Financial Market Crisis Research Articles

A study on the backtesting and correlation of systemic risk in Chinese financial institutions: an empirical analysis based on MES and Delta CoVaR

Effectively measuring the risk level of financial institutions is the key to preventing and defusing systemic risks. This paper uses the unconditional coverage test method to backtest the systemic risk of 35 listed financial institutions in China, and uses the quantile coherence method to construct a quantile frequency domain correlation network to explore the frequency domain mechanism of systemic risk correlation of financial institutions. The study found that: (1) During the financial market crisis, the Delta CoVaR commonly used systemic risk measurement indicators such as MES, CoVaR, and failed to effectively measure the systemic risk of China's financial institutions. (2) Compared with the short-term correlation layer and the medium-term correlation layer, China's financial institutions have obvious extreme risk linkage effects in the long-term correlation layer.(3) In the short-term, medium-term and long-term correlation layers, small and medium-sized financial institutions such as Ningbo Bank, Industrial Securities and Dongfang Energy all have high correlation importance. Relevant departments should pay attention to preventing the risk of "too correlated to fail" of small and medium-sized financial institutions in my country.

CEO overconfidence and the informativeness of bank stock prices

This study examines the effect of the overconfidence of chief executive officers (CEOs) on the informativeness of banks' stock prices. Using an option-based overconfidence measure, we demonstrate that banks with overconfident CEOs have less informative stock prices. This finding is robust to alternative measures of overconfident CEOs and to addressing endogeneity with propensity score matching, an instrumental variable approach, and difference-in-differences analysis. Furthermore, banking and financial market crises strengthen the negative effect of overconfident CEOs on stock price informativeness, especially in larger banks. Finally, better corporate governance or higher capital mitigates the negative impact of overconfident CEOs on banks' stock price informativeness. Policymakers should consider implementing supervisory strategies that require banks to provide accurate information and encourage private-sector monitoring of banks.

Analysing the impacts of unscheduled news events on stock market contagion during the epidemic

AbstractThis paper investigates the impact of unscheduled news announcements on market contagion during the COVID‐19 pandemic. Using coexceedance of stock returns as a metric for market contagion effect, we assess the contribution of news releases from the United States and China on the financial contagion of a representative group of global equity markets through a quantile analysis framework. The empirical results are mixed: news events originating in the United States have a greater impact on market contagion compared with those originating in China, especially at lower quantiles. Stock markets respond asymmetrically to good news versus bad news, and the latter lead to a sharper common fall among the markets than the boost to the market caused by good news. We also find evidence that conditional variance and investor sentiment play some role in the spread of financial market crises, despite differences in extent and direction.

Data-driven modeling of capital liquidity changes during financial market crises

Abstract Against the backdrop of the ongoing global financial crisis, clarifying the mechanism of the role of the drivers of capital liquidity changes is the basis for maintaining financial stability during financial market crises. This paper proposes the basic hypothesis of capital liquidity changes during a financial market crisis, with reference to related studies. Subsequently, a data-driven model of capital liquidity changes during the financial market crisis is constructed based on the vector autoregressive model, and the main nodes of capital liquidity changes during the financial market crisis are obtained according to the changes in the degrees of freedom of the model. The MCMC method is utilized to assess the model’s smoothness and ensure the stability of the data-driven model of capital liquidity changes. The empirical analysis of the model finds that the positive shock of capital liquidity change on stock growth rate exhibits a positive response, and the stock growth rate explains 0.527% and 1.292% of the capital liquidity change on average during one year of financial market crisis. It has also been found that the arbitrage motive drives capital liquidity more strongly during a financial market crisis compared to the hedging motives. The model proposed in this paper helps to prompt policymakers to monitor the changes in capital mobility and make useful decisions in a timely manner, which in turn maintains the stable operation of the financial market.

An exploration of the mathematical structure and behavioural biases of 21st century financial crises

In this paper we contrast the dynamics of the 2022 Ukraine invasion financial crisis with notable financial crises of the 21st century — the dot-com bubble, global financial crisis and COVID-19. We study the similarity in market dynamics and associated implications for equity investors between various financial market crises and we introduce new mathematical techniques to do so. First, we study the strength of collective dynamics during different market crises, and compare suitable portfolio diversification strategies with respect to the unique number of sectors and stocks for optimal systematic risk reduction. Next, we introduce a new linear operator method to quantify distributional distance between equity returns during various crises. Our method allows us to fairly compare underlying stock and sector performance during different time periods, normalising for those collective dynamics driven by the overall market. Finally, we introduce a new combinatorial portfolio optimisation framework driven by random sampling to investigate whether particular equities and equity sectors are more effective in maximising investor risk-adjusted returns during market crises.

Model-based reinforcement learning with non-Gaussian environment dynamics and its application to portfolio optimization.

The rapid development of quantitative portfolio optimization in financial engineering has produced promising results in AI-based algorithmic trading strategies. However, the complexity of financial markets poses challenges for comprehensive simulation due to various factors, such as abrupt transitions, unpredictable hidden causal factors, and heavy tail properties. This paper aims to address these challenges by employing heavy-tailed preserving normalizing flows to simulate the high-dimensional joint probability of the complex trading environment under a model-based reinforcement learning framework. Through experiments with various stocks from three financial markets (Dow, NASDAQ, and S&P), we demonstrate that Dow outperforms the other two based on multiple evaluation metrics in our testing system. Notably, our proposed method mitigates the impact of unpredictable financial market crises during the COVID-19 pandemic, resulting in a lower maximum drawdown. Additionally, we explore the explanation of our reinforcement learning algorithm, employing the pattern causality method to study interactive relationships among stocks, analyzing dynamics of training for loss functions to ensure convergence, visualizing high-dimensional state transition data with t-SNE to uncover effective patterns for portfolio optimization, and utilizing eigenvalue analysis to study convergence properties of the environment's model.

Business entrepreneurs’ intention towards takaful participation to mitigate risk: a study in Sri Lanka based on the theory of planned behaviour

PurposeTakaful is a social security approach that guarantees business risks in light of shari’ah, thus playing a crucial role in human life and the economy. The purpose of this study is to examine the factors that influence the behavioural intention of micro, small and medium-sized enterprises (MSMEs) entrepreneurs to participate in takaful in Sri Lanka.Design/methodology/approachThis study is designed quantitatively with deductive approach using the theory of planned behaviour. A total of 432 MSMEs in Sri Lanka were surveyed using convenience sampling to measure the intention to participate in takaful as a risk mitigation. The collected data were analysed through partial least square-structural equational modelling.FindingsAttitude, subjective norm and perceived behavioural control variables positively influenced the intention, with t-values of 3.216, 3.813 and 3.859, respectively. The influence of these variables exhibits not much difference.Research limitations/implicationsThis study only focuses on MSMEs and a general takaful scheme. Future researchers may consider family takaful involvement among Sri Lankan business entrepreneurs.Practical implicationsTakaful practitioners should gain from the entrepreneurs’ intention to participate in takaful. Findings from this study could help marketing managers to revamp their strategies to further attract the entrepreneurs and make them to understand risk they are facing and, subsequently, participate in the takaful scheme.Originality/valueThis paper focuses on the context of Muslim minority among pluralism, where there is no regulation for Islamic financial products and services, and under the Islamic financial market crisis. This unleashes how business owners feel about takaful system on different dimensions.

The Problematika kebijakan ekonomi di tengah Resesi Ekonomi dan dampaknya terhadap dunia pendidikan.

After the Covid – 19 Pandemic ended, there were very significant changes in various ways. One of the things that has changed is in the economic field. The pandemic has thrown the economy into disarray because human mobility is limited, so advancing the economy is very difficult. To overcome this, some countries have adopted a policy of raising interest rates simultaneously, which has implications for financial market crises and economic weakness, known as an economic recession. This has an indirect impact on the world of education. Because education cannot be separated from the economy, education can run smoothly if the economy is also running smoothly, but now there is a gap that causes problems in the world of education. The purpose of this article is to look at the problems that occurred in the world of education when these economic policies were implemented so that the term economic recession emerged. The author will try to find solutions to these problems from various scientific references, so hopefully we can overcome these problems as best we can. This research method is a survey and field study with data collection techniques is by observation and qualitative descriptive. The results obtained are that there are many problems in the world of education after the economic policy is implemented. In fact, this impact starts from the educational actors who are above and even reaches the educational actors who are below, namely students.

Securitization of pandemic risk by using coronabond.

This article investigates the pandemic risk coverage within the European Union member states through insurance securitization. This strategy allows the transfer of health risks from the insurance market to the financial markets. We focus on the financial market crisis caused by the COVID-19 pandemic to securitize the losses caused by the latter. Over the period from 24/01/2020 (the first proven case of contamination in Europe) to 31/03/2020 (end of the dramatic decrease in financial markets), we apply the extreme value theory allowing the selection of the trigger threshold. We identify an immediate reaction of the financial markets following a pandemic shock, the effect of which fades after a few days. The response of stock market indices, measured by the fluctuation of return rates, is not very high. Nevertheless, the reaction of the financial markets is sufficient for the corona bond triggering, provided that the threshold for triggering the incidence rate is optimal. In addition, the securitization of insurance risk could be an alternative process to the classic risk transfer techniques such as co-insurance and reinsurance. Finally, a reinsurance pool dedicated to the insurance scheme's management against the effects of a pandemic is crucial for insurance securitization. These results could have implications for various actors such as insurers, financial investors, and States.

Are Exchange Rate Contagions Asymmetric? Evidence from Emerging Market Economies

ABSTRACT In view of increasing importance of emerging market currencies in the global foreign exchange markets and the growing concerns regarding the vulnerability of these currencies to global crises, we assess the connectedness of 16 emerging currencies by employing asymmetric domains of time and frequency spanning March 2011 to January 2022. We first notice bidirectional interconnectedness (both positive and negative) among three clusters of sampled exchange rates. The currency contagions follow divergent directions during crisis periods. During US debt selling crisis, there is a short-run negative contagion pointing to the appreciation of currencies. Following the Chinese financial market crisis, emerging market currencies demonstrated devaluation. There is long-run positive contagion (devaluation) in response to European Debt Crisis, Russian Ruble Crisis, Brazilian economic crisis, and Argentinian monetary crisis. The sampled exchange rates demonstrate negative long-run connectedness (appreciation) after COVID-19. The major transmitters to total connectedness are South Africa, Poland, and Mexico and major receivers include Thailand, the Philippines, Malaysia, India, Indonesia, and Egypt. In the long run, China is emerging as a significant transmitter. Our study draws significant policy and practical implications for regulators, investors, and financial market participants.

Volatility forecasting with Hybrid‐long short‐term memory models: Evidence from the COVID‐19 period

AbstractVolatility forecasting, a central issue in financial risk modelling and management, has attracted increasing attention after several major financial market crises. In this article, we draw upon the literature on volatility forecasting and hybrid models to construct the Hybrid‐long short‐term memory (LSTM) models to forecast the intraday realized volatility in three major US stock indexes. We construct the hybrid models by combining one or multiple traditional time series models with the LSTM model, and incorporating either the estimated parameters, or the predicted volatility, or both from the statistical models as additional input values into the LSTM model. We perform the out‐of‐sample test of our Hybrid‐LSTM models in volatility forecasting during the coronavirus disease 2019 (COVID‐19) period. Empirical results show that the Hybrid‐LSTM models can still significantly improve the volatility forecasting performance of the LSTM model during the COVID‐19 period. By analysing how the construction methods may influence the forecasting performance of the Hybrid‐LSTM models, we provide some suggestions on their design. Finally, we identify the optimal Hybrid‐LSTM model for each stock index and compare its performance with the LSTM model on each day during our sample period. We find that the Hybrid‐LSTM models' great capability of capturing market dynamics explains their good performance in forecasting.

Monetary and Fiscal Policy in Times of Crises: A New Keynesian Perspective in Continuous Time

To analyse the interdependence between monetary and fiscal policy during a financial crisis, we develop an open-economy DSGE model with monetary and fiscal policy as well as financial markets in a continuous-time framework based on stochastic differential equations. Monetary policy is modelled using both a standard and a modified Taylor rule and fiscal policy is modelled as either expansionary or austere. In addition, we differentiate between open economies and monetary union members. We find evidence that the modified Taylor rule notably reduces the likelihood that the financial market crisis affects the real economy. But if we assume that households are averse with respect to outstanding government debt, we find that a combination of expansionary monetary policy and austere fiscal policy provides better stabilisation of both domestic and foreign economies in terms of both output and inflation. In the case of a monetary union, we find that stabilisation of output in the country where the financial shock originates is no longer as easy and, in terms of prices, there is now deflation in the country where the crisis originated and a positive inflation rate in the other country.

世界金融市场危机的发展与现状

世界金融市场危机的发展与现状

ESG performance and stock prices: evidence from the COVID-19 outbreak in China

This paper investigates the role of environmental, social, and governance (ESG) performance in stock prices during the market financial crisis caused by the COVID-19 pandemic. We use the Chinese listed company data as the bases for adopting an event-study method to identify the impact of ESG performance on cumulative abnormal returns. Empirical results suggest that ESG performance significantly increases firms’ cumulative abnormal returns and has asymmetric effects during the pandemic. Our results are robust to various robustness checks that consider the replacement of event window period, ESG measurement, adding other control variables, and sample exclusion of Hubei Province. We further find that reputation and insurance effects are important mechanisms through which ESG performance influences stock prices. Lastly, heterogeneous analyses show that ESG effects are considerably pronounced among firms with low human capital and bad image and in high-impact regions.

Design and Application of a Financial Distress Early Warning Model Based on Data Reasoning and Pattern Recognition

Since the 1990s, emerging market financial crises have occurred frequently, causing huge damage to the real economy, and if we cannot find effective means of early warning and prevention of financial crises, the entire international economy and society will bear the high costs of crisis management. Difference nonparametric test and Spearman nonparametric correlation analysis were carried out with cash flow financial data, and 14 financial indicators with strong discriminant ability were selected from 28 financial indicators as the input variables of the model. Due to the limitations of traditional statistical methods, a BP neural network financial distress early warning model is established. Finally, a particle swarm optimization BP neural network financial early warning model is established for the shortcomings of the BP network. These 14 indicators can have strong information timeliness. The prediction accuracy rates of the two early warning models for the test samples are 80% and 85%, respectively. The empirical results show that the two models have good prediction effects. The prediction effect of the swarm optimization BP neural network model is better than that of the BP neural network model. Therefore, the particle swarm optimization BP neural network model proposed in this paper is suitable for solving the problem of discrimination and prediction of the financial distress of enterprises. The company’s financial distress early warning has good application prospects and application value. Therefore, it has very important research significance for the early warning of the corporate financial crisis.

CUSTOMER EXPECTATIONS IN THE GERMAN BANKING SECTOR

The last financial market crisis, which affected the whole world in 2008, brought about major changes. As a result of this crisis, customers have become more suspicious and since then the banks have been constantly being prescribed new regulations and controls for supervision. History shows that crises repeat themselves, so that companies always had to adapt to the times and changing requirements. Due to the rapid change in the financial services offered, national borders are being overcome. The boundaries of conventional market segments are eliminated and new products are created. The challenge for the money industry is growing with new providers, like Fintechs, and products and throughout all those changes customers adapt their expectations and their satisfaction might be affected.

Official fiscal forecasts in EU member states under the European Semester and Fiscal Compact – An empirical assessment

The efficacy of official forecasts in the EU has been under the spotlight since the introduction of the euro, with biases widely reported prior to the 2008–12 financial and sovereign bond market crisis. Changes to the EU fiscal rules and procedures, in the form of the European Semester and Fiscal Compact, in the early 2010s were adopted to improve forecasting, including through providing a role for independent fiscal institutions. Using data for 22 countries between 2013 and 2019, this paper shows that, despite these changes, biases, of a pessimistic form, remain in forecasts of budget balance and output variables in Stability and Convergence Programmes and the European Commission's Spring Forecasts. Econometric analysis indicates forecast errors in both the headline budget balance and the structural budget balance being explained by forecast errors in output variables and by EU fiscal rule requirements. Member states under an excessive deficit procedure provide optimistic headline budget balance forecasts compared to non-EDP countries, while those that have not met their medium-term objective report smaller forecast errors for the structural budget balance. Independent fiscal institutions are linked to a smaller bias to forecasts of the structural budget balance but have no effect on the forecast errors of the headline budget balance.

Asymmetric connectedness across Asia-Pacific currencies: Evidence from time-frequency domain analysis

We estimate the asymmetric time- and frequency connectedness across 11 Asia-Pacific exchange rates using daily data from Jan 1995 to Mar 2021. Our results reveal that in terms of static spillover, Asia-Pacific currencies are mainly disconnected except Australian Dollar and Singapore Dollar during normal times. The currencies form contagions during crisis periods. The currencies form positive and negative clusters during both short and long run. In terms of time-domain spillover, the pattern of daily return connectedness shows that the currencies of developed (emerging) economies are net transmitters (receivers) of shocks. We observe positive short run contagions (devaluation) of sampled currencies during Asian Financial Crisis and COVID19 pandemic. There are negative (appreciation) long run spillovers during Argentinean debt crisis and Chinese financial market crisis and positive long run contagions during Global Financial Crisis. The study carries important implications for policy makers and investors.

Cash demand in times of crisis

This paper focuses on the role of specific types of crisis (technological crisis, financial market crisis, natural disaster) and their effects on the demand for cash in an international context. As evidence from the last 30 years shows, demand for cash increases during periods of crisis, regardless of the nature of the crisis. The nature of the crisis does, however, determine whether small or large banknote denominations are affected more. This study finds that times of payment uncertainties are associated with increased demand for small denominations, probably reflecting an elevated demand for transaction balances. By contrast, in times of financial crisis or general economic uncertainty, the increased demand for cash is largely the result of consumers taking precautionary actions and building up non-transaction balances; for this reason, there is greater demand for large banknote denominations. This study finds that cash continues to play an important role in crisis management. Whether this function can also be fulfilled by a future central bank digital currency, however, remains to be seen.

清末 金融危機와 海關銀號의 倒産-天津의 津海關을 중심으로-

This study analyzed the process that the financial market crisis in the late Qing Dynasty threatened the stability of customs administration through the Jin Haiguan (津海關, a customs office) in Tianjin, China. The proxy tax collection structure of customs in the Qing Dynasty was a device to manage the costs and risks produced in the procedure of administration by the tax collection authorities. The tax collection contractors were guaranteed the right to operate customs duties in return for participating in the tax collection business. After the disintegration of the Canton system, the Qing Dynasty installed Customs banks, superseding the Hong merchants who were in charge of the tax collection contracting business during the early period. The tax collection was delegated to operators selected by the Superintendents. The late tax collection contracting business was led by Qianzhuang and Yin hao (錢莊, 銀號, traditional Chinese banking institutions), which were engaged in the conventional financial industry. As the Customs banks profited from loans and receipts based on the right to operate tax revenue, the financial market conditions significantly affected their profitability. The two financial crises in Tianjin in the 1900s distinctly implicated the adverse imp act of market changes on the stability of the Customs banks’ ta x collection structure. The first was damage to the Customs banks due to the deterioration of currency quality. As a result of the tax collection contractors taking on the risk of customs administration, the Qing Dynasty maintained stable tax revenue, while the profitability of the Customs banks was inevitably degraded. The second was the prospect of bankruptcy as the financial environment was aggravated. The Customs banks’ stability and profitability through managing considerable quantities of tax revenue through financial activities were destined to suffer a severe blow when market liquidity was restricted. The first crisis succeeded in early settlement through the active intervention of the Qing Dynasty. The local authorities normalized the currency quality, and the market immediately stabilized. However, the second crisis rendered the Qing dynasty unable to address due to the aftermath of the revolution, precipitating the collapse of the financial market in Tianjin. According to the nature of the financial market in the late Qing Dynasty based on the credit economy, the bankruptcies of financial institutions generated a chain reaction, and financial institutions that had direct or indirect claim-obligation relationship with a Customs bank A in Tianjin started to fail as well. Nonetheless, in the second crisis, the Qing Dynasty did not protect the Customs banks but instead reclaimed Liu Feng bank’s right to operate the Customs banks and transferred it to HSBC. Although the local government showed an active move to support the Customs banks in the unstable market situation, it was to thoroughly ensure the stability of the tax revenue administration. Under the circumstances where the possibility of A’s bankruptcy increased, the tax collection authority decided to replace the tax collection contractors rather than bear the risk. It was a typical coping mechanism of the bureaucracy, which prioritized the stability of customs administration.