Enhanced Indexation Based on Second-Order Stochastic Dominance
Enhanced Indexation Based on Second-Order Stochastic Dominance
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DOI：
10.2139/ssrn.1776966
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发表时间：
2011-03
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通讯作者：
Diana Roman;G. Mitra;Victor Zverovich
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文献类型：
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作者：
Diana Roman;G. Mitra;Victor Zverovich
二阶随机优势（SSD）在投资组合选择中具有公认的重要性，因为它提供了对风险厌恶投资者行为理论的自然解释。最近，基于SSD的投资组合选择模型已被提出;这些模型假设一个参考分布是可用的，并构造一个投资组合，其收益分布主导参考分布相对于SSD。我们提出了一个实证研究，分析了这种战略的有效性，在增强的indeferencies的背景下。通过投资组合再平衡和回测，研究了来自FTSE 100，SP 500和日经225的几个数据集。得出三个主要结论。首先，基于SSD的模型选择的投资组合始终优于指数和传统的指数跟踪器。其次，基于SSD的模型不需要施加基数约束，因为自然选择了少量的股票。因此，它们不存在通常与指数跟踪模型相关的计算困难。最后，基于SSD的模型对于场景集合中的小变化是鲁棒的，并且很少或不需要重新平衡。
Second order Stochastic Dominance (SSD) has a well recognised importance in portfolio selection, since it provides a natural interpretation of the theory of risk-averse investor behaviour. Recently, SSD-based models of portfolio choice have been proposed; these assume that a reference distribution is available and a portfolio is constructed, whose return distribution dominates the reference distribution with respect to SSD. We present an empirical study which analyses the effectiveness of such strategies in the context of enhanced indexation. Several datasets, drawn from FTSE 100, SP 500 and Nikkei 225 are investigated through portfolio rebalancing and backtesting. Three main conclusions are drawn. First, the portfolios chosen by the SSD based models consistently outperformed the indices and the traditional index trackers. Secondly, the SSD based models do not require imposition of cardinality constraints since naturally a small number of stocks are selected. Thus, they do not present the computational difficulty normally associated with index tracking models. Finally, the SSD based models are robust with respect to small changes in the scenario set and little or no rebalancing is necessary.