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Portalloc.

高效前沿组合的最佳资本分配

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Syntax

[风险，风险，风险，风险，风险，总体，总体return] = Portalloc（Portrack，Portryurn，Portwts，风险性）
[RiskyRisk,RiskyReturn,RiskyWts,RiskyFraction,OverallRisk,OverallReturn] = portalloc(___,BorrowRate,RiskAversion)
Portalloc.(PortRisk,PortReturn,PortWts,RisklessRate,BorrowRate,RiskAversion)

Description

example

[RiskyRisk,RiskyReturn,风险WTS,风险效力,总体缺席,OverallReturn] = portalloc(PortRisk,Portryurn.,PortWts,RisklessRate)计算这一风险投资组合之间的最佳风险投资组合和最佳资金NASSETSand the risk-free asset.

example

[RiskyRisk,RiskyReturn,风险WTS,风险效力,总体缺席,OverallReturn] = portalloc(___,BorrowRate,RiskAversion)specifies options using one or more optional arguments in addition to the input arguments in the previous syntax.

example

Portalloc.(PortRisk,Portryurn.,PortWts,RisklessRate,BorrowRate,RiskAversion)when invoked without any output arguments, a graph of the optimal capital allocation decision is displayed.

Examples

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打开直播脚本

此示例显示如何通过从资产数据生成高效的边界，然后查找最佳风险投资组合并分配资本来计算最佳风险投资组合。无风险投资回报率为8％，借款率为12％。

ExpReturn = [0.1 0.2 0.15]; ExpCovariance = [0.005 -0.010 0.004 -0.010 0.040 -0.002 0.004 -0.002 0.023]; [PortRisk, PortReturn, PortWts] = portopt(ExpReturn,。。。ExpCovariance); RisklessRate = 0.08; BorrowRate = 0.12; RiskAversion = 3; [RiskyRisk, RiskyReturn, RiskyWts, RiskyFraction,。。。总体缺席, OverallReturn] = portalloc(PortRisk, PortReturn,。。。Portwts，有风险，冒险，冒险
RiskyRisk = 0.1283
风险return = 0.1788
风险WTS =1×30.0265 0.6023 0.3712
风险效力= 1.1898
总体缺席= 0.1527
总体return = 0.1899.

Input Arguments

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每个风险资产高效前沿组合的标准偏差, specified as an逃亡-通过-1向量。

Data Types:double

每个风险资产高效边境投资组合的预期返回指定了一个逃亡-通过-1向量。

Data Types:double

分配给每个资产的权重, specified as an逃亡按资产数量（NASSETS）分配给每个资产的权重的矩阵。每行代表一个有效的风险资产的前沿组合。投资组合中的所有重量都是1。

Data Types:double

无风险贷款利率, specified as a scalar decimal.

Data Types:double

(Optional) Borrowing rate, specified as a scalar decimal. If borrowing is not desired, or not an option, set theBorrowRatetoNaN（这是默认值）。

Data Types:double

(Optional) Coefficient of investor's degree of risk aversion, specified as a scalar numeric. Higher numbers indicate greater risk aversion. Typical coefficients range from2.0through4.0。默认值RiskAversionis3。

Note

Consider that a less risk-averse investor would be expected to accept much greater risk and, consequently, a more risk-averse investor would accept less risk for a given level of return. Therefore, making theRiskAversionargument higher reflects the risk-return tradeoff in the data.

Data Types:double

Output Arguments

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Standard deviation of the optimal risky portfolio, returned as a scalar.

Expected return of the optimal risky portfolio, returned as a scalar.

Weights allocated to the optimal risky portfolio, returned a1-通过-NASSETS向量。The total of all weights in the portfolio is1。

Fraction of the complete portfolio (that is, the overall portfolio including risky and risk-free assets) allocated to the risky portfolio, returned as a scalar.

Standard deviation of the optimal overall portfolio, returned as a scalar.

Expected rate of return of the optimal overall portfolio, returned as a scalar.

参考资料

[1] Bodie，Z.，Kane，A.和A. Marcus。Investments.McGraw-Hill Education, 2013.

See Also

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Topics

在R2006A之前介绍

Financial Toolbox Documentation

万博1manbetx

A Practical Guide to Modeling Financial Risk with MATLAB

A Practical Guide to Modeling Financial Risk with MATLAB

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