Forward([0.1,0.2]), [10,20],[0,1])
	2-element Vector{Float64}:
	28.18181818181818
	18.18181818181818
	```
	"""
	function present_values(interest, cashflows)
	pvs = Vector{Float64}(undef,length(cashflows))
	pvs[end] = Yields.discount(interest, lastindex(cashflows) - 1, lastindex(cashflows)) * cashflows[end]
	for (t, cf) in Iterators.reverse(enumerate(cashflows[1:end - 1]))
	pvs[t] = Yields.discount(interest, t - 1, t) * (cf + pvs[t + 1])
	end
	return pvs
	end
	function present_values(interest,cashflows,times)
	present_values_accumulator(interest,cashflows,times)
	end
	function present_values_accumulator(interest,cashflows,times,pvs=[0.0])
	from_time = length(times) == 1 ? 0. : times[end-1]
	pv = discount(interest,from_time,last(times)) *(first(pvs) + last(cashflows))
	pvs = pushfirst!(pvs,pv)
	if length(cashflows) > 1
	new_cfs = @view cashflows[1:end-1]
	new_times = @view times[1:end-1]
	return present_values_accumulator(interest,new_cfs,new_times,pvs)
	else
	# last discount and return
	return pvs[1:end-1] # end-1 get rid of trailing 0.0
	end
	end
	# if given a vector of rates, assume that it should be a forward discount yield
	function present_values(y::Vector{T}, cfs, times) where {T <: Real}
	return present_values(Yields.Forward(y), cfs, times)
	end

[KuldeepBorkar]

@alecloudenback I was able to find PV there but I was not able to find NPV.
Is NPV implemented seperately or should I be using PV only????
Could you please elaborate a bit😿

[alecloudenback]

present_value is a more flexible and generic version of what other languages (python, Excel) call NPV, see #27