Early warning or too late? A (pseudo-)real-time identification of leading indicators of financial stress

Duprey, Thibaut; Klaus, Benjamin

doi:10.1016/j.jbankfin.2021.106196

Cited by 16 publications

(7 citation statements)

References 31 publications

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“…The findings demonstrate the effectiveness of the three measures for early warning and forecasting [ 15 ]: liabilities/total assets, cash flow/total liabilities, and total net income/total assets. According to Duprey and Klaus, the multivariate discriminant analysis prediction model can only categorise whether the sample company is experiencing a financial failing crisis and cannot calculate the likelihood of a crisis [ 16 , 17 ]. Huang and Wang said that the model she created could ascertain the company's state and that operators were not required to have advanced professional skills in order to assess the company's health [ 18 ].…”

Section: Related Workmentioning

confidence: 99%

[Retracted] Prediction and Analysis of Corporate Financial Risk Assessment Using Logistic Regression Algorithm in Multiple Uncertainty Environment

Li¹,

Yan²,

Lu³

et al. 2022

Journal of Environmental and Public Health

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Currently, the level of economic globalisation is expanding, which gives organizations more room to grow while also subjecting them to an increasing amount of pressure from the market. Companies are forced to deal with an increasing number of unclear aspects due to the unstable internal and external environments, which also increases the risks they confront. A management system for corporate financial risk is according to studies on early warning systems for financial risks. Its goals are to raise the standard of corporate financial management and boost economic advantages, identify concerns and potential hazards in the corporate financial management process, stop corporate financial crises in their tracks, and lessen the losses brought on by such crises. The financial risk management of the organization is predicted and examined in this research using the logistic regression model. The use of a logistic regression model allows for the simultaneous analysis of various risk factors, such as discrete and continuous variables, as well as the analysis of external variables’ interactions and confounding. This method is suited for widespread usage in practice because it has shown exceptional outcomes in study that are 16.24% better than those of the conventional method.

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Section: Related Workmentioning

confidence: 99%

[Retracted] Prediction and Analysis of Corporate Financial Risk Assessment Using Logistic Regression Algorithm in Multiple Uncertainty Environment

Li¹,

Yan²,

Lu³

et al. 2022

Journal of Environmental and Public Health

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“…The house price-to-income ratio indicator [54], which is used in some of the literature studying real estate, can be used to measure the housing affordability of households and also to measure the prosperity of the real estate market. In this study, we will use this indicator to replace residential prices to perform robustness tests with the full sample.…”

Section: Robustness Testmentioning

confidence: 99%

A Study on the Factors Influencing Household Consumption from a Money Demand Perspective: Evidence from Chinese Urban Residents

Zhang,

Liu

2023

Sustainability

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Based on the classic Keynesian theory of money demand and city panel data, in this study, we investigate the impacts of different money demand motives on urban household consumption in China, and provide ideas for promoting sustainable growth in household consumption in China. The results of this study show the following: First, in general, the theory of money demand motivation can adequately explain household consumption in large and medium-sized cities in China. Second, the CPI time series has a significant adverse effect on the real money demand of most households. Third, residents significantly reduce food consumption to satisfy speculative money demand for financial instruments, and the lower the income level, the keener households are to invest in high-risk stocks. Fourth, even for high-income households, the precautionary money demand generated via the purchase of commercial insurance still has a significant crowding-out effect on their total consumption. Social security spending, which reduces the precautionary money demand of households, has a much more positive impact on high-income households.

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“…Most indices use a similar set of stress measures, such as spreads or volatility, but the market coverage differs sometimes. Broadly speaking, two types of indices exist: those focused exclusively on market prices like ours (Cardarelli, Elekdag and Lall, 2011;International Monetary Fund, 2018) and those that include also credit and money aggregates to track the evolution of leverage (Koop and Korobilis, 2014;Kapetanios, Price and Young, 2018) for a higher frequency analysis and a longer time span but focus only on a coincident measure of financial stress, while the latter requires a lower frequency and a shorter time span but may contain additional predictive power by capturing the leverage and credit cycle (Duprey and Klaus, 2021).…”

Section: The Ukfsi Against Alternative Indicesmentioning

confidence: 99%

Systemic Financial Stress and Macroeconomic Amplifications in the United Kingdom*

et al. 2021

Self Cite

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We develop a daily composite index of financial stress for the United Kingdom over 50 years, the UKFSI. The index includes market stress indicators based on their incremental information to capture financial crises. During the COVID-19 crisis, financial stress peaks but remains less severe than during the Global Financial Crisis. The UKFSI is used in a threshold vector autoregression to differentiate the economic dynamics between tranquil and stressful periods. We highlight the importance of nonlinearities that amplify shocks. But we find no evidence of financial shocks contributing to the COVID-19 crisis, possibly reflecting effective policy interventions. I. IntroductionOver the past five decades, the UK financial sector has been buffeted by a few major shocks, which have highlighted the importance of macro-financial linkages. On the one hand, the severe economic and financial meltdown during the global financial crisis (GFC) was amplified within the banking sector. On the other hand, the spread of the COVID-19 pandemic unleashed profound economic and financial stress, but the shock was partly absorbed by a more resilient banking sector and unprecedented policy support.Against this backdrop, we develop a daily systemic financial stress index for the United Kingdom, the UK Financial Stress Index (UKFSI). We demonstrate its importance for assessing the transmission of financial shocks and the amplification of small shocks during stressful periods.The UKFSI is a daily-from 1971 onwards-composite index of systemic financial stress, that is, it tracks periods characterized by higher volatilities, valuation losses and a JEL Classification numbers: C31, C54, G01, G15. *The authors thank Andy Blake, David Aikman, Lee Foulger and colleagues who participated in Bank of England seminars on the subject. The views expressed are those of the authors and do not necessarily reflect those of the Bank of England (its Monetary Policy Committee, Financial Policy Committee or Prudential Regulatory Committee) nor those of the Bank of Canada. All errors remain our own.

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Early warning or too late? A (pseudo-)real-time identification of leading indicators of financial stress

Cited by 16 publications

References 31 publications

[Retracted] Prediction and Analysis of Corporate Financial Risk Assessment Using Logistic Regression Algorithm in Multiple Uncertainty Environment

[Retracted] Prediction and Analysis of Corporate Financial Risk Assessment Using Logistic Regression Algorithm in Multiple Uncertainty Environment

A Study on the Factors Influencing Household Consumption from a Money Demand Perspective: Evidence from Chinese Urban Residents

Systemic Financial Stress and Macroeconomic Amplifications in the United Kingdom*

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