衡量实验性资产市场中的错误定价

Owen Powell
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引用次数: 3

摘要

错误定价(价格与其潜在基本价值之间的差异)是市场的一个重要特征。关于该主题的文献包括许多不同的测量方法。这种情况是不能令人满意的,因为不清楚结果对测量方法的选择有多大的敏感性。本文表明,数字无关性是一个重要的条件,它使以前的许多基于算术均值的测度成为不可能。此外,在附加的假设下,可以证明几何均值是唯一满足数值独立性的聚集函数。这导致了两种新的错误定价方法的提出,几何偏差(用于定价过高)和几何绝对偏差(用于绝对错误定价)。一个应用程序说明了这些新措施对先前实验结果的潜在影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measuring Mispricing in Experimental Asset Markets
Mispricing (the difference between prices and their underlying fundamental values) is an important characteristic of markets. The literature on the topic consists of many different measures. This state of affairs is unsatisfactory, since it is not clear to which extent results are sensitive to the choice of measure. This paper shows that numeraire independence is an important condition that disallows many previous arithmetic mean-based measures. Furthermore, under additional assumptions it can be shown that the geometric mean is the only such aggregation function to satisfy numeraire independence. This leads to the proposal of two new measures of mispricing, Geometric Deviation (for overpricing) and Geometric Absolute Deviation (for absolute mispricing). An application illustrates the potential impact of these new measures on previous experimental results.
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