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Portalloc

最佳资本分配给有效的边境投资组合

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Syntax

[风险风险风险，风险收益，风险风险，风险折磨，整体风险，整体逆转] = Portalloc（Portrisk，Portresturn，PorteTurn，portwts，tighlessrate）
[RiskyRisk,RiskyReturn,RiskyWts,RiskyFraction,OverallRisk,OverallReturn] = portalloc(___,BorrowRate,RiskAversion)
Portalloc(PortRisk,PortReturn,PortWts,RisklessRate,BorrowRate,RiskAversion)

Description

example

[RiskyRisk,RiskyReturn,风险,风险折断,整体风险,OverallReturn] = portalloc(PortRisk,Portreturn,PortWts,RisklessRate)计算最佳风险投资组合和该风险投资组合之间的资金最佳分配NASSETSand the risk-free asset.

example

[RiskyRisk,RiskyReturn,风险,风险折断,整体风险,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,Portreturn,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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打开实时脚本

此示例显示了如何通过从资产数据中生成有效的前沿，然后找到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％，借贷利率为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,。。。整体风险, OverallReturn] = portalloc(PortRisk, PortReturn,。。。portwts，无风险，借贷，风险验证）
RiskyRisk = 0.1283
风险收益= 0.1788
危险=1×30.0265 0.6023 0.3712
风险折断= 1.1898
整体风险= 0.1527
总体= 0.1899

Input Arguments

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每个风险资产有效边界投资组合的标准偏差, specified as anNPORTS-经过-1向量。

Data Types:double

每个风险资产有效的边境投资组合的预期回报，指定NPORTS-经过-1向量。

Data Types:double

分配给每个资产的权重, specified as anNPORTS根据资产数量（NASSETS）分配给每个资产的权重矩阵。每行代表有效的风险资产前沿投资组合。投资组合中的所有权重为1。

Data Types:double

无风险贷款率, 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。的默认值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-经过-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

[1] Bodie，Z.，Kane，A。和A. Marcus。Investments.麦格劳 - 希尔教育，2013年。

Version History

在R2006a之前引入

See Also

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