Greedy allocation

PortfolioOptimisers.GreedyAllocationResult Type

struct GreedyAllocationResult{__T_retcode, __T_shares, __T_cost, __T_w, __T_cash, __T_fb} <: FiniteAllocationOptimisationResult

Result type for Greedy Allocation portfolio optimisation.

Fields

• retcode: Optimisation return code.

• shares: Number of shares allocated per asset.

• cost: Cost of the allocation.

• w: Realised portfolio weights.

• cash: Remaining uninvested cash after allocation.

• fb: Fallback result or estimator.

Related

• GreedyAllocation

• FiniteAllocationOptimisationResult

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PortfolioOptimisers.factory Method

factory(a::Union{Nothing, <:AbstractEstimator, <:AbstractAlgorithm,
                 <:AbstractResult}, args...; kwargs...) -> a

No-op factory function for constructing objects with a uniform interface.

Defining methods which dispatch on the first argument allows for a consistent factory interface across different types.

factory and port_opt_view are the two propagation mechanisms in this library. They are duals: factory threads runtime values (prior moments, observation weights, previous portfolio weights) down through a composed struct tree; port_opt_view threads an index selection (a subset of assets or observations) down through the same tree.

Arguments

• a: Indicates no object should be constructed.

• args...: Arbitrary positional arguments (ignored).

• kwargs...: Arbitrary keyword arguments (ignored).

Returns

• a: The input unchanged.

Examples

julia> factory(nothing, 1, 2; x = 3)

julia> factory(MeanValue())
MeanValue
  w ┴ nothing

Related

• port_opt_view

• AbstractEstimator

• AbstractAlgorithm

• AbstractResult

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factory(res::FiniteAllocationOptimisationResult, fb::Option{<:FOptE_FOpt})

Rebuild a finite allocation result with an updated fallback optimiser fb.

Like the continuous-result generic, every finite allocation result carries fb as its last field, so the rebuild copies all fields unchanged except the trailing fb. Concrete result types may override this method when rebuilding requires more than swapping fb.

Related

• FOptE_FOpt

• FiniteAllocationOptimisationResult

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PortfolioOptimisers.GreedyAllocation Type

struct GreedyAllocation{__T_unit, __T_args, __T_kwargs, __T_fb} <: FiniteAllocationOptimisationEstimator

Greedy Allocation portfolio optimiser.

GreedyAllocation converts continuous portfolio weights to discrete share quantities using a greedy two-pass allocation: first round shares to the nearest unit multiple, then iteratively buy remaining shares with leftover cash in order of largest weight.

Mathematical definition

$$\begin{array}{rl}{x}_i^{(0)}& =\mathrm{round}\left(\frac{w_{i}C}{p_i\cdot \mathrm{unit}}\right)\cdot \mathrm{unit},\\ r^{(0)}& =C-{\mathit{x}}^{(0)⊺}\mathit{p}.\end{array}$$

Then iteratively while $r>0$:

$$\begin{array}{rl}{i}^{\ast }& =\underset{i:p_i\le r}{\arg max}{w}_i,\\ x_{i^{\ast }}& \leftarrow x_{i^{\ast }}+\mathrm{unit},\\ r& \leftarrow r-p_{i^{\ast }}\cdot \mathrm{unit}.\end{array}$$

Where:

• $x_i^{(0)}$: Initial share allocation for asset $i$.

• $r^{(0)}$: Residual cash after initial allocation.

• $\mathit{w}$: Target weight vector.

• $C$: Available cash.

• $\mathit{p}$: Asset price vector.

• $\mathrm{unit}$: Minimum share purchase unit.

• $i^{\ast }$: Asset with largest weight among those affordable with remaining cash $r$.

• ${\mathit{x}}^{(0)}$: Initial share allocation vector.

Fields

• unit: Minimum purchase unit (e.g., price per share or lot size).

• args: Additional positional arguments forwarded to round.

• kwargs: Additional keyword arguments.

• fb: Fallback result or estimator.

Constructors

GreedyAllocation(;
    unit::Number = 1,
    args::Tuple = (),
    kwargs::NamedTuple = (;),
    fb::Option{<:FOptE_FOpt} = nothing
) -> GreedyAllocation

Keywords correspond to the struct's fields.

Validation

• unit > 0.

Examples

julia> GreedyAllocation()
GreedyAllocation
    unit ┼ Int64: 1
    args ┼ Tuple{}: ()
  kwargs ┼ @NamedTuple{}: NamedTuple()
      fb ┴ nothing

Related

• FiniteAllocationOptimisationEstimator

• DiscreteAllocation

• GreedyAllocationResult

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PortfolioOptimisers.roundmult Function

roundmult(val, prec, args...; kwargs...)

Round a value to the nearest multiple of prec.

Arguments

• val: Value to round.

• prec: Precision (multiple to round to).

• args...: Additional arguments passed to Base.round.

• kwargs...: Additional keyword arguments passed to Base.round.

Returns

• Rounded value.

Related

• GreedyAllocation

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PortfolioOptimisers.finite_sub_allocation! Function

finite_sub_allocation!(w, p, cash, bgt, ...)

In-place finite allocation for one side (long or short) of the portfolio using the greedy algorithm.

Modifies the allocation in-place, greedily assigning shares to assets to minimise allocation error.

Arguments

• w: Target portfolio weights (in-place modified).

• p: Asset prices.

• cash: Cash available.

• bgt: Budget target.

• Additional parameters.

Returns

• Modified allocation vector.

Related

• finite_sub_allocation

• GreedyAllocation

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PortfolioOptimisers.optimise Method

optimise(ga::GreedyAllocation{<:Any, <:Any, <:Any, Nothing},
         fai::FiniteAllocationInput; kwargs...) -> GreedyAllocationResult

Run the Greedy Allocation portfolio optimisation.

Arguments

• ga: The greedy allocation optimiser to use.

• fai: The FiniteAllocationInput carrying the target weights, prices, cash budget, and optional horizon and fees.

• kwargs: Additional keyword arguments passed to the optimisation function.

Related

• GreedyAllocation

• GreedyAllocationResult

• FiniteAllocationInput

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