A-KA Model: an Optimization of the Stock’s Portofolio

Filippo Regina, M. Bisceglia
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引用次数: 1

Abstract

Abstract The elaborate proposes a compact alternative methodology to the classical stocks portfolio optimization based on the normal distribution of the returns of the assets named Adaptable - Kurtosis Asymmetry model (A-KA). In the financial theory is well-known that odd-order moments of a distribution describe a particular performance characteristic; on the contrary, the even-order moments tell a precise sense of risk of a distribution of returns. If it is true that, in general terms, minimizing the variance also minimizes the volatility of portfolio return is also true that we should minimize the kurtosis to get away from unpleasant situations in case “Extreme” events occur, especially if negative. The idea behind this paper is to exploit the four moments of return’s distributions, optimizing an alternative risk indicator to variance, such as the kurtosis of the final distribution of the portfolio, making constraints on distributive asymmetry, in a dynamic underlying logic.
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A-KA模型:股票投资组合的优化
摘要本文提出了一种基于资产收益正态分布的经典股票投资组合优化的紧凑替代方法——自适应峰度不对称模型(a-KA)。在金融理论中,众所周知,分布的奇数阶矩描述了一个特定的性能特征;相反,偶数阶矩反映了收益分布的精确风险感。如果在一般情况下,方差最小化也会使投资组合回报的波动性最小化,那么在“极端”事件发生的情况下,尤其是在负面情况下,我们也应该最小化峰度,以避免不愉快的情况。本文背后的想法是利用收益率分布的四个矩,在动态底层逻辑中优化方差的替代风险指标,如投资组合最终分布的峰度,对分配不对称性进行约束。
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发文量
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审稿时长
20 weeks
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