What color is your balance sheet? The relevance and explanatory power of wealth accounts

E. Melse
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引用次数: 5

Abstract

The growing need for more relevant detail in financial statements proper to be produced annually, quarterly or monthly, and possibly continuously, translates into an urgent need for more advanced methods and tools for trend analysis. This paper takes a broader view at balance sheet analysis. We observe balance sheet items at the highest level of aggregation and compare them with the next level of detail. This exposes a multidimensional structure produced by all balance sheet items and their time points. This innovative approach to balance sheet analysis provides a new method to determine the relevance and materiality of accounting information. Instead of computing accounting ratios separately, we apply multivariate analysis as to explore the “data space” of the balance sheet of our example company: 3M. We study ten‐years of quarterly balance sheets and discuss some trends by comparing scatter plots with spectral map analysis – spectramap for short – and color coding to expose latent variables hidden in this data. We substantiate that we can explain the larger part of variance present in balance sheets in a more meaningful manner. This paper also seeks to corroborate the generality assumption that underlies the structure of the balance sheet. We strive to increase the usability of balance sheet data and underpin its explanatory power.
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你的资产负债表是什么颜色的?财富账户的相关性和解释力
由于越来越需要每年、每季度或每月甚至可能连续编制财务报表,因此迫切需要更先进的趋势分析方法和工具。本文对资产负债表分析采取了更广泛的观点。我们在汇总的最高层次观察资产负债表项目,并将其与下一层次的细节进行比较。这暴露了由所有资产负债表项目及其时间点产生的多维结构。这种创新的资产负债表分析方法为确定会计信息的相关性和重要性提供了一种新的方法。我们不是单独计算会计比率,而是应用多元分析来探索我们的例子公司3M的资产负债表的“数据空间”。我们研究了十年的季度资产负债表,并通过比较散点图和光谱图分析(光谱图用于短编码和彩色编码)来讨论一些趋势,以揭示隐藏在这些数据中的潜在变量。我们证实,我们可以以更有意义的方式解释资产负债表中存在的大部分方差。本文还试图证实作为资产负债表结构基础的一般性假设。我们努力提高资产负债表数据的可用性,巩固其解释力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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