财富管理:非线性依赖模型

IF 0.3 Q4 BUSINESS, FINANCE Algorithmic Finance Pub Date : 2017-01-01 DOI:10.3233/AF-170203
M. Montenegro, P. Albuquerque
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引用次数: 4

摘要

本研究以Markowitz(1952)提出的经典投资组合理论为基础,结合局部高斯相关模型进行优化,提出了一种增强型的投资组合选择方法。这种新颖的投资组合选择方法包含两个假设:收益的非线性和资产之间的关系是动态的经验观察。通过从1985年至2015年间雅虎财经从标准普尔500指数中选择10种资产,衡量新提出的模型的表现,并与Markowitz(1952)的投资组合选择模型进行比较。结果表明,使用局部高斯相关模型选择的投资组合在63%使用块引导的情况下优于传统的Markowitz(1952)方法,在71%使用标准引导的情况下优于传统的Markowitz(1952)方法。比较计算出的夏普比率,在研究的大多数情况下,提出的模型产生了更好的调整风险回报。5
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Wealth management: Modeling the nonlinear dependence
This work aims the development of an enhanced portfolio selection method, which is based on the classical portfolio theory proposed by Markowitz (1952) and incorporates the local Gaussian correlation model for optimization. This novel method of portfolio selection incorporates two assumptions: the non-linearity of returns and the empirical observation that the relation between assets is dynamic. By selecting ten assets from those available in Yahoo Finance from S&P500, between 1985 and 2015, the performance of the new proposed model was measured and compared to the model of portfolio selection of Markowitz (1952). The results showed that the portfolios selected using the local Gaussian correlation model performed better than the traditional Markowitz (1952) method in 63% of the cases using block bootstrap and in 71% of the cases using the standard bootstrap. Comparing the calculated Sharpe ratios, the proposed model yielded a better adjusted risk-return in the majority of the cases studied. 5
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来源期刊
Algorithmic Finance
Algorithmic Finance BUSINESS, FINANCE-
CiteScore
0.40
自引率
0.00%
发文量
6
期刊介绍: Algorithmic Finance is both a nascent field of study and a new high-quality academic research journal that seeks to bridge computer science and finance. It covers such applications as: High frequency and algorithmic trading Statistical arbitrage strategies Momentum and other algorithmic portfolio management Machine learning and computational financial intelligence Agent-based finance Complexity and market efficiency Algorithmic analysis of derivatives valuation Behavioral finance and investor heuristics and algorithms Applications of quantum computation to finance News analytics and automated textual analysis.
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