Near optimal centering (b)

PortfolioOptimisers.optimise — Method

optimise(noc::NearOptimalCentering{<:Any, <:Any, <:Any, <:Any, <:Any, <:Any, <:Any,
                  <:Any, <:Any, <:Any, <:Any, <:Any, Nothing
              },
         rd::ReturnsResult; str_names::Bool = false, save::Bool = true, kwargs...) -> NearOptimalCenteringResult

Run the Near Optimal Centering portfolio optimisation.

Arguments

noc: The near optimal centering optimiser to use.
rd: The returns result to use. If isa(noc.opt.pe, AbstractPriorResult), rd is not necessary if doing a standalone optimisation, but may be required/desired by fallbacks and/or clusterisation.
str_names: Whether to use string names for the assets in the optimisation.
save: Whether to save the JuMP model in the optimisation result.
kwargs: Additional keyword arguments passed to the optimisation function.

Validation

No field in the tree of noc holds an Online. An ArgumentError naming the field is thrown otherwise, through assert_batch_entry: a plain optimise is a batch fit, and a wrapper resolves only at the warm-up of the fold loop's online arm.

Related

source

optimise(noc::NearOptimalCentering{<:Any, <:Any, <:Any, <:Any, <:Any, <:Any, <:Any,
                  <:Any, <:Any, <:Any, <:Any, <:Any, Nothing
              },
         rd::ReturnsResult; str_names::Bool = false, save::Bool = true, kwargs...) -> NearOptimalCenteringResult

Run the Near Optimal Centering portfolio optimisation.

struct ReturnsResult{__T_nx, __T_X, __T_nf, __T_F, __T_nb, __T_B, __T_ts, __T_iv, __T_ivpa, __T_pnl} <: AbstractReturnsResult

Returns data of a universe: the asset returns, and optionally the factor returns, the benchmark returns, the timestamps, the implied volatilities and an Asset Panel.

optimise(
    opt::OptimisationEstimator,
    args...;
    kwargs...
) -> Union{HierarchicalRiskParityResult{HierarchicalResult{__T_pr, __T_clr, __T_wb, __T_fees, __T_retcode, __T_w, __T_imsk}, <:AbstractBaseRiskMeasure, <:Scalariser, Nothing} where {__T_pr, __T_clr, __T_wb, __T_fees, __T_retcode, __T_w, __T_imsk}, HierarchicalRiskParityResult{HierarchicalResult{__T_pr, __T_clr, __T_wb, __T_fees, __T_retcode, __T_w, __T_imsk}, <:AbstractVector{var"#s7444"}, <:Scalariser, Nothing} where {__T_pr, __T_clr, __T_wb, __T_fees, __T_retcode, __T_w, __T_imsk, var"#s7444"<:AbstractBaseRiskMeasure}}

Solve an optimisation estimator, and walk its fallback chain when a solve fails.

optimise(opt::OptimisationEstimator, args...; kwargs...) -> OptimisationResult
optimise(opt::OptimisationResult, args...; kwargs...) -> OptimisationResult

Run a portfolio optimisation with the estimator opt, and return an OptimisationResult.

optimise(
    td::Union{TimeDependent{<:AbstractVector{<:Union{var"#s7444", var"#s7443"} where {var"#s7444"<:NonFiniteAllocationOptimisationEstimator, var"#s7443"<:NonFiniteAllocationOptimisationResult}}}, TimeDependent{<:TimeDependentOptimiserCallable}, TimeDependent{<:PreviousWeightsFunction}, TimeDependent{<:Union{Function, Type}}},
    args...;
    kwargs...
) -> Any

Optimise with a TimeDependent schedule standing in for the optimiser, outside any fold loop.

optimise(pw::PreviousWeights{<:Any, <:Any, Nothing}, rd::ReturnsResult = ReturnsResult();
         kwargs...) -> NaiveOptimisationResult

Hold the weights the head carries.

optimise(bcrp::BestConstantRebalancedPortfolio{<:Any, <:Any, <:Any, <:Any, Nothing},
         rd::ReturnsResult; kwargs...) -> NaiveOptimisationResult

Run the best constant rebalanced portfolio optimisation.

optimise(ew::EqualWeighted{<:Any, <:Any, <:Any, <:Any, Nothing},
         rd::ReturnsResult; kwargs...) -> NaiveOptimisationResult

Run the equal-weighted portfolio optimisation.

optimise(iv::InverseVolatility{<:Any, <:Any, <:Any, <:Any, <:Any, Nothing},
         rd::ReturnsResult; kwargs...) -> NaiveOptimisationResult

Run the inverse volatility portfolio optimisation.

optimise(rw::RandomWeighted{<:Any, <:Any, <:Any, <:Any, <:Any, <:Any, <:Any, Nothing},
         rd::ReturnsResult; kwargs...) -> NaiveOptimisationResult

Run the random-weighted portfolio optimisation.

optimise(hrp::HierarchicalRiskParity{<:Any, <:Any, <:Any, <:Nothing},
         rd::ReturnsResult; kwargs...) -> HierarchicalRiskParityResult

Run the Hierarchical Risk Parity portfolio optimisation.

optimise(sh::SchurComplementHierarchicalRiskParity{<:Any, <:Any, Nothing},
         rd::ReturnsResult; kwargs...) -> SchurComplementHierarchicalRiskParityResult

Run the Schur complement hierarchical risk parity optimisation.

optimise(hec::HierarchicalEqualRiskContribution{
                 <:Any, <:Any, <:Any, <:Any, <:Any, <:Any, Nothing
             },
        rd::ReturnsResult; branchorder::Symbol = :optimal, kwargs...) -> HierarchicalEqualRiskContributionResult

Run the Hierarchical Equal Risk Contribution portfolio optimisation.

optimise(nco::NestedClustered{<:Any, <:Any, <:Any, <:Any, <:Any, <:Any, <:Any,
                  <:Any, <:Any, <:Any, Nothing
              }, rd::ReturnsResult;
         branchorder::Symbol = :optimal, str_names::Bool = false,
         save::Bool = true, kwargs...) -> NestedClusteredResult

Run the Nested Clustered Optimisation portfolio optimisation.

optimise(st::Stacking{<:Any, <:Any, <:Any, <:Any, <:Any, <:Any, <:Any, <:Any,
                 <:Any, <:Any, Nothing
             }, rd::ReturnsResult;
         branchorder::Symbol = :optimal, str_names::Bool = false,
         save::Bool = true, kwargs...) -> StackingResult

Run the Stacking portfolio optimisation.

optimise(sr::SubsetResampling{<:Any, <:Any, <:Any, <:Any, <:Any, <:Any, <:Any,
                 <:Any, <:Any, <:Any, <:Any, <:Any, Nothing
             }, rd::ReturnsResult;
         branchorder::Symbol = :optimal, str_names::Bool = false,
         save::Bool = true, kwargs...) -> SubsetResamplingResult

Run the Subset Resampling portfolio optimisation.

optimise(da::DiscreteAllocation{<:Any, <:Any, <:Any, <:Any, Nothing},
         fai::FiniteAllocationInput; str_names::Bool = false,
         save::Bool = true, kwargs...) -> DiscreteAllocationResult

Allocate a book into whole shares with a DiscreteAllocation that carries no fallback.

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

Run the Greedy Allocation portfolio optimisation.

optimise(opt::OnlinePortfolioSelection{<:Any, <:Any, <:Any, <:Any, Nothing}, rd::ReturnsResult; kwargs...) -> NaiveOptimisationResult

Runs the Causal Pass over rd, and returns the Next-Period Allocation.

optimise(mr::MeanRisk{<:Any, <:Any, <:Any, <:Any, Nothing},
         rd::ReturnsResult; str_names::Bool = false, save::Bool = true, kwargs...) -> MeanRiskResult

Run the Mean-Risk portfolio optimisation.

optimise(frc::FactorRiskContribution{<:Any, <:Any, <:Any, <:Any, <:Any, <:Any,
                  <:Any, <:Any, Nothing
              },
         rd::ReturnsResult; str_names::Bool = false, save::Bool = true, kwargs...) -> FactorRiskContributionResult

Run the Factor Risk Contribution portfolio optimisation.

struct NearOptimalCentering{__T_opt, __T_r, __T_obj, __T_bins, __T_w_min, __T_w_min_ini, __T_w_opt, __T_w_opt_ini, __T_w_max, __T_w_max_ini, __T_ucs_flag, __T_alg, __T_fb} <: RiskJuMPOptimisationEstimator

Near Optimal Centering (NOC) portfolio optimiser.

struct NearOptimalCenteringResult{__T_jr, __T_r, __T_w_min_retcode, __T_w_opt_retcode, __T_w_max_retcode, __T_noc_retcode, __T_fb} <: RiskJuMPOptimisationResult

Result type for Near Optimal Centering portfolio optimisation.

optimise(rb::RiskBudgeting{<:Any, <:Any, <:Any, <:Any, Nothing},
         rd::ReturnsResult; str_names::Bool = false, save::Bool = true, kwargs...) -> RiskBudgetingResult

Run the Risk Budgeting portfolio optimisation.

optimise(rrb::RelaxedRiskBudgeting{<:Any, <:Any, <:Any, <:Any, Nothing},
         rd::ReturnsResult; str_names::Bool = false, save::Bool = true, kwargs...) -> RelaxedRiskBudgetingResult

Run the Relaxed Risk Budgeting portfolio optimisation.