On the mitigation of valuation uncertainty risk: the importance of a robust proxy for the “cumulative state of market incompleteness”

IF 0.4 4区 经济学 Q4 BUSINESS, FINANCE
Oghenovo Adewale Obrimah
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引用次数: 1

Abstract

Suppose the same set of assets enters a primary market in either a monotone decreasing or monotone increasing sequence of asset risk. This study shows that the errors that attend the valuations of those assets in the context of the two different orderings are noncoincident. The sequence in which new assets arrive within a market is thus a source of valuation uncertainty risk. The formal theory shows that both asset risk and valuation uncertainty risk are mitigated if investors condition valuations of new assets on a dynamically evolving intertemporal mechanism that has parameterization as an explicit robust measure for the “cumulative state of [market] incompleteness” (CSI). Theoretically, relative to every preceding state, the CSI is a sufficient measure for the severity of market-conditioned valuation uncertainty risk. Although the derivation of a specific measure for the CSI is beyond the scope of this study, the formal theory arrives at three mathematically specified risk metrics that approximate the properties of the CSI. Let q and M denote, respectively, the individual initial public offering quality and the CSI. The CSI has the explicit parameterization Mt = ⋃ts=1(qs | Ms-1), as is expected of any well-defined measure, is self-propagating.
论降低估值不确定性风险:"市场不完备累积状态"的可靠代理的重要性
假设同一组资产以资产风险单调递减或单调递增的顺序进入一级市场。本研究表明,在两种不同排序的背景下,参与这些资产估值的误差是不一致的。因此,新资产进入市场的顺序是估值不确定性风险的一个来源。正式理论表明,如果投资者将新资产的估值置于动态演变的跨期机制上,则资产风险和估值不确定性风险都得到了缓解,该机制具有参数化作为“[市场]不完全性累积状态”(CSI)的明确稳健度量。理论上,相对于前一种状态,沪深指数足以衡量市场条件下估值不确定性风险的严重程度。虽然CSI的具体度量的推导超出了本研究的范围,但正式理论得出了三个数学上指定的风险度量,这些度量近似于CSI的属性。设q和M分别表示个体首次公开发行质量和沪深指数。CSI具有显式的参数化Mt =变数=1(qs | Ms-1),正如任何定义良好的测量所期望的那样,是自传播的。
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来源期刊
CiteScore
1.20
自引率
28.60%
发文量
8
期刊介绍: As monetary institutions rely greatly on economic and financial models for a wide array of applications, model validation has become progressively inventive within the field of risk. The Journal of Risk Model Validation focuses on the implementation and validation of risk models, and aims to provide a greater understanding of key issues including the empirical evaluation of existing models, pitfalls in model validation and the development of new methods. We also publish papers on back-testing. Our main field of application is in credit risk modelling but we are happy to consider any issues of risk model validation for any financial asset class. The Journal of Risk Model Validation considers submissions in the form of research papers on topics including, but not limited to: Empirical model evaluation studies Backtesting studies Stress-testing studies New methods of model validation/backtesting/stress-testing Best practices in model development, deployment, production and maintenance Pitfalls in model validation techniques (all types of risk, forecasting, pricing and rating)
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