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A NON-PARAMETRIC TEST PROCEDURE BASED ON RANGE STATISTICS TO IDENTIFY CAUSES OF NON-NORMALITY IN SPECULATIVE PRICE CHANGE DISTRIBUTIONS.

机译:一种基于范围统计量的非参数测试程序,用于识别价格变动中价格异常的原因。

摘要

Most models of asset pricing or market equilibrium generally require the assumption of stationary price change generation. That is, the mean and/or variance of the price change is hypothesized to be constant over time. On the other hand, the widely accepted models of speculative price change generation, such as the subordinated stochastic process models, have their basis in mixtures of random variables. These mixtures, or compositisations, define non-stationary, non-Normally distributed forms. Therefore, the models based on mixtures cannot be reconciled to requirements of stationarity. A contaminated process, such as that suggested by Mandelbroit, implies continuously changing mean and/or variance. However, an alternative concept of mixture exists, which is consistent with models requiring stationary moments. This process is referred to as slippage. Slippage defines a state where moments are constant for intervals of time, but do change value. If speculative price changes were found to be characterized by slippage, rather than by contamination, then such a finding would still be consistent with the empirical distributions of price changes. More importantly, slippage would meet the requirement of stationarity imposed on the capital market and options models. This work advanced a methodology that discriminates between contamination-based and slippage-based non-stationarity in speculative price changes. Such a technique is necessary, inasmuch as curve fitting or estimation of moments cannot so discriminate. The technique employs non-parametric range estimators. Any given form of non-Normality induces an identifiable pattern of bias upon these estimators. Once a pattern induced by a time series of price changes is identified; this pattern then infers whether contamination, or, alternatively, slippage, generated the time series. Due to the composition and technique of the procedure developed here, it is referred to as a "Range Spectrum." The results examined here find that stocks do display contamination, as hypothesized by the subordinate stochastic models. A broad based index of price change, however, displays the characteristics of slippage. This quality not only has implications for, but suggests possibilities for further research, in the areas of diversification, securities and options pricing, and market timing.
机译:大多数资产定价或市场均衡模型通常都需要假设固定价格变动的产生。即,假设价格变化的均值和/或方差随时间变化是恒定的。另一方面,被广泛接受的投机性价格变动产生模型,例如从属随机过程模型,则以混合随机变量为基础。这些混合物或复合物定义了非平稳的,非正态分布的形式。因此,基于混合的模型不能符合平稳性的要求。像曼德尔布罗伊特(Mandelbroit)所建议的那样,受污染的过程意味着不断变化的均值和/或方差。但是,存在混合的替代概念,这与需要平稳力矩的模型是一致的。此过程称为滑移。打滑定义了一种状态,在该状态下,矩在一定的时间间隔内保持不变,但会改变值。如果发现投机性价格变动的特征是滑点而不是污染,那么这种发现仍将与价格变动的经验分布相一致。更重要的是,滑点将满足对资本市场和期权模型施加平稳性的要求。这项工作提出了一种方法,该方法可以区分投机价格变动中基于污染的和基于滑动的非平稳性。这种技术是必需的,因为曲线拟合或力矩估计不能如此区分。该技术采用非参数范围估计器。任何给定形式的非正态性都会在这些估计量上引起可识别的偏差模式。一旦确定了由价格变化的时间序列引起的模式;然后,此模式可以推断是污染还是滑动产生了时间序列。由于此处开发的过程的组成和技术,它被称为“范围频谱”。此处检查的结果发现,库存确实显示出污染,这是由下级随机模型所假设的。然而,广泛的价格变化指数显示出滑点的特征。这种质量不仅对多元化​​,证券和期权定价以及市场时机领域有影响,而且为进一步研究提供了可能性。

著录项

  • 作者

    ABRAHAMSON ALLEN ARNOLD.;

  • 作者单位
  • 年度 1982
  • 总页数
  • 原文格式 PDF
  • 正文语种 en
  • 中图分类

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