分析危机对银行财务比率的影响

Osman Nal, A. Cai
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引用次数: 0

摘要

在这项研究中,我们提供了一个实用的框架和方法来分析银行冲击(经济或金融性质)对银行基本面的影响,避免使用复杂的计量经济学方法。为此,我们将注意力集中在2007-2008年全球金融危机对美国四大银行的影响上,并使用2002-第四季度至2020-第二季度的季度监管数据,研究了这些机构选定财务比率的趋势变化。我们首先绘制每家银行这些财务比率的时间序列图表,并比较危机前、过渡期和危机后的时期。为此,我们简单地将趋势线与银行数据的移位、斜率和波动性三个参数拟合。shift参数描述了在比较危机前后时期变量的水平变化。斜率参数表示趋势线的陡峭度差异,而波动性参数与所有三个周期相关,并描述每个周期内数据的变化。我们的研究结果表明,与危机前相比,危机后时期的资本比率(一项重要的监管金融比率)全面较高,表明这是一种积极的转变。我们没有看到资本比率系列斜率参数的显著变化,这导致我们建议使用虚拟变量回归模型,其中斜率被视为固定常数。我们进一步表明,危机前和过渡期的特点是波动性较高,最终在危机后时期消退。最后,我们建议金融从业者使用位移、斜率和波动性参数来理解金融时间序列数据的趋势,因为与更复杂的计量经济模型相比,它更容易实施和解释结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analyzing Impact of a Crisis on Bank Financial Ratios
In this study we provide a practical framework and methodology for analyzing the effects of banking shocks (economic or financial in nature) on bank fundamentals, that avoids the use of complicated econometrics methods. For this, we focus our attention to the effects of the 2007-2008 global financial crisis on the four largest US banks and examine the variation of trends in the select financial ratios for those institutions using quarterly regulatory data running from 2002-Q4 to 2020-Q2. We start by plotting time series charts of those financial ratios for each bank and compare the before-crisis, transition and after-crisis periods. For this, we simply fit trend lines with three parameters of shift, slope, and volatility to the banking data. The shift parameter describes the level change of the variable when before- and after-crisis periods are compared. The slope parameter pronounces the difference in steepness of the trend lines, while the volatility parameter is associated with all three periods and describe the variation in the data during each period. Our results indicate that capital ratios, an important regulatory financial ratio, are higher across the board in the after-crisis period compared to before-crisis period, suggesting a positive shift. We don’t see significant changes in slope parameter for the capital ratio series leading us to suggest the use of dummy variable regression model where slope is treated as a fixed constant. We further show that pre-crisis and transition periods are characterized by higher volatilities that ultimately subside in the after-crisis period. Lastly, we conclude by suggesting that financial practitioners use the shift, slope and volatility parameters in understanding trends in financial time series data since it is easy to implement and interpret the results compared to more sophisticated econometric models.
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